TMTpro reagents: a set of isobaric labeling mass tags enables simultaneous proteome-wide measurements across 16 samples

A Multipoint Validation of Quantification in Capillary Electrophoresis Mass Spectrometry Proteomics: Isobaric Multiplexing with Tandem Mass Tags

Multiplexing quantification using isobaric barcoding has gained traction in trace-sensitive and single-cell mass spectrometry (MS), both in nanoflow liquid chromatography (nanoLC) and capillary electrophoresis (CE). In nanoLC-MS, ratio compression from isobaric interferences is known to challenge quantification accuracy during tandem MS (MS2), which is effectively remedied using simultaneous precursor selection (SPS) MS3. Despite mounting interest in CE-MS for trace-sensitive bottom-up proteomics, the fidelity of multiplexed quantification is unknown using this technology. Here, we address this fundamental knowledge gap by holistically investigating quantification depth, reproducibility, and accuracy using a validated mouse-yeast two-proteome model. CE-based quantification via the MS2 and SPS-MS3 strategies were benchmarked against the nanoLC SPS-MS3 gold standard. We found electrophoresis-correlative (Eco) ion sorting to order peptides into high-flux transients of nominally isobaric m/z values (Δm/z < 1-2 Th). While the MS2 approach struggled with ratio distortion, the SPS-MS3 robustly eliminated them for both separations. The reproducibility and accuracy proved indistinguishable between CE and nanoLC using MS2 or SPS-MS3 quantification. CE enhanced the depth of quantification by ∼12-fold. These analytical insights can be used to design trace CE-MS studies with high scientific rigor.

Proteomics and physiologic analysis reveal different response strategies to cadmium stress in Lentinula edodes

Lentinula edodes (L. edodes) is the second most widely cultivated edible mushroom worldwide. However, it has the ability to accumulate cadmium (Cd), which poses significant health risks. Despite its significance, the protein-level response mechanisms to Cd stress remain insufficiently understood. This study aims to investigate the differential responses of the low-Cd-accumulating strain Le4606 and the high-Cd-accumulating strain Le4625 under Cd stress by biochemical and proteomic methodologies. The results indicate that Le4625 exhibits enhanced Cd absorption, proline accumulation, and vacuolar sequestration for detoxification, with ZRC1 detected exclusively at 7 h. Conversely, Le4606 demonstrates proficiency in glutathione-mediated detoxification, thioredoxin antioxidant activity, tricarboxylic acid cycle activity, autophagy, and Cd extrusion. Overall, vacuolar sequestration and glutathione-mediated detoxification are important for the differences in Cd accumulation. The distinct response strategies offer valuable insights into the underlying mechanisms of Cd accumulation. This research establishes a theoretical foundation for the breeding of low-Cd-accumulating cultivars, benefiting human health.

Temporal Proteomic Profiling of Pheromone-Induced Cell Cycle Re-Entry in Saccharomyces cerevisiae

The regulation of cell cycle progression in response to environmental cues is essential for cellular adaptation. In Saccharomyces cerevisiae, the BAR1 gene modulates sensitivity to the mating pheromone α-factor, which induces cell cycle arrest in G1. Here, we investigated the dynamic proteomic response in the bar1 deletion strain using a 27-plex experimental design with TMTproD isobaric labeling. Asynchronous bar1Δ cells were treated with α-factor and then released from the pheromone-induced cell cycle arrest in G1. Using higher-order TMTpro sample multiplexing, we generated global temporal profiles of protein abundance associated with recovery from this arrest, with triplicate samples collected at eight time points from 0 to 165 min after washing out the pheromone. We identify specific proteins involved in cell cycle re-entry and in the attenuation of the pheromone signal, providing insights into the regulatory mechanisms of mating response in yeast. This study also contributes significantly to dynamic proteomic analysis of cell cycle progression. We present a versatile approach for investigating complex cellular processes and showcase cell cycle progression following release from pheromone-induced arrest in yeast.

High-Throughput Workflow for Detergent-free Cell-Based Proteomic Characterization

We have developed an automated cell-based workflow for the quantification of proteins by liquid chromatography-mass spectrometry (LC-MS) that facilitates large-scale perturbation studies carried out in a 96-well plate format and enables the preparation of one full plate in approximately 4 h, showcasing a high-throughput (HTP) concept. Cells were grown in a 96-well plate and lysed via ultrasonication. Proteins were subsequently solubilized, extracted, and processed into tryptic peptides for 2 h before being acquired by data-independent acquisition mass spectrometry (DIA-MS). This workflow leverages adaptive focused acoustics (AFA) technology for ultrasonication to aid cell lysis and protein solubilization on an automated liquid handling platform. As proof of principle, AC16 human cardiomyocyte-like cells were cultured in a 96-well plate under optimized conditions that were compatible with the downstream HTP pipeline. Over 30,000 peptides were identified, corresponding to the detection of 5100 unique proteins. 50% of measured proteins had an average coefficient of variation (CV) under 25% from approximately 30,000 cells. Our optimized detergent-free buffer consisting of ammonium bicarbonate yielded comparable findings. For the same number of cells, 5000 proteins were identified from 29,000 peptides, 40% of which demonstrated a CV under 25%.

Turnover atlas of proteome and phosphoproteome across mouse tissues and brain regions

Understanding how proteins in different mammalian tissues are regulated is central to biology. Protein abundance, turnover, and post-translational modifications such as phosphorylation are key factors that determine tissue-specific proteome properties. However, these properties are challenging to study across tissues and remain poorly understood. Here, we present Turnover-PPT, a comprehensive resource mapping the abundance and lifetime of 11,000 proteins and 40,000 phosphosites in eight mouse tissues and various brain regions using advanced proteomics and stable isotope labeling. We reveal tissue-specific short- and long-lived proteins, strong correlations between interacting protein lifetimes, and distinct impacts of phosphorylation on protein turnover. Notably, we discover a remarkable pattern of turnover changes for peroxisome proteins in specific tissues and that phosphorylation regulates the stability of neurodegeneration-related proteins, such as Tau and α-synuclein. Thus, Turnover-PPT provides fundamental insights into protein stability, tissue dynamic proteotypes, and functional protein phosphorylation and is accessible via an interactive web-based portal at https://yslproteomics.shinyapps.io/tissuePPT.

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.

Boosting the Sensitivity of Quantitative Single-Cell Proteomics with Infrared-Tandem Mass Tags

Single-cell proteomics is a powerful approach to precisely profile protein landscapes within individual cells toward a comprehensive understanding of proteomic functions and tissue and cellular states. The inherent challenges associated with limited starting material demand heightened analytical sensitivity. Just as advances in sample preparation maximize the amount of material that makes it from the cell to the mass spectrometer, we strive to maximize the number of ions that make it from ion source to the detector. In isobaric tagging experiments, limited reporter ion generation limits quantitative accuracy and precision. The combination of infrared photoactivation and ion parking circumvents the m/z dependence inherent in HCD, maximizing reporter generation and avoiding unintended degradation of TMT reporter molecules in infrared-tandem mass tags (IR-TMT). The method was applied to single-cell human proteomes using 18-plex TMTpro, resulting in 4-5-fold increases in reporter signal compared to conventional SPS-MS3 approaches. IR-TMT enables faster duty cycles, higher throughput, and increased peptide identification and quantification. Comparative experiments showcase 4-5-fold lower injection times for IR-TMT, providing superior sensitivity without compromising accuracy. In all, IR-TMT enhances the dynamic range of proteomic experiments and is compatible with gas-phase fractionation and real-time searching, promising increased gains in the study of cellular heterogeneity.

Monitoring Functional Posttranslational Modifications Using a Data-Driven Proteome Informatic Pipeline

Posttranslational modifications (PTMs) are of significant interest in molecular biomedicine due to their crucial role in signal transduction across various cellular and organismal processes. Characterizing PTMs, distinguishing between functional and inert modifications, quantifying their occupancies, and understanding PTM crosstalk are challenging tasks in any biosystem. Studying each PTM often requires a specific, labor-intensive experimental design. Here, we present a PTM-centric proteome informatic pipeline for predicting relevant PTMs in mass spectrometry-based proteomics data without prior information. Once predicted, these in silico identified PTMs can be incorporated into a refined database search and compared to measured data. As a practical application, we demonstrate how this pipeline can be used to study glycoproteomics in oral squamous cell carcinoma based on the proteome profile of primary tumors. Subsequently, we experimentally identified cellular proteins that are differentially expressed in cells treated with multikinase inhibitors dasatinib and staurosporine using mass spectrometry-based proteomics. Computational enrichment analysis was then employed to determine the potential PTMs of differentially expressed proteins induced by both drugs. Finally, we conducted an additional round of database search with the predicted PTMs. Our pipeline successfully analyzed the enriched PTMs, and detected proteins not identified in the initial search. Our findings support the effectiveness of PTM-centric searching of MS data in proteomics based on computational enrichment analysis, and we propose integrating this approach into future proteomics search engines.

Ergothioneine controls mitochondrial function and exercise performance via direct activation of MPST

Ergothioneine (EGT) is a diet-derived, atypical amino acid that accumulates to high levels in human tissues. Reduced EGT levels have been linked to age-related disorders, including neurodegenerative and cardiovascular diseases, while EGT supplementation is protective in a broad range of disease and aging models. Despite these promising data, the direct and physiologically relevant molecular target of EGT has remained elusive. Here, we use a systematic approach to identify how mitochondria remodel their metabolome in response to exercise training. From these data, we find that EGT accumulates in muscle mitochondria upon exercise training. Proteome-wide thermal stability studies identify 3-mercaptopyruvate sulfurtransferase (MPST) as a direct molecular target of EGT; EGT binds to and activates MPST, thereby boosting mitochondrial respiration and exercise training performance in mice. Together, these data identify the first physiologically relevant EGT target and establish the EGT-MPST axis as a molecular mechanism for regulating mitochondrial function and exercise performance.

Isobaric Labeling Update in MaxQuant

We present an update of the MaxQuant software for isobaric labeling data and evaluate its performance on benchmark data sets. Impurity correction factors can be applied to labels mixing C- and N-type reporter ions such as TMT Pro. Application to a single-cell multispecies mixture benchmark shows the high accuracy of the impurity-corrected results. TMT data recorded with FAIMS separation can be analyzed directly in MaxQuant without splitting the raw data into separate files per FAIMS voltage. Weighted median normalization is applied to several data sets, including large-scale human body atlas data. In the benchmark data sets, the weighted median normalization either removes or strongly reduces the batch effects between different TMT plexes and results in clustering by biology. In data sets including reference channels, we find that weighted median normalization performs as well or better when the reference channels are ignored and only the sample channel intensities are used, suggesting that the measurement of reference channels is unnecessary when using weighted median normalization in MaxQuant. We demonstrate that MaxQuant including the weighted median normalization performs well on multinotch MS3 data, as well as on phosphorylation data. MaxQuant is freely available for any purpose and can be downloaded from https://www.maxquant.org/.

Identification of molecular determinants of gene-specific bursting patterns by high-throughput imaging screens

Stochastic transcriptional bursting is a universal property of active genes. While different genes exhibit distinct bursting patterns, the molecular mechanisms that govern gene-specific stochastic bursting are largely unknown. We have developed a high-throughput-imaging-based screening strategy to identify cellular factors that determine the bursting patterns of native genes in human cells. We identify protein acetylation as a prominent effector of burst frequency and burst size acting via decreasing off-times and gene-specific changes in the on-time. These effects are not correlated with promoter acetylation. Instead, we demonstrate acetylation of the Integrator complex as a key determinant of gene bursting that alters Integrator interactions with transcription elongation and RNA processing factors but without affecting pausing. Our results suggest a prominent role for non-histone acetylation of a transcription cofactors as a mechanism for modulation of bursting via a far-downstream checkpoint.

RBM43 controls PGC1α translation and a PGC1α-STING signaling axis

Obesity is associated with systemic inflammation that impairs mitochondrial function. This disruption curtails oxidative metabolism, limiting adipocyte lipid metabolism and thermogenesis, a metabolically beneficial program that dissipates chemical energy as heat. Here, we show that PGC1α, a key governor of mitochondrial biogenesis, is negatively regulated at the level of its mRNA translation by the RNA-binding protein RBM43. RBM43 is induced by inflammatory cytokines and suppresses mitochondrial biogenesis in a PGC1α-dependent manner. In mice, adipocyte-selective Rbm43 disruption elevates PGC1α translation and oxidative metabolism. In obesity, Rbm43 loss improves glucose tolerance, reduces adipose inflammation, and suppresses activation of the innate immune sensor cGAS-STING in adipocytes. We further identify a role for PGC1α in safeguarding against cytoplasmic accumulation of mitochondrial DNA, a cGAS ligand. The action of RBM43 defines a translational regulatory axis by which inflammatory signals dictate cellular energy metabolism and contribute to metabolic disease pathogenesis.

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.

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.

Development of an Adaptive, Economical, and Easy-to-Use SP3-TMT Automated Sample Preparation Workflow for Quantitative Proteomics

Liquid handling robots have been developed to automate various steps of the bottom-up proteomics workflow, however, protocols for the generation of isobarically labeled peptides remain limited. Existing methods often require costly specialty devices and are constrained by fixed workflows. To address this, we developed a cost-effective, flexible, automated sample preparation protocol for TMT-labeled peptides using the Biomek i5 liquid handler. Our approach leverages Single-Pot Solid-Phase-Enhanced Sample Preparation (SP3) with paramagnetic beads to streamline protein cleanup and digestion. The protocol also allows for adjustment of trypsin concentration and peptide-to-TMT ratio to increase throughput and reduce costs, respectively. We compared our automated and manual 18-plex TMT-Pro labeling workflows by monitoring select protein markers of the Unfolded Protein Response (UPR) in pharmacologically activatable, engineered cell lines. Overall, the automated protocol demonstrated equivalent performance in peptide and protein identifications, digestion and labeling efficiency, and an enhancement in the dynamic range of TMT quantifications. Compared to the manual method, the Biomek protocol significantly reduces hands-on time and minimizes sample handling errors. The 96-well format additionally allows for the number of TMT reactions to be scaled up quickly without a significant increase in user interaction. Our optimized automated workflow enhances throughput, reproducibility, and cost-effectiveness, making it a valuable tool for high-throughput proteomics studies.

4-plex quantitative glycoproteomics using glycan/protein-stable isotope labeling in cell culture

Alterations in glycoprotein abundance and glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics is pivotal for biomarker discovery, but comprehensive analysis within biological samples remains challenging due to low abundance, complexity, and lack of universal technology. We developed a multiplex glycoproteomic approach using an LC-ESI-MS platform for direct comparison of glycoproteomic quantitation. Glycopeptides were isotopically labeled during cell culture, achieving high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation was validated by mixing the same cell line in a 1:1:1:1 ratio, with mathematical correction applied to deconvolute the ratios. This method proved reliable and was applied to a comparative glycoproteomic study of three breast cancer cell lines (HTB22, MDA-MB-231, MDA-MB-231BR) and one brain cancer cell line (CRL-1620), quantifying glycopeptides from three replicates. The expression of glycopeptides was relatively quantified, and up/down-regulation between cell lines was investigated. This approach provided insights into glycosylation microheterogeneity, crucial for breast cancer brain metastasis research. Benefits include eliminating fluctuations from nano electrospray ionization and reducing analysis time, enabling up to 4-plex profiling in a single injection. Metabolic labeling introduced mass differences at the MS1 level, ensuring increased sensitivity and higher resolution for accurate quantitation. SIGNIFICANCE: Alternations in glycoprotein abundance, changes in glycosylation levels, and variations in glycan structures are closely linked to numerous diseases. The quantitative exploration of glycoproteomics has emerged as a popular area of research for biomarker discovery. However, conducting a comprehensive quantitative analysis of the glycoproteome within biological samples remains challenging due to low abundance, inherent complexities, and the absence of universal quantitative technology. Here, we developed a multiplex glycoproteomic approach using an LC-ESI-MS platform to facilitate direct comparison of glycoproteomic quantitation and enhance throughput. This approach offers benefits such as eliminating quantitative fluctuations arising from nano electrospray ionization (ESI) and reducing analysis time, enabling up to 4-plex glycoproteomic profiling in a single injection. Glycopeptides were stable isotopic labeled during cell culture procedure, attaching to monosaccharides, amino acids, or both. We achieved a high labeling efficiency (≥ 95 %) for both glycans and peptides. Quantitation validation was tested on glycopeptides by mixing the same cell line with 1:1:1:1 ratio. Due to the overlapped isotopes, a mathematical correction was applied to deconvolute the ratio of 4-plex glycopeptides. This method demonstrated quantitative reliability and was successfully applied to a comparative glycoproteomic study of three breast cancer cells (HTB22, MDA-MB-231, and MDA-MB-231BR) and one brain cancer cell (CRL-1620), identifying a total of 264 glycopeptides from three replicates. The expression of glycopeptides among these four cells was relatively quantified and up/down-regulation between two cell lines was investigated. The exploration of glycosylation microheterogeneity through glycopeptide quantification may offer valuable insights for further investigation into breast cancer brain metastasis. Conclusion: The primary advantage of our presented work lies in the multiplexing offered by combining two established labeling techniques, SILAC and IDAWG, both of which have been effectively used and widely cited in the scientific community. This combination enhances the applicability and accuracy of our method, as demonstrated by the extensive citations and successful use of these techniques independently. We believe that this multiplexing approach significantly advances the field, despite the method's current limitation to cell systems.

Multiomics Approach Identifies Key Proteins and Regulatory Pathways in Colorectal Cancer

The prevalence rate of colorectal cancer (CRC) has dramatically increased in recent decades. However, robust CRC biomarkers with therapeutic value for early diagnosis are still lacking. To comprehensively reveal the molecular characteristics of CRC development, we employed a multiomics strategy to investigate eight different types of CRC samples. Proteomic analysis revealed 2022 and 599 differentially expressed tissue proteins between CRC and control groups in CRC patients and CRC mice, respectively. In patients with colorectal precancerous lesions, 25 and 34 significantly changed proteins were found between patients and healthy controls in plasma and white blood cells, respectively. Notably, vesicle-associated membrane protein-associated protein A (VAPA) was found to be consistently and significantly decreased in most types of CRC samples, and its level was also significantly correlated with increased overall survival of CRC patients. Furthermore, 37 significantly enriched pathways in CRC were further validated via metabolomics analysis. Ten VAPA-related pathways were found to be significantly enriched in CRC samples, among which PI3K-Akt signaling, central carbon metabolism in cancer, cholesterol metabolism, and ABC transporter pathways were also enriched in the premalignant stage. Our study identified VAPA and its associated pathways as key regulators, suggesting their potential applications in the early diagnosis and prognosis of CRC.

Robust proteome profiling of cysteine-reactive fragments using label-free chemoproteomics

Identifying pharmacological probes for human proteins represents a key opportunity to accelerate the discovery of new therapeutics. High-content screening approaches to expand the ligandable proteome offer the potential to expedite the discovery of novel chemical probes to study protein function. Screening libraries of reactive fragments by chemoproteomics offers a compelling approach to ligand discovery, however, optimising sample throughput, proteomic depth, and data reproducibility remains a key challenge. We report a versatile, label-free quantification proteomics platform for competitive profiling of cysteine-reactive fragments against the native proteome. This high-throughput platform combines SP4 plate-based sample preparation with rapid chromatographic gradients. Data-independent acquisition performed on a Bruker timsTOF Pro 2 consistently identified ~23,000 cysteine sites per run, with a total of ~32,000 cysteine sites profiled in HEK293T and Jurkat lysate. Crucially, this depth in cysteinome coverage is met with high data completeness, enabling robust identification of liganded proteins. In this study, 80 reactive fragments were screened in two cell lines identifying >400 ligand-protein interactions. Hits were validated through concentration-response experiments and the platform was utilised for hit expansion and live cell experiments. This label-free platform represents a significant step forward in high-throughput proteomics to evaluate ligandability of cysteines across the human proteome.

Advancements in Single-Cell Proteomics and Mass Spectrometry-Based Techniques for Unmasking Cellular Diversity in Triple Negative Breast Cancer

BACKGROUND

Triple-negative breast cancer (TNBC) is an aggressive and complex subtype of breast cancer characterized by a lack of targeted treatment options. Intratumoral heterogeneity significantly drives disease progression and complicates therapeutic responses, necessitating advanced analytical approaches to understand its underlying biology. This review aims to explore the advancements in single-cell proteomics and their application in uncovering cellular diversity in TNBC. It highlights innovations in sample preparation, mass spectrometry-based techniques, and the potential for integrating proteomics into multi-omics platforms.

METHODS

The review discusses the combination of improved sample preparation methods and cutting-edge mass spectrometry techniques in single-cell proteomics. It emphasizes the challenges associated with protein analysis, such as the inability to amplify proteins akin to transcripts, and examines strategies to overcome these limitations.

RESULTS

Single-cell proteomics provides a direct link to phenotype and cell behavior, complementing transcriptomic approaches and offering new insights into the mechanisms driving TNBC. The integration of advanced techniques has enabled deeper exploration of cellular heterogeneity and disease mechanisms.

CONCLUSION

Despite the challenges, single-cell proteomics holds immense potential to evolve into a high-throughput and scalable multi-omics platform. Addressing existing hurdles will enable deeper biological insights, ultimately enhancing the diagnosis and treatment of TNBC.

Optimal Sample Preparation Workflow for Quantitative Mass Spectrometry-Based Studies in the Low Range

Mass spectrometry (MS) enables the high-throughput characterization of thousands of proteins in one single run. Nowadays, advances in the field have allowed for deep analysis of low cell numbers, even reaching the single-cell level. However, standardized protocols are still needed in this regard, especially oriented for non-proteomics specialists. Here we detail a reproducible, easy-to-implement workflow for cell-limited sample preparation, from cell storage to peptide labelling, for further TMT-based relative quantitative MS-based analysis.

Improving Glycoproteomic Analysis Workflow by Systematic Evaluation of Glycopeptide Enrichment, Quantification, Mass Spectrometry Approach, and Data Analysis Strategies

Glycosylation is one of the most prevalent and crucial protein modifications. Quantitative site-specific characterization of glycosylation usually requires sophisticated intact glycopeptide analysis using glycoproteomics. Recent efforts have focused on the interrogation of intact glycopeptide analyses using tandem mass spectrometry. However, a systematic evaluation of the quantitative glycoproteomic workflow is still lacking. This study compared different strategies for glycopeptide enrichment alongside glycopeptide quantitation, as well as mass spectrometry and data analysis strategies, providing a comprehensive assessment of their efficacy. The ZIC-HILIC enrichment method demonstrated superior performance, representing a 26% improvement in identified glycopeptiudes compared to the MAX enrichment method. Quantification using TMT provided high precision and throughput with an average CV of 8%. Through systematic evaluation, this study established that the ZIC-HILIC enrichment method, quantification with TMT, and collision energies of 25, 35, and 45 using tandem mass spectrometry are the optimal workflow for higher-energy collisional dissociation (HCD) fragmentation, significantly enhancing the analysis of intact glycopeptides. Precise energy adjustment is crucial for the identification of certain glycans. Intact glycopeptides were analyzed using different software tools to investigate the identification and quantification of glycopeptides. By applying optimal settings, 5514 unique intact glycopeptides were in luminal and basal patient-derived xenograft (PDX) characterized models, highlighting distinct glycosylation profiles that may influence tumor behavior. This study offers a systematic approach to evaluate glycoproteomic analysis workflow.

Organ-specific electrophile responsivity mapping in live C. elegans

Proximity labeling technologies are limited to indexing localized protein residents. Such data-although valuable-cannot inform on small-molecule responsivity of local residents. We here bridge this gap by demonstrating in live C. elegans how electrophile-sensing propensity in specific organs can be quantitatively mapped and ranked. Using this method, >70% of tissue-specific responders exhibit electrophile responsivity, independent of tissue-specific abundance. One responder, cyp-33e1-for which both human and worm orthologs are electrophile responsive-marshals stress-dependent gut functions, despite manifesting uniform abundance across all tissues studied. Cyp-33e1's localized electrophile responsivity operates site specifically, triggering multifaceted responses: electrophile sensing through the catalytic-site cysteine results in partitioning between enzyme inhibition and localized production of a critical metabolite that governs global lipid availability, whereas rapid dual-cysteine site-specific sensing modulates gut homeostasis. Beyond pinpointing chemical actionability within local proteomes, organ-specific electrophile responsivity mapping illuminates otherwise intractable locale-specific metabolite signaling and stress response programs influencing organ-specific decision-making.

SYNTAXIN OF PLANTS 132 underpins secretion of cargoes associated with salicylic acid signaling and pathogen defense

Secretory trafficking in plant cells is facilitated by SNARE (soluble N-ethylmaleimide-sensitive factor attachment protein receptor) proteins that drive membrane fusion of cargo-containing vesicles. In Arabidopsis, SYNTAXIN OF PLANTS 132 (SYP132) is an evolutionarily ancient SNARE that functions with syntaxins SYP121 and SYP122 at the plasma membrane. Whereas SYP121 and SYP122 mediate overlapping secretory pathways, albeit with differences in their importance in plant-environment interactions, the SNARE SYP132 is absolutely essential for plant development and survival. SYP132 promotes endocytic traffic of the plasma membrane H+-ATPase AHA1 and aquaporin PIP2;1, and it coordinates plant growth and bacterial pathogen immunity through PATHOGENESIS-RELATED1 (PR1) secretion. Yet, little else is known about SYP132 cargoes. Here, we used advanced quantitative tandem mass tagging (TMT)-MS combined with immunoblot assays to track native secreted cargo proteins in the leaf apoplast. We found that SYP132 supports a basal level of secretion in Arabidopsis leaves, and its overexpression influences salicylic acid and jasmonic acid defense-related cargoes including PR1, PR2, and PR5 proteins. Impairing SYP132 function also suppressed defense-related secretory traffic when challenged with the bacterial pathogen Pseudomonas syringae. Thus, we conclude that, in addition to its role in hormone-related H+-ATPase cycling, SYP132 influences basal plant immunity.

Expanding the Landscape of Aging via Orbitrap Astral Mass Spectrometry and Tandem Mass Tag (TMT) Integration

Aging results in a progressive decline in physiological function due to the deterioration of essential biological processes, such as transcription and RNA splicing, ultimately increasing mortality risk. Although proteomics is emerging as a powerful tool for elucidating the molecular mechanisms of aging, existing studies are constrained by limited proteome coverage and only observe a narrow range of lifespan. To overcome these limitations, we integrated the Orbitrap Astral Mass Spectrometer with the multiplex tandem mass tag (TMT) technology to profile the proteomes of three brain tissues (cortex, hippocampus, striatum) and kidney in the C57BL/6JN mouse model, achieving quantification of 8,954 to 9,376 proteins per tissue (cumulatively 12,749 across all tissues). Our sample population represents balanced sampling across both sexes and three age groups (3, 12, and 20 months), comprising young adulthood to early late life (approximately 20-60 years of age for human lifespan). To enhance quantitative accuracy, we developed a peptide filtering strategy based on resolution and signal-to-noise thresholds. Our analysis uncovered distinct tissue-specific patterns of protein abundance, with age and sex differences in the kidney, while brain tissues exhibit notable age changes and limited sex differences. In addition, we identified both proteomic changes that are linear with age (i.e., continuous) and that have a non-linear pattern (i.e., non-continuous), revealing complex protein dynamics over the adult lifespan. Integrating our findings with early developmental proteomic data from brain tissues highlighted further divergent age-related trajectories, particularly in synaptic proteins. This study not only provides a robust data analysis workflow for TMT datasets generated using the Orbitrap Astral mass spectrometer but also expands the proteomic landscape of aging, capturing proteins with age and sex effects with unprecedented depth.

SUMO-targeted Ubiquitin Ligases as crucial mediators of protein homeostasis in Candida glabrata

Candida glabrata is an opportunistic human pathogen, capable of causing severe systemic infections that are often resistant to standard antifungal treatments. To understand the importance of protein SUMOylation in the physiology and pathogenesis of C. glabrata, we earlier identified the components of SUMOylation pathway and demonstrated that the deSUMOylase CgUlp2 is essential for pathogenesis. In this work we show that the CgUlp2 is essential to maintain protein homeostasis via the SUMO-targeted ubiquitin ligase pathway. The dual loss of deSUMOylase and specific ubiquitin ligase, CgSlx8, results in heightened protein degradation, rendering the cells vulnerable to various stressors. This degradation affects crucial processes such as purine biosynthesis and compromises mitochondrial function in the mutants. Importantly, the absence of these ubiquitin ligases impedes the proliferation of C. glabrata in macrophages. These findings underscore the significance of SUMOylation and SUMO-mediated protein homeostasis as pivotal regulators of C. glabrata physiology and capacity to survive in host cells. Understanding these mechanisms could pave the way for the development of effective antifungal treatments.

High-throughput identification of calcium-regulated proteins across diverse proteomes

Calcium ions play important roles in nearly every biological process, yet whole-proteome analysis of calcium effectors has been hindered by a lack of high-throughput, unbiased, and quantitative methods to identify protein-calcium engagement. To address this, we adapted protein thermostability assays in budding yeast, human cells, and mouse mitochondria. Based on calcium-dependent thermostability, we identified 2,884 putative calcium-regulated proteins across human, mouse, and yeast proteomes. These data revealed calcium engagement of signaling hubs and cellular processes, including metabolic enzymes and the spliceosome. Cross-species comparison of calcium-protein engagement and mutagenesis experiments identified residue-specific cation engagement, even within well-known EF-hand domains. Additionally, we found that the dienoyl-coenzyme A (CoA) reductase DECR1 binds calcium at physiologically relevant concentrations with substrate-specific affinity, suggesting direct calcium regulation of mitochondrial fatty acid oxidation. These discovery-based proteomic analyses of calcium effectors establish a key resource to dissect cation engagement and its mechanistic effects across multiple species and diverse biological processes.

AI-empowered perturbation proteomics for complex biological systems

The insufficient availability of comprehensive protein-level perturbation data is impeding the widespread adoption of systems biology. In this perspective, we introduce the rationale, essentiality, and practicality of perturbation proteomics. Biological systems are perturbed with diverse biological, chemical, and/or physical factors, followed by proteomic measurements at various levels, including changes in protein expression and turnover, post-translational modifications, protein interactions, transport, and localization, along with phenotypic data. Computational models, employing traditional machine learning or deep learning, identify or predict perturbation responses, mechanisms of action, and protein functions, aiding in therapy selection, compound design, and efficient experiment design. We propose to outline a generic PMMP (perturbation, measurement, modeling to prediction) pipeline and build foundation models or other suitable mathematical models based on large-scale perturbation proteomic data. Finally, we contrast modeling between artificially and naturally perturbed systems and highlight the importance of perturbation proteomics for advancing our understanding and predictive modeling of biological systems.

Non-antibiotic pharmaceutical phenylbutazone binding to MexR reduces the antibiotic susceptibility of Pseudomonas aeruginosa

Antimicrobial resistance has been an increasingly serious threat to global public health. The contribution of non-antibiotic pharmaceuticals to the development of antibiotic resistance has been overlooked. Our study found that the anti-inflammatory drug phenylbutazone could protect P. aeruginosa against antibiotic mediated killing by binding to the efflux pump regulator MexR. In this study, antibiotic activity against P. aeruginosa alone or in combination with phenylbutazone was evaluated in vitro and in vivo. Resazurin accumulation assay, transcriptomic sequencing, and PISA assay were conducted to explore the underlying mechanism for the reduced antibiotic susceptibility caused by phenylbutazone. Then EMSA, ITC, molecular dynamic simulations, and amino acid substitutions were used to investigate the interactions between phenylbutazone and MexR. We found that phenylbutazone could reduce the susceptibility of P. aeruginosa to multiple antibiotics, including parts of β-lactams, fluoroquinolones, tetracyclines, and macrolides. Phenylbutazone could directly bind to MexR, then promote MexR dissociating from the mexA-mexR intergenic region and de-repress the expression of MexAB-OprM efflux pump. The overexpressed MexAB-OprM pump resulted in the reduced antibiotic susceptibility. And the His41 and Arg21 residues of MexR were involved in the phenylbutazone-MexR interaction. We hope this study would imply the potential risk of antibiotic resistance caused by non-antibiotic pharmaceuticals.

USP20 deletion promotes eccentric cardiac remodeling in response to pressure overload and increases mortality

Left ventricular hypertrophy (LVH) caused by chronic pressure overload with subsequent pathological remodeling is a major cardiovascular risk factor for heart failure and mortality. The role of deubiquitinases in LVH has not been well characterized. To define whether the deubiquitinase ubiquitin-specific peptidase 20 (USP20) regulates LVH, we subjected USP20 knockout (KO) and cognate wild-type (WT) mice to chronic pressure overload by transverse aortic constriction (TAC) and measured changes in cardiac function by serial echocardiography followed by histological and biochemical evaluations. USP20-KO mice showed severe deterioration of systolic function within 4 wk of TAC compared with WT cohorts. Both USP20-KO TAC and WT-TAC cohorts presented cardiac hypertrophy following pressure overload. However, USP20-KO-TAC mice showed an increase in cardiomyocyte length and developed maladaptive eccentric hypertrophy, a phenotype generally observed with volume overload states and decompensated heart failure. In contrast, WT-TAC mice displayed an increase in cardiomyocyte width, producing concentric remodeling that is characteristic of pressure overload. In addition, cardiomyocyte apoptosis, interstitial fibrosis, and mouse mortality were augmented in USP20-KO-TAC compared with WT-TAC mice. Quantitative mass spectrometry of LV tissue revealed that the expression of sarcomeric myosin heavy chain 7 (MYH7), a fetal gene normally upregulated during cardiac remodeling, was significantly reduced in USP20-KO after TAC. Mechanistically, we identified increased degradative lysine-48 polyubiquitination of MYH7 in USP20-KO hearts, indicating that USP20-mediated deubiquitination likely prevents protein degradation of MYH7 during pressure overload. Our findings suggest that USP20-dependent signaling pathways regulate the layering pattern of sarcomeres to suppress maladaptive remodeling during chronic pressure overload and prevent cardiac failure.NEW & NOTEWORTHY We identify ubiquitin-specific peptidase 20 (USP20) as an important enzyme that is required for cardiac homeostasis and function, particularly during myocardial pressure overload. USP20 regulates protein stability of cardiac MYH7, an essential molecular motor protein expressed in sarcomeres; loss-of-function mutations of MYH7 are associated with human hypertrophic cardiomyopathy, cardiac failure, and sudden death. Enhancing USP20 activity could be a potential therapeutic approach to prevent the development of maladaptive state of eccentric hypertrophy and heart failure.

Achieving a 35-Plex Tandem Mass Tag Reagent Set through Deuterium Incorporation

Mass spectrometry-based sample multiplexing with isobaric tags permits the development of high-throughput and precise quantitative biological assays with proteome-wide coverage and minimal missing values. Here, we nearly doubled the multiplexing capability of the TMTpro reagent set to a 35-plex through the incorporation of one deuterium isotope into the reporter group. Substituting deuterium frequently results in suboptimal peak coelution, which can compromise the accuracy of reporter ion-based quantification. To counteract the deuterium effect on quantitation, we implemented a strategy that necessitated the segregation of nondeuterium and deuterium-containing channels into distinct subplexes during normalization procedures, with reassembly through a common bridge channel. This multiplexing strategy of "design independent sub-plexes but acquire together" (DISAT) was used to compare protein expression differences between human cell lines and in a cysteine-profiling (i.e., chemoproteomics) experiment to identify compounds binding to cysteine-113 of Pin1.

Multiomic characterization of RNA microenvironments by oligonucleotide-mediated proximity-interactome mapping

RNA molecules form complex networks of molecular interactions that are central to their function and to cellular architecture. But these interaction networks are difficult to probe in situ. Here, we introduce Oligonucleotide-mediated proximity-interactome MAPping (O-MAP), a method for elucidating the biomolecules near an RNA of interest, within its native context. O-MAP uses RNA-fluorescence in situ hybridization-like oligonucleotide probes to deliver proximity-biotinylating enzymes to a target RNA in situ, enabling nearby molecules to be enriched by streptavidin pulldown. This induces exceptionally precise biotinylation that can be easily optimized and ported to new targets or sample types. Using the noncoding RNAs 47S, 7SK and Xist as models, we develop O-MAP workflows for discovering RNA-proximal proteins, transcripts and genomic loci, yielding a multiomic characterization of these RNAs' subcellular compartments and new regulatory interactions. O-MAP requires no genetic manipulation, uses exclusively off-the-shelf parts and requires orders of magnitude fewer cells than established methods, making it accessible to most laboratories.

Deletion of miR-33, a regulator of the ABCA1-APOE pathway, ameliorates neuropathological phenotypes in APP/PS1 mice

INTRODUCTION

Rare variants in ABCA1 increase the risk of developing Alzheimer's disease (AD). ABCA1 facilitates the lipidation of apolipoprotein E (apoE). This study investigated whether microRNA-33 (miR-33)-mediated regulation of this ABCA1-APOE pathway affects phenotypes of an amyloid mouse model.

METHODS

We generated mir-33+/+;APP/PS1 and mir-33-/-;APP/PS1 mice to determine changes in amyloid pathology using biochemical and histological analyses. We used RNA sequencing and mass spectrometry to identify the transcriptomic and proteomic changes between our genotypes. We also performed mechanistic experiments by determining the role of miR-33 in microglial migration and amyloid beta (Aβ) phagocytosis.

RESULTS

Mir-33 deletion increases ABCA1 levels and reduces Aβ accumulation and glial activation. Multi-omics studies suggested miR-33 regulates the activation and migration of microglia. We confirm that the inhibition of miR-33 significantly increases microglial migration and Aβ phagocytosis.

DISCUSSION

These results suggest that miR-33 might be a potential drug target by modulating ABCA1 level, apoE lipidation, Aβ level, and microglial function.

HIGHLIGHTS

Loss of microRNA-33 (miR-33) increased ABCA1 protein levels and the lipidation of apolipoprotein E. Loss of miR-33 reduced amyloid beta (Aβ) levels, plaque deposition, and gliosis. mRNAs and proteins dysregulated by miR-33 loss relate to microglia and Alzheimer's disease. Inhibition of miR-33 increased microglial migration and Aβ phagocytosis in vitro.

Proteomic analysis of the pyrenoid-traversing membranes of Chlamydomonas reinhardtii reveals novel components

Pyrenoids are algal CO2-fixing organelles that mediate approximately one-third of global carbon fixation and hold the potential to enhance crop growth if engineered into land plants. Most pyrenoids are traversed by membranes that are thought to supply them with concentrated CO2. Despite the critical nature of these membranes for pyrenoid function, they are poorly understood, with few protein components known in any species.• Here we identify protein components of the pyrenoid-traversing membranes from the leading model alga Chlamydomonas reinhardtii by affinity purification and mass spectrometry of membrane fragments. Our proteome includes previously-known proteins as well as novel candidates.• We further characterize two of the novel pyrenoid-traversing membrane-resident proteins, Cre10.g452250, which we name Pyrenoid Membrane Enriched 1 (PME1), and LCI16. We confirm their localization, observe that they physically interact, and find that neither protein is required for normal membrane morphology.• Taken together, our study identifies the proteome of pyrenoid-traversing membranes and initiates the characterization of a novel pyrenoid-traversing membrane complex, building toward a mechanistic understanding of the pyrenoid.

Labeled and Label-Free Target Identifications of Natural Products

Target identification, employing chemical proteomics, constitutes a continuous challenging endeavor in the drug development of natural products (NPs). Understanding their targets is crucial for deciphering their mechanisms and developing potential probes or drugs. Identifications fall into two main categories: labeled and label-free techniques. Labeled methods use the molecules tagged with markers such as biotin or fluorescent labels to easily detect interactions with target proteins. Thorough structure-activity relationships are essential before labeling to avoid changes in the biological activity or binding specificity. In contrast, label-free technologies identify target proteins without modifying natural products, relying on changes in the stability, thermal properties, or precipitation in the presence or absence of these products. Each approach has its advantages and disadvantages, offering a comprehensive understanding of the mechanisms and therapeutic potential of the NPs. Here, we summarize target identification techniques for natural molecules, highlight case studies of notable NPs, and explore future applications and directions.

Mimicking and analyzing the tumor microenvironment

The tumor microenvironment (TME) is increasingly appreciated to play a decisive role in cancer development and response to therapy in all solid tumors. Hypoxia, acidosis, high interstitial pressure, nutrient-poor conditions, and high cellular heterogeneity of the TME arise from interactions between cancer cells and their environment. These properties, in turn, play key roles in the aggressiveness and therapy resistance of the disease, through complex reciprocal interactions between the cancer cell genotype and phenotype, and the physicochemical and cellular environment. Understanding this complexity requires the combination of sophisticated cancer models and high-resolution analysis tools. Models must allow both control and analysis of cellular and acellular TME properties, and analyses must be able to capture the complexity at high depth and spatial resolution. Here, we review the advantages and limitations of key models and methods in order to guide further TME research and outline future challenges.

Mass Spectrometry-Based Proteomics for Assessing Epitranscriptomic Regulations

Epitranscriptomics is a rapidly evolving field that explores chemical modifications in RNA and how they contribute to dynamic and reversible regulations of gene expression. These modifications, for example, N6-methyladenosine (m6A), are crucial in various RNA metabolic processes, including splicing, stability, subcellular localization, and translation efficiency of mRNAs. Mass spectrometry-based proteomics has become an indispensable tool in unraveling the complexities of epitranscriptomics, offering high-throughput, precise protein identification, and accurate quantification of differential protein expression. Over the past two decades, advances in mass spectrometry, including the improvement of high-resolution mass spectrometers and innovative sample preparation methods, have allowed researchers to perform in-depth analyses of epitranscriptomic regulations. This review focuses on the applications of bottom-up proteomics in the field of epitranscriptomics, particularly in identifying and quantifying epitranscriptomic reader, writer, and eraser (RWE) proteins and in characterizing their functions, posttranslational modifications, and interactions with other proteins. Together, by leveraging modern proteomics, researchers can gain deep insights into the intricate regulatory networks of RNA modifications, advancing fundamental biology, and fostering potential therapeutic applications.

An Extensive Atlas of Proteome and Phosphoproteome Turnover Across Mouse Tissues and Brain Regions

Understanding how proteins in different mammalian tissues are regulated is central to biology. Protein abundance, turnover, and post-translational modifications like phosphorylation, are key factors that determine tissue-specific proteome properties. However, these properties are challenging to study across tissues and remain poorly understood. Here, we present Turnover-PPT, a comprehensive resource mapping the abundance and lifetime of 11,000 proteins and 40,000 phosphosites across eight mouse tissues and various brain regions, using advanced proteomics and stable isotope labeling. We revealed tissue-specific short- and long-lived proteins, strong correlations between interacting protein lifetimes, and distinct impacts of phosphorylation on protein turnover. Notably, we discovered that peroxisomes are regulated by protein turnover across tissues, and that phosphorylation regulates the stability of neurodegeneration-related proteins, such as Tau and α-synuclein. Thus, Turnover-PPT provides new fundamental insights into protein stability, tissue dynamic proteotypes, and the role of protein phosphorylation, and is accessible via an interactive web-based portal at https://yslproteomics.shinyapps.io/tissuePPT.

Investigation and Development of the BODIPY-Embedded Isotopic Signature for Chemoproteomics Labeling and Targeted Profiling

A common goal in mass spectrometry-based chemoproteomics is to directly measure the site of conjugation between the target protein and the small molecule ligand. However, these experiments are inherently challenging due to the low abundance of labeled proteins and the difficulty in identifying modification sites using standard proteomics software. Reporter tags that either generate signature fragment ions or isotopically encode target peptides can be used for the preemptive discovery of labeled peptides even in the absence of identification. We investigated the potential of BODIPY FL azide as a click chemistry enabled chemoproteomics reagent due to the presence of boron and the unique 1:4 natural abundance ratio of 10B:11B. The isotopes of boron encode BODIPY-labeled peptides with a predictable pattern between the monoisotopic (M) and M+1 peaks. BODIPY-labeled peptides were identified in MS1 spectra using an R script that filters for the signature 10B:11B intensity ratio and mass defect. Application of the boron detection script resulted in three times the labeled peptide coverage achieved for a BODIPY-conjugated BSA sample compared with untargeted data-dependent acquisition sequencing. Furthermore, we used the inherent HF neutral loss signature from BODIPY to assist with BODIPY-modified peptide identification. Finally, we demonstrate the application of this approach using the BODIPY-conjugated BSA sample spiked into a complex E. coli. digest. In summary, our results show that the commercially available BODIPY FL azide clicked to alkyne-labeled peptides provides a unique isotopic signature for pinpointing the site(s) of modification with the added potential for on- or off-line UV or fluorescence detection.

Enhanced Sample Multiplexing-Based Targeted Proteomics with Intelligent Data Acquisition

Targeted proteomics has been playing an increasingly important role in hypothesis-driven protein research and clinical biomarker discovery. We previously created a workflow, Tomahto, to enable real-time targeted pathway proteomics assays using two-dimensional multiplexing technology. Coupled with the TMT 11-plex reagent, hundreds of proteins of interest from up to 11 samples can be targeted and accurately quantified in a single-shot experiment with remarkable sensitivity. However, room remains to further improve the sensitivity, accuracy, and throughput, especially for targeted studies demanding a high peptide-level success rate. Here, bearing in mind the goal to improve peptide-level targeting, we introduce several new functionalities in Tomahto, featuring the integration of gas-phase fractionation using the FAIMS device, an accompanying software program (TomahtoPrimer) to customize fragmentation for each peptide target, and support for higher multiplexing capacity with the latest TMTpro reagent. We demonstrate that adding these features to the Tomahto platform significantly improves overall success rate from 89% to 98% in a single 60 min targeted assay of 290 peptides across human cell lines, while boosting quantitative accuracy via reducing TMT reporter ion interference.

An atlas of the aging mouse proteome reveals the features of age-related post-transcriptional dysregulation

To what extent and how post-transcriptional dysregulation affects aging proteome remains unclear. Here, we provide proteomic data of whole-tissue lysates (WTL) and low-solubility protein-enriched fractions (LSF) of major tissues collected from mice of 6, 15, 24, and 30 months of age. Low-solubility proteins are preferentially affected by age and the analysis of LSF doubles the number of proteins identified to be differentially expressed with age. Simultaneous analysis of proteome and transcriptome using the same tissue homogenates reveals the features of age-related post-transcriptional dysregulation. Post-transcriptional dysregulation becomes evident especially after 24 months of age and age-related post-transcriptional dysregulation leads to accumulation of core matrisome proteins and reduction of mitochondrial membrane proteins in multiple tissues. Based on our in-depth proteomic data and sample-matched transcriptome data of adult, middle-aged, old, and geriatric mice, we construct the Mouse aging proteomic atlas ( https://aging-proteomics.info/ ), which provides a thorough and integrative view of age-related gene expression changes.

Age-associated clonal B cells drive B cell lymphoma in mice

Although cancer is an age-related disease, how the processes of aging contribute to cancer progression is not well understood. In this study, we uncovered how mouse B cell lymphoma develops as a consequence of a naturally aged system. We show here that this malignancy is associated with an age-associated clonal B cell (ACBC) population that likely originates from age-associated B cells. Driven by c-Myc activation, promoter hypermethylation and somatic mutations, IgM+ ACBCs clonally expand independently of germinal centers and show increased biological age. ACBCs become self-sufficient and support malignancy when transferred into young recipients. Inhibition of mTOR or c-Myc in old mice attenuates pre-malignant changes in B cells during aging. Although the etiology of mouse and human B cell lymphomas is considered distinct, epigenetic changes in transformed mouse B cells are enriched for changes observed in human B cell lymphomas. Together, our findings characterize the spontaneous progression of cancer during aging through both cell-intrinsic and microenvironmental changes and suggest interventions for its prevention.

Multifaceted Proteome Analysis at Solubility, Redox, and Expression Dimensions for Target Identification

Multifaceted interrogation of the proteome deepens the system-wide understanding of biological systems; however, mapping the redox changes in the proteome has so far been significantly more challenging than expression and solubility/stability analyses. Here, the first high-throughput redox proteomics approach integrated with expression analysis (REX) is devised and combined with the Proteome Integral Solubility Alteration (PISA) assay. The whole PISA-REX experiment with up to four biological replicates can be multiplexed into a single tandem mass tag TMTpro set. For benchmarking this compact tool, HCT116 cells treated with auranofin are analyzed, showing great improvement compared with previous studies. PISA-REX is then applied to study proteome remodeling upon stimulation of human monocytes by interferon α (IFN-α). Applying this tool to study the proteome changes in plasmacytoid dendritic cells (pDCs) isolated from wild-type versus Ncf1-mutant mice treated with interferon α, shows that NCF1 deficiency enhances the STAT1 pathway and modulates the expression, solubility, and redox state of interferon-induced proteins. Providing comprehensive multifaceted information on the proteome, the compact PISA-REX has the potential to become an industry standard in proteomics and to open new windows into the biology of health and disease.

Protocol for the isolation and proteomic analysis of pathological tau-seeds

The aggregation and spreading of "tau-seeds" are key for the development and progression of tauopathies, including Alzheimer's disease. Here we describe the steps to isolate and analyze biochemically active tau-seeds from human, mouse, and cell origin. We detail the procedure to isolate soluble tau-seeds by size exclusion chromatography and seeding assay. The isolated tau-seed can be further analyzed to determine the interactome by mass spectrometry. This workflow identifies protein-protein interactors of tau-seeds, providing a useful tool for finding new therapeutic targets. For complete details on the use and execution of this protocol, please refer to Martinez et al.1.

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provides robust protein quantifications in identifying differentially abundant proteins and spatially covariable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial coexpression analysis.

Improved deconvolution of natural products' protein targets using diagnostic ions from chemical proteomics linkers

Identification of interactions between proteins and natural products or similar active small molecules is crucial for understanding of their mechanism of action on a molecular level. To search elusive, often labile, and low-abundant conjugates between proteins and active compounds, chemical proteomics introduces a feasible strategy that allows to enrich and detect these conjugates. Recent advances in mass spectrometry techniques and search algorithms provide unprecedented depth of proteome coverage and the possibility to detect desired modified peptides with high sensitivity. The chemical 'linker' connecting an active compound-protein conjugate with a detection tag is the critical component of all chemical proteomic workflows. In this review, we discuss the properties and applications of different chemical proteomics linkers with special focus on their fragmentation releasing diagnostic ions and how these may improve the confidence in identified active compound-peptide conjugates. The application of advanced search options improves the identification rates and may help to identify otherwise difficult to find interactions between active compounds and proteins, which may result from unperturbed conditions, and thus are of high physiological relevance.

Conjugation of primary amine groups in targeted proteomics

Primary amines, in the form of unmodified N-terminus of peptide/protein and unmodified lysine residue, are perhaps the most important functional groups that can serve as the starting points in proteomic analysis, especially via mass spectrometry-based approaches. A variety of multifunctional probes that conjugate primary amine groups through covalent bonds have been developed and employed to facilitate protein/protein complex characterization, including identification, quantification, structure and localization elucidation, protein-protein interaction investigation, and so forth. As an integral part of more accurate peptide quantification in targeted proteomics, isobaric stable isotope-coded primary amine labeling approaches eventually facilitated protein/peptide characterization at the single-cell level, paving the way for single-cell proteomics. The development and advances in the field can be reviewed in terms of key components of a multifunctional probe: functional groups and chemistry for primary amine conjugation; hetero-bifunctional moiety for separation/enrichment of conjugated protein/protein complex; and functionalized linker/spacer. Perspectives are primarily focused on optimizing primary amine conjugation under physiological conditions to improve characterization of native proteins, especially those associated with the surface of living cells/microorganisms.

Fibre-specific mitochondrial protein abundance is linked to resting and post-training mitochondrial content in the muscle of men

Analyses of mitochondrial adaptations in human skeletal muscle have mostly used whole-muscle samples, where results may be confounded by the presence of a mixture of type I and II muscle fibres. Using our adapted mass spectrometry-based proteomics workflow, we provide insights into fibre-specific mitochondrial differences in the human skeletal muscle of men before and after training. Our findings challenge previous conclusions regarding the extent of fibre-type-specific remodelling of the mitochondrial proteome and suggest that most baseline differences in mitochondrial protein abundances between fibre types reported by us, and others, might be due to differences in total mitochondrial content or a consequence of adaptations to habitual physical activity (or inactivity). Most training-induced changes in different mitochondrial functional groups, in both fibre types, were no longer significant in our study when normalised to changes in markers of mitochondrial content.

Cellular thermal shift assay: an approach to identify and assess protein target engagement

INTRODUCTION

A comprehensive and global knowledge of protein target engagement is of vital importance for mechanistic studies and in drug development. Since its initial introduction, the cellular thermal shift assay (CETSA) has proven to be a reliable and flexible technique that can be widely applied to multiple contexts and has profound applications in facilitating the identification and assessment of protein target engagement.

AREAS COVERED

This review introduces the principle of CETSA, elaborates on western blot-based CETSA and MS-based thermal proteome profiling (TPP) as well as the major applications and prospects of these approaches.

EXPERT OPINION

CETSA primarily evaluates a given ligand binding to a particular target protein in cells and tissues with the protein thermal stabilities analyzed by western blot. When coupling mass spectrometry with CETSA, thermal proteome profiling allows simultaneous proteome-wide experiment that greatly increased the efficiency of target engagement evaluation, and serves as a promising strategy to identify protein targets and off-targets as well as protein-protein interactions to uncover the biological effects. The CETSA approaches have broad applications and potentials in drug development and clinical research.

Multi-omics revealed the mechanism of feed efficiency in sheep by the combined action of the host and rumen microbiota

This study was conducted to investigate potential regulatory mechanisms of feed efficiency (FE) in sheep by linking rumen microbiota with its host by the multi-omics analysis. One hundred and ninety-eight hybrid female sheep (initial body weight = 30.88 ± 4.57 kg; 4-month-old) were selected as candidate sheep. Each test sheep was fed in an individual pen for 60 days, and the residual feed intake (RFI) was calculated. The ten candidate sheep with the highest RFI were divided into the Low-FE group, and the ten with the lowest RFI were divided into the High-FE group, all selected for sample collection. The RFI, average daily gain and average daily feed intake were highly significantly different between the two experimental groups (P < 0.05). Compared with Low-FE group, the insulin-like growth factor-1 and very low-density lipoprotein in serum and the propionate in rumen significantly increased in High-FE group (P < 0.01), but the acetate:propionate ratio in rumen significantly decreased in High-FE group (P = 0.034). Metagenomics revealed Selenomonas ruminantium, Selenomonas sp. and Faecalibacterium prausnitzi i were key bacteria, and increased abundance of the genes encoding the enzymes for cellulose degradation and production of propionate in High-FE group. The results of proteomics and section showed the rumen papilla length (P < 0.001) and expression of carbonic anhydrase and Na+/K+-ATPase were significantly higher in High-FE group (P < 0.05). On the other hand, the acetyl-CoA content significantly increased in the liver of High-FE group (P = 0.002). The relative expression levels of insulin-like growth factor-1 and apolipoprotein A4 genes were significantly up-regulated in the liver of High-FE group (P < 0.01), but relative expression level of monoacylglycerol O-acyltransferase 3 gene was significantly down-regulated (P = 0.037). These findings provide the mechanism by which the collaborative interaction between rumen microbiota fermentation and host uptake and metabolism of fermentation products impacts feed efficiency traits in sheep.