Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry

Standard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics

Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography-mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms. To systematically analyze and assess the quality of large-scale urinary proteomics data, we develop a comprehensive quality control (QC) system named MSCohort, which extracted 81 metrics for individual experiment and the whole cohort quality evaluation. Additionally, we present a standard operating procedure (SOP) for high-throughput urinary proteome analysis based on MSCohort QC system. Our study involves 20 LC-MS platforms and reveals that, when combined with a comprehensive QC system and a unified SOP, the data generated by data-independent acquisition (DIA) workflow in urine QC samples exhibit high robustness, sensitivity, and reproducibility across multiple LC-MS platforms. Furthermore, we apply this SOP to hybrid benchmarking samples and clinical colorectal cancer (CRC) urinary proteome including 527 experiments. Across three different LC-MS platforms, the analyses report high quantitative reproducibility and consistent disease patterns. This work lays the groundwork for large-scale clinical urinary proteomics studies spanning multiple platforms, paving the way for precision medicine research.

Proteomic Analysis of Breast Cancer Subtypes Identifies Stromal Contributions that Dictate Aggressive Malignant Behavior

Breast cancer manifests as multiple subtypes with distinct patient outcomes and treatment strategies. Here, we optimized proteomic analysis of Formalin-Fixed Paraffin-Embedded (FFPE) specimens from patients diagnosed with five breast cancer subtypes, luminal A, luminal B, Her2, triple negative (TNBC) and metaplastic breast cancers (MBC), and from disease-free individuals undergoing reduction mammoplasty (RM). We identified and quantified ∼6,000 protein groups (with >2 peptides per protein) with significant changes in over 26% of proteins comparing each cancer subtype with control RM. Stringent statistical filters allowed us to deeply mine 576 significant conserved protein changes shared by all subtypes and protein changes unique to each subtype. The most aggressive subtype, MBC, revealed exacerbated stromal stress responses, as illustrated by a collagenolytic extracellular matrix (ECM) and immune participation biased towards neutrophils and eosinophils. Immunostaining of breast tissue sections confirmed differences across subtypes, in particular, a dramatic upregulation of SERPINH1, neutrophil-specific myeloperoxidase and eosinophil cationic protein in MBC. In summary, deep proteomic, digitalized protein abundance profiles, generated from FFPE breast cancer tissues, revealed significant changes in ECM and cellular proteins providing insight into clinically relevant states.

Substrate stiffness dictates unique doxorubicin-induced senescence-associated secretory phenotypes and transcriptomic signatures in human pulmonary fibroblasts

Cells are subjected to dynamic mechanical environments which impart forces and induce cellular responses. In age-related conditions like pulmonary fibrosis, there is both an increase in tissue stiffness and an accumulation of senescent cells. While senescent cells produce a senescence-associated secretory phenotype (SASP), the impact of physical stimuli on both cellular senescence and the SASP is not well understood. Here, we show that mechanical tension, modeled using cell culture substrate rigidity, influences senescent cell markers like SA-β-gal and secretory phenotypes. Comparing human primary pulmonary fibroblasts (IMR-90) cultured on physiological (2 kPa), fibrotic (50 kPa), and plastic (approximately 3 GPa) substrates, followed by senescence induction using doxorubicin, we identified unique high-stiffness-driven secretory protein profiles using mass spectrometry and transcriptomic signatures, both showing an enrichment in collagen proteins. Consistently, clusters of p21 + cells are seen in fibrotic regions of bleomycin induced pulmonary fibrosis in mice. Computational meta-analysis of single-cell RNA sequencing datasets from human interstitial lung disease confirmed these stiffness SASP genes are highly expressed in disease fibroblasts and strongly correlate with mechanotransduction and senescence-related pathways. Thus, mechanical forces shape cell senescence and their secretory phenotypes.

β-hydroxybutyrate is a metabolic regulator of proteostasis in the aged and Alzheimer disease brain

Loss of proteostasis is a hallmark of aging and Alzheimer disease (AD). We identify β-hydroxybutyrate (βHB), a ketone body, as a regulator of protein solubility. βHB primarily provides ATP substrate during periods of reduced glucose availability, and regulates other cellular processes through protein interactions. We demonstrate βHB-induced protein insolubility is not dependent on covalent protein modification, pH, or solute load, and is observable in mouse brain in vivo after delivery of a ketone ester. This mechanism is selective for pathological proteins such as amyloid-β, and exogenous βHB ameliorates pathology in nematode models of amyloid-β aggregation toxicity. We generate libraries of the βHB-induced protein insolublome using mass spectrometry proteomics, and identify common protein domains and upstream regulators. We show enrichment of neurodegeneration-related proteins among βHB targets and the clearance of these targets from mouse brain. These data indicate a metabolically regulated mechanism of proteostasis relevant to aging and AD.

Proteomic Profiling Towards a Better Understanding of Genetic Based Muscular Diseases: The Current Picture and a Look to the Future

Proteomics accelerates diagnosis and research of muscular diseases by enabling the robust analysis of proteins relevant for the manifestation of neuromuscular diseases in the following aspects: (i) evaluation of the effect of genetic variants on the corresponding protein, (ii) prediction of the underlying genetic defect based on the proteomic signature of muscle biopsies, (iii) analysis of pathophysiologies underlying different entities of muscular diseases, key for the definition of new intervention concepts, and (iv) patient stratification according to biochemical fingerprints as well as (v) monitoring the success of therapeutic interventions. This review presents-also through exemplary case studies-the various advantages of mass proteomics in the investigation of genetic muscle diseases, discusses technical limitations, and provides an outlook on possible future application concepts. Hence, proteomics is an excellent large-scale analytical tool for the diagnostic workup of (hereditary) muscle diseases and warrants systematic profiling of underlying pathophysiological processes. The steady development may allow to overcome existing limitations including a quenched dynamic range and quantification of different protein isoforms. Future directions may include targeted proteomics in diagnostic settings using not only muscle biopsies but also liquid biopsies to address the need for minimally invasive procedures.

Circadian Proteomics Reassesses the Temporal Regulation of Metabolic Rhythms by Chlamydomonas Clock

Circadian clocks execute temporal regulation of metabolism by modulating the timely expression of genes. Clock regulation of mRNA synthesis was envisioned as the primary driver of these daily rhythms. mRNA oscillations often do not concur with the downstream protein oscillations, revealing the importance to study protein oscillations. Chlamydomonas reinhardtii is a well-studied miniature plant model. We quantitatively probed the Chlamydomonas proteome for two subsequent circadian cycles using high throughput SWATH-DIA mass spectrometry. We quantified > 1000 proteins, half of which demonstrate circadian rhythms. Among these rhythmic proteins, > 90% peak around subjective midday or midnight. We uncovered key enzymes involved in Box C/D pathway, amino acid biosynthesis, fatty acid (FA) biosynthesis and peroxisomal β-oxidation of FAs are driven by the clock, which were undocumented from earlier transcriptomic studies. Proteins associated with key biological processes such as photosynthesis, redox, carbon fixation, glycolysis and TCA cycle show extreme temporal regulation. We conclude that circadian proteomics is required to complement transcriptomic studies to understand the complex clock regulation of organismal biology. We believe our study will not only refine and enrich the evaluation of temporal metabolic processes in C. reinhardtii but also provide a novel understanding of clock regulation across species.

A Multiyear Longitudinal Harmonization Study of Quality Controls in Mass Spectrometry Proteomics Core Facilities

Quality control procedures play a pivotal role in ensuring the reliability and consistency of data generated in mass spectrometry-based proteomics laboratories. However, the lack of standardized quality control practices across laboratories poses challenges for data comparability and reproducibility. In response, we conducted a harmonization study within proteomics laboratories of the Core for Life alliance with the aim of establishing a common quality control framework, which facilitates comprehensive quality assessment and identification of potential sources of performance drift. Through collaborative efforts, we developed a consensus quality control standard for longitudinal assessment and adopted common processing software. We generated a 4-year longitudinal data set from multiple instruments and laboratories, which enabled us to assess intra- and interlaboratory variability, to identify causes of performance drift, and to establish community reference values for several quality control parameters. Our study enhances data comparability and reliability and fosters a culture of collaboration and continuous improvement within the proteomics community to ensure the integrity of proteomics data.

Exogenous expression of ATP8, a mitochondrial encoded protein, from the nucleus in vivo

Replicative errors, inefficient repair, and proximity to sites of reactive oxygen species production make mitochondrial DNA (mtDNA) susceptible to damage with time. We explore in vivo allotopic expression (re-engineering mitochondrial genes and expressing them from the nucleus) as an approach to rescue defects arising from mtDNA mutations. We used a mouse strain C57BL/6J(mtFVB) with a natural polymorphism (m.7778 G>T) in the mitochondrial ATP8 gene that encodes a protein subunit of the ATP synthase. We generated a transgenic mouse with an epitope-tagged recoded mitochondrial-targeted ATP8 gene expressed from the ROSA26 locus in the nucleus and used the C57BL/6J(mtFVB) strain to verify successful incorporation. The allotopically expressed ATP8 protein in transgenic mice was constitutively expressed across all tested tissues, successfully transported into the mitochondria, and incorporated into ATP synthase. The ATP synthase with transgene had similar activity to non-transgenic control, suggesting successful integration and function. Exogenous ATP8 protein had no negative impact on measured mitochondrial function, metabolism, or behavior. Successful allotopic expression of a mitochondrially encoded protein in vivo in a mammal is a step toward utilizing allotopic expression as a gene therapy in humans to repair physiological consequences of mtDNA defects that may accumulate in congenital mitochondrial diseases or with age.

Substrate Stiffness Dictates Unique Doxorubicin-induced Senescence-associated Secretory Phenotypes and Transcriptomic Signatures in Human Pulmonary Fibroblasts

Cells are subjected to dynamic mechanical environments which impart forces and induce cellular responses. In age-related conditions like pulmonary fibrosis, there is both an increase in tissue stiffness and an accumulation of senescent cells. While senescent cells produce a senescence-associated secretory phenotype (SASP), the impact of physical stimuli on both cellular senescence and the SASP is not well understood. Here, we show that mechanical tension, modeled using cell culture substrate rigidity, influences senescent cell markers like SA-β-gal and secretory phenotypes. Comparing human primary pulmonary fibroblasts (IMR-90) cultured on physiological (2 kPa), fibrotic (50 kPa), and plastic (approximately 3 GPa) substrates, followed by senescence induction using doxorubicin, we identified unique high-stiffness-driven secretory protein profiles using mass spectrometry and transcriptomic signatures, both showing an enrichment in collagen proteins. Consistently, clusters of p21+ cells are seen in fibrotic regions of bleomycin induced pulmonary fibrosis in mice. Computational meta-analysis of single-cell RNA sequencing datasets from human interstitial lung disease confirmed these stiffness SASP genes are highly expressed in disease fibroblasts and strongly correlate with mechanotransduction and senescence-related pathways. Thus, mechanical forces shape cell senescence and their secretory phenotypes.

Proteomic characterization of murine hematopoietic stem progenitor cells reveals dynamic fetal-to-adult changes in metabolic-related pathways

Hematopoietic stem progenitor cells (HSPCs) give rise to the hematopoietic system, maintain hematopoiesis throughout the lifespan, and undergo molecular and functional changes during their development and aging. The importance of hematopoietic stem cell (HSC) biology has led to their extensive characterization at genomic and transcriptomic levels. However, the proteomics of HSPCs throughout the murine lifetime still needs to be fully completed. Here, using mass spectrometry (MS)-based quantitative proteomics, we report on the dynamic changes in the proteome of HSPCs from four developmental stages in the fetal liver (FL) and the bone marrow (BM), including E14.5, young (2 months), middle-aged (8 months), and aging (18 months) stages. Proteomics unveils highly dynamic protein kinetics during the development and aging of HSPCs. Our data identify stage-specific developmental features of HSPCs, which can be linked to their functional maturation and senescence. Our proteomic data demonstrated that FL HSPCs depend on aerobic respiration to meet their proliferation and oxygen supply demand, while adult HSPCs prefer glycolysis to preserve the HSC pool. By functional assays, we validated the decreased mitochondrial metabolism, glucose uptake, reactive oxygen species (ROS) production, protein synthesis rate, and increased glutathione S-transferase (GST) activity during HSPC development from fetal to adult. Distinct metabolism pathways and immune-related pathways enriched in different HSPC developmental stages were revealed at the protein level. Our study will have broader implications for understanding the mechanism of stem cell maintenance and fate determination and reversing the HSC aging process.

Mass Spectrometry Advances in Analysis of Glioblastoma

Some cancers such as glioblastoma (GBM), show minimal response to medical interventions, often only capable of mitigating tumor growth or alleviating symptoms. High metabolic activity in the tumor microenvironment marked by immune responses and hypoxia, is a crucial factor driving tumor progression. The many developments in mass spectrometry (MS) over the last decades have provided a pivotal tool for studying proteins, along with their posttranslational modifications. It is known that the proteomic landscape of GBM comprises a wide range of proteins involved in cell proliferation, survival, migration, and immune evasion. Combination of MS imaging and microscopy has potential to reveal the spatial and molecular characteristics of pathological tissue sections. Moreover, integration of MS in the surgical process in form of techniques such as DESI-MS or rapid evaporative ionization MS has been shown as an effective tool for rapid measurement of metabolite profiles, providing detailed information within seconds. In immunotherapy-related research, MS plays an indispensable role in detection and targeting of cancer antigens which serve as a base for antigen-specific therapies. In this review, we aim to provide detailed information on molecular profile in GBM and to discuss recent MS advances and their clinical benefits for targeting this aggressive disease.

Proteome-wide copy-number estimation from transcriptomics

Protein copy numbers constrain systems-level properties of regulatory networks, but proportional proteomic data remain scarce compared to RNA-seq. We related mRNA to protein statistically using best-available data from quantitative proteomics and transcriptomics for 4366 genes in 369 cell lines. The approach starts with a protein's median copy number and hierarchically appends mRNA-protein and mRNA-mRNA dependencies to define an optimal gene-specific model linking mRNAs to protein. For dozens of cell lines and primary samples, these protein inferences from mRNA outmatch stringent null models, a count-based protein-abundance repository, empirical mRNA-to-protein ratios, and a proteogenomic DREAM challenge winner. The optimal mRNA-to-protein relationships capture biological processes along with hundreds of known protein-protein complexes, suggesting mechanistic relationships. We use the method to identify a viral-receptor abundance threshold for coxsackievirus B3 susceptibility from 1489 systems-biology infection models parameterized by protein inference. When applied to 796 RNA-seq profiles of breast cancer, inferred copy-number estimates collectively re-classify 26-29% of luminal tumors. By adopting a gene-centered perspective of mRNA-protein covariation across different biological contexts, we achieve accuracies comparable to the technical reproducibility of contemporary proteomics.

Automated High-Throughput Biological Sex Identification from Archeological Human Dental Enamel Using Targeted Proteomics

Biological sex is key information for archeological and forensic studies, which can be determined by proteomics. However, the lack of a standardized approach for fast and accurate sex identification currently limits the reach of proteomics applications. Here, we introduce a streamlined mass spectrometry (MS)-based workflow for the determination of biological sex using human dental enamel. Our approach builds on a minimally invasive sampling strategy by acid etching, a rapid online liquid chromatography (LC) gradient coupled to a high-resolution parallel reaction monitoring (PRM) assay allowing for a throughput of 200 samples per day (SPD) with high quantitative performance enabling confident identification of both males and females. Additionally, we developed a streamlined data analysis pipeline and integrated it into a Shiny interface for ease of use. The method was first developed and optimized using modern teeth and then validated in an independent set of deciduous teeth of known sex. Finally, the assay was successfully applied to archeological material, enabling the analysis of over 300 individuals. We demonstrate unprecedented performance and scalability, speeding up MS analysis by 10-fold compared to conventional proteomics-based sex identification methods. This work paves the way for large-scale archeological or forensic studies enabling the investigation of entire populations rather than focusing on individual high-profile specimens. Data are available via ProteomeXchange with the identifier PXD049326.

An Equine Protein Atlas Highlights Synovial Fluid Proteome Dynamics during Experimentally LPS-Induced Arthritis

In human proteomics, substantial efforts are ongoing to leverage large collections of mass spectrometry (MS) fragment ion spectra into extensive spectral libraries (SL) as a resource for data independent acquisition (DIA) analysis. Currently, such initiatives in equine research are still missing. Here we present a large-scale equine SL, comprising 6394 canonical proteins and 89,329 unique peptides, based on data dependent acquisition analysis of 75 tissue and body fluid samples from horses. The SL enabled large-scale DIA-MS based quantification of the same samples to generate a quantitative equine protein distribution atlas to infer dominant proteins in different organs and body fluids. Data mining revealed 163 proteins uniquely identified in a specific type of tissue or body fluid, serving as a starting point to determine tissue-specific or tissue-type-specific proteins. We showcase the SL by highlighting proteome dynamics in equine synovial fluid samples during experimental lipopolysaccharide-induced arthritis. A fuzzy c-means cluster analysis pinpointed SERPINB1, ATRN, NGAL, LTF, MMP1, and LBP as putative biomarkers for joint inflammation. This SL provides an extendable resource for future equine studies employing DIA-MS.

Evaluation of a Proteomics-Guided Protein Signature for Breast Cancer Detection in Breast Tissue

The distinction between noncancerous and cancerous breast tissues is challenging in clinical settings, and discovering new proteomics-based biomarkers remains underexplored. Through a pilot proteomic study (discovery cohort), we aimed to identify a protein signature indicative of breast cancer for subsequent validation using six published proteomics/transcriptomics data sets (validation cohorts). Sequential window acquisition of all theoretical (SWATH)-based mass spectrometry revealed 370 differentially abundant proteins between noncancerous tissue and breast cancer. Protein-protein interaction-based networks and enrichment analyses revealed dysregulation in pathways associated with extracellular matrix organization, platelet degranulation, the innate immune system, and RNA metabolism in breast cancer. Through multivariate unsupervised analysis, we identified a four-protein signature (OGN, LUM, DCN, and COL14A1) capable of distinguishing breast cancer. This dysregulation pattern was consistently verified across diverse proteomics and transcriptomics data sets. Dysregulation magnitude was notably higher in poor-prognosis breast cancer subtypes like Basal-Like and HER2 compared to Luminal A. Diagnostic evaluation (receiver operating characteristic (ROC) curves) of the signature in distinguishing breast cancer from noncancerous tissue revealed area under the curve (AUC) ranging from 0.87 to 0.9 with predictive accuracy of 80% to 82%. Upon stratifying, to solely include the Basal-Like/Triple-Negative subtype, the ROC AUC increased to 0.922-0.959 with predictive accuracy of 84.2%-89%. These findings suggest a potential role for the identified signature in distinguishing cancerous from noncancerous breast tissue, offering insights into enhancing diagnostic accuracy.

A Comprehensive and Robust Multiplex-DIA Workflow Profiles Protein Turnover Regulations Associated with Cisplatin Resistance

Measuring protein turnover is essential for understanding cellular biological processes and advancing drug discovery. The multiplex DIA mass spectrometry (DIA-MS) approach, combined with dynamic SILAC labeling (pulse-SILAC, or pSILAC), has proven to be a reliable method for analyzing protein turnover and degradation kinetics. Previous multiplex DIA-MS workflows have employed various strategies, including leveraging the highest isotopic labeling channels of peptides to enhance the detection of isotopic MS signal pairs or clusters. In this study, we introduce an improved and robust workflow that integrates a novel machine learning strategy and channel-specific statistical filtering, enabling dynamic adaptation to systematic or temporal variations in channel ratios. This allows comprehensive profiling of protein turnover throughout the pSILAC experiment without relying solely on the highest channel signals. Additionally, we developed KdeggeR , a data processing and analysis package optimized for pSILAC-DIA experiments, which estimates and visualizes peptide and protein degradation rates and dynamic profiles. Our integrative workflow was benchmarked on both 2-channel and 3-channel standard DIA datasets and across two mass spectrometry platforms, demonstrating its broad applicability. Finally, applying this workflow to an aneuploid cancer cell model before and after cisplatin resistance development demonstrated a strong negative correlation between transcript regulation and protein degradation for major protein complex subunits. We also identified specific protein turnover signatures associated with cisplatin resistance.

Exploring the protein signature of endometrial cancer: A comprehensive review through diverse samples and mass spectrometry-based proteomics

Endometrial cancer (EC) is increasing incidence among women, and it constitutes a health problem for women globally. An important aspect of EC management involves the use of protein biomarkers for early detection and monitoring. Protein biomarkers allow the identification of high-risk patients, the detection of the disease in its early stages, and the assessment of treatment responses. Mass spectrometry (MS)-based proteomics offers robust analytical techniques and a comprehensive understanding of proteins. Proteomics methods allow scientists to investigate both the quantities and functions of proteins. Thus, it provides valuable insights into how proteins are altered under different conditions. This review summarizes recent advances in MS-based proteomic biomarker discovery for EC, focusing on different sample types and MS-based techniques used in clinical studies. The review emphasized in detail the most commonly used key sources such as blood, urine, vaginal fluids and tissue. Furthermore, MS-based proteomics techniques such as untargeted, targeted, sequential window acquisition of all theoretical mass spectra (SWATH-MS) and mass spectrometry imaging used in the discovery and validation/validation phases were evaluated. This review highlights the importance of biomarker discovery and clinical translation to improve diagnostic and therapeutic outcomes in EC. It aims to provide a comprehensive overview of MS-based proteomics in EC, guiding future research and clinical 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.

SWATH-MS Based Secretome Proteomic Analysis of Pseudomonas aeruginosa Against MRSA

The study uses Sequential Window Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH)-MS in conjunction with secretome proteomics to identify key proteins that Pseudomonas aeruginosa secretes against methicillin-resistant Staphylococcus aureus (MRSA). Variations in the inhibition zones indicated differences in strain resistance. Multivariate statistical methods were applied to filter the proteomic results, revealing five potential protein biomarkers, including Peptidase M23. Gene ontology (GO) analysis and sequence alignment supported their antibacterial activity. Thus, SWATH-MS provides a comprehensive understanding of the secretome of P. aeruginosa in its action against MRSA, guiding future antibacterial research.

Deep Spectral Library of Mice Retina for Myopia Research: Proteomics Dataset generated by SWATH and DIA-NN

The retina plays a crucial role in processing and decoding visual information, both in normal development and during myopia progression. Recent advancements have introduced a library-independent approach for data-independent acquisition (DIA) analyses. This study demonstrates deep proteome identification and quantification in individual mice retinas during myopia development, with an average of 6,263 ± 86 unique protein groups. We anticipate that the use of a predicted retinal-specific spectral library combined with the robust quantification achieved within this dataset will contribute to a better understanding of the proteome complexity. Furthermore, a comprehensive mice retinal-specific spectral library was generated, encompassing a total identification of 9,401 protein groups, 70,041 peptides, 95,339 precursors, and 761,868 transitions acquired using SWATH-MS acquisition on a ZenoTOF 7600 mass spectrometer. This dataset surpasses the spectral library generated through high-pH reversed-phase fractionation by data-dependent acquisition (DDA). The data is available via ProteomeXchange with the identifier PXD046983. It will also serve as an indispensable reference for investigations in myopia research and other retinal or neurological diseases.

Proteomic Characterization of Transfusable Blood Components: Fresh Frozen Plasma, Cryoprecipitate, and Derived Extracellular Vesicles via Data-Independent Mass Spectrometry

Extracellular vesicles (EVs) are a heterogeneous collection of particles that play a crucial role in cell-to-cell communication, primarily due to their ability to transport molecules, such as proteins. Thus, profiling EV-associated proteins offers insight into their biological effects. EVs can be isolated from various biological fluids, including donor blood components such as cryoprecipitate and fresh frozen plasma (FFP). In this study, we conducted a proteomic analysis of five single donor units of cryoprecipitate, FFP, and EVs derived from these blood components using a quantitative mass spectrometry approach. EVs were successfully isolated from both cryoprecipitate and FFP based on community guidelines. We identified and quantified approximately 360 proteins across all sample groups. Principal component analysis and heatmaps revealed that both cryoprecipitate and FFP are similar. Similarly, EVs derived from cryoprecipitate and FFP are comparable. However, they differ between the originating fluids and their derived EVs. Using the R-package MS-DAP, differentially expressed proteins (DEPs) were identified. The DEPs for all comparisons, when submitted for gene enrichment analysis, are involved in the complement and coagulation pathways. The protein profile generated from this study will have important clinical implications in increasing our knowledge of the proteins that are associated with EVs derived from blood components.

Amyloid β accelerates age-related proteome-wide protein insolubility

Loss of proteostasis is a highly conserved feature of aging across model organisms and results in the accumulation of insoluble protein aggregates. Protein insolubility is also a unifying feature of major age-related neurodegenerative diseases, including Alzheimer's Disease (AD), in which hundreds of insoluble proteins associate with aggregated amyloid beta (Aβ) in senile plaques. Despite the connection between aging and AD risk, therapeutic approaches to date have overlooked aging-driven generalized protein insolubility as a contributing factor. However, proteins that become insoluble during aging in model organisms are capable of accelerating Aβ aggregation in vitro and lifespan in vivo. Here, using an unbiased proteomics approach, we questioned the relationship between Aβ and age-related protein insolubility. Specifically, we uncovered that Aβ expression drives proteome-wide protein insolubility in C. elegans, even in young animals, and this insoluble proteome is highly similar to the insoluble proteome driven by normal aging, this vulnerable sub-proteome we term the core insoluble proteome (CIP). We show that the CIP is enriched with proteins that modify Aβ toxicity in vivo, suggesting the possibility of a vicious feedforward cycle in the context of AD. Importantly, using human genome-wide association studies (GWAS), we show that the CIP is replete with biological processes implicated not only in neurodegenerative diseases but also across a broad array of chronic, age-related diseases (CARDs). This provides suggestive evidence that age-related loss of proteostasis could play a role in general CARD risk. Finally, we show that the geroprotective, gut-derived metabolite, Urolithin A, relieves Aβ toxicity, supporting its use in clinical trials for dementia and age-related diseases.

Reference Materials for Improving Reliability of Multiomics Profiling

High-throughput technologies for multiomics or molecular phenomics profiling have been extensively adopted in biomedical research and clinical applications, offering a more comprehensive understanding of biological processes and diseases. Omics reference materials play a pivotal role in ensuring the accuracy, reliability, and comparability of laboratory measurements and analyses. However, the current application of omics reference materials has revealed several issues, including inappropriate selection and underutilization, leading to inconsistencies across laboratories. This review aims to address these concerns by emphasizing the importance of well-characterized reference materials at each level of omics, encompassing (epi-)genomics, transcriptomics, proteomics, and metabolomics. By summarizing their characteristics, advantages, and limitations along with appropriate performance metrics pertinent to study purposes, we provide an overview of how omics reference materials can enhance data quality and data integration, thus fostering robust scientific investigations with omics technologies.

Combined assembloid modeling and 3D whole-organ mapping captures the microanatomy and function of the human fallopian tube

The fallopian tubes play key roles in processes from pregnancy to ovarian cancer where three-dimensional (3D) cellular and extracellular interactions are important to their pathophysiology. Here, we develop a 3D multicompartment assembloid model of the fallopian tube that molecularly, functionally, and architecturally resembles the organ. Global label-free proteomics, innovative assays capturing physiological functions of the fallopian tube (i.e., oocyte transport), and whole-organ single-cell resolution mapping are used to validate these assembloids through a multifaceted platform with direct comparisons to fallopian tube tissue. These techniques converge at a unique combination of assembloid parameters with the highest similarity to the reference fallopian tube. This work establishes (i) an optimized model of the human fallopian tubes for in vitro studies of their pathophysiology and (ii) an iterative platform for customized 3D in vitro models of human organs that are molecularly, functionally, and microanatomically accurate by combining tunable assembloid and tissue mapping methods.

Sirt2 Regulates Liver Metabolism in a Sex-Specific Manner

Sirtuin-2 (Sirt2), an NAD+-dependent lysine deacylase enzyme, has previously been implicated as a regulator of glucose metabolism, but the specific mechanisms remain poorly defined. Here, we observed that Sirt2-/- males, but not females, have decreased body fat, moderate hypoglycemia upon fasting, and perturbed glucose handling during exercise compared to wild type controls. Conversion of injected lactate, pyruvate, and glycerol boluses into glucose via gluconeogenesis was impaired, but only in males. Primary Sirt2-/- male hepatocytes exhibited reduced glycolysis and reduced mitochondrial respiration. RNAseq and proteomics were used to interrogate the mechanisms behind this liver phenotype. Loss of Sirt2 did not lead to transcriptional dysregulation, as very few genes were altered in the transcriptome. In keeping with this, there were also negligible changes to protein abundance. Site-specific quantification of the hepatic acetylome, however, showed that 13% of all detected acetylated peptides were significantly increased in Sirt2-/- male liver versus wild type, representing putative Sirt2 target sites. Strikingly, none of these putative target sites were hyperacetylated in Sirt2-/- female liver. The target sites in the male liver were distributed across mitochondria (44%), cytoplasm (32%), nucleus (8%), and other compartments (16%). Despite the high number of putative mitochondrial Sirt2 targets, Sirt2 antigen was not detected in purified wild type liver mitochondria, suggesting that Sirt2's regulation of mitochondrial function occurs from outside the organelle. We conclude that Sirt2 regulates hepatic protein acetylation and metabolism in a sex-specific manner.

Feature selection by replicate reproducibility and non-redundancy

MOTIVATION

A fundamental step in many analyses of high-dimensional data is dimension reduction. Two basic approaches are introduction of new synthetic coordinates and selection of extant features. Advantages of the latter include interpretability, simplicity, transferability, and modularity. A common criterion for unsupervized feature selection is variance or dynamic range. However, in practice, it can occur that high-variance features are noisy, that important features have low variance, or that variances are simply not comparable across features because they are measured in unrelated numeric scales or physical units. Moreover, users may want to include measures of signal-to-noise ratio and non-redundancy into feature selection.

RESULTS

Here, we introduce the RNR algorithm, which selects features based on (i) the reproducibility of their signal across replicates and (ii) their non-redundancy, measured by linear dependence. It takes as input a typically large set of features measured on a collection of objects with two or more replicates per object. It returns an ordered list of features, i1,i2,…,ik, where feature i1 is the one with the highest reproducibility across replicates, i2 that with the highest reproducibility across replicates after projecting out the dimension spanned by i1, and so on. Applications to microscopy-based imaging of cells and proteomics highlight benefits of the approach.

AVAILABILITY AND IMPLEMENTATION

The RNR method is available via Bioconductor (Huber W, Carey VJ, Gentleman R et al. (Orchestrating high-throughput genomic analysis with bioconductor. Nat Methods 2015;12:115-21.) in the R package FeatSeekR. Its source code is also available at https://github.com/tcapraz/FeatSeekR under the GPL-3 open source license.

Neuropilin-1 sex-dependently modulates inflammatory, angiogenic and osteogenic phenotypes in the calcifying valve interstitial cell

The pathological mechanisms underlying the sex-dependent presentation of calcific aortic stenosis (AS) remain poorly understood. We aim to analyse sex-specific responses of valve interstitial cells (VICs) to calcific environments and to identify new pathological and potentially druggable targets. First, VICs from stenotic patients were modelled using pro-calcifying media (HP). Both male and female VICs were inflamed upon calcific HP challenge, although the inflammatory response was higher in female VICs. The osteogenic and calcification responses were higher in male VICs. To identify new players involved in the responses to HP, proteomics analyses were performed on additional calcifying VICs. Neuropilin-1 (NRP-1) was significantly up-regulated in male calcifying VICs and that was confirmed in aortic valves (AVs), especially nearby neovessels and calcifications. Regardless of the sex, NRP-1 expression was correlated to inflammation, angiogenesis and osteogenic markers, but with stronger associations in male AVs. To further evidence the role of NRP-1, in vitro experiments of silencing or supplementation with soluble NRP-1 (sNRP-1) were performed. NRP-1 silencing or addition of sNRP-1 reduced/mended the expression of any sex-specific response triggered by HP. Moreover, NRP-1 regulation contributed to significantly diminish the baseline enhanced expression of pro-inflammatory, pro-angiogenic and pro-osteogenic markers mainly in male VICs. Validation studies were conducted in stenotic AVs. In summary, pharmacologic targeting of NRP-1 could be used to target sex-specific phenotypes in AS as well as to exert protective effects by reducing the basal expression of pathogenic markers only in male VICs.

A proximity proteomics pipeline with improved reproducibility and throughput

Proximity labeling (PL) via biotinylation coupled with mass spectrometry (MS) captures spatial proteomes in cells. Large-scale processing requires a workflow minimizing hands-on time and enhancing quantitative reproducibility. We introduced a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. Combining this with optimized quantitative MS based on data-independent acquisition (DIA), we increased sample throughput and improved protein identification and quantification reproducibility. We applied this pipeline to delineate subcellular proteomes across various compartments. Using the 5HT2A serotonin receptor as a model, we studied temporal changes of proximal interaction networks induced by receptor activation. In addition, we modified the pipeline for reduced sample input to accommodate CRISPR-based gene knockout, assessing dynamics of the 5HT2A network in response to perturbation of selected interactors. This PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, enhancing throughput and reproducibility of standard protocols.

PD-1/LAG-3 co-signaling profiling uncovers CBL ubiquitin ligases as key immunotherapy targets

Many cancer patients do not benefit from PD-L1/PD-1 blockade immunotherapies. PD-1 and LAG-3 co-upregulation in T-cells is one of the major mechanisms of resistance by establishing a highly dysfunctional state in T-cells. To identify shared features associated to PD-1/LAG-3 dysfunctionality in human cancers and T-cells, multiomic expression profiles were obtained for all TCGA cancers immune infiltrates. A PD-1/LAG-3 dysfunctional signature was found which regulated immune, metabolic, genetic, and epigenetic pathways, but especially a reinforced negative regulation of the TCR signalosome. These results were validated in T-cell lines with constitutively active PD-1, LAG-3 pathways and their combination. A differential analysis of the proteome of PD-1/LAG-3 T-cells showed a specific enrichment in ubiquitin ligases participating in E3 ubiquitination pathways. PD-1/LAG-3 co-blockade inhibited CBL-B expression, while the use of a bispecific drug in clinical development also repressed C-CBL expression, which reverted T-cell dysfunctionality in lung cancer patients resistant to PD-L1/PD-1 blockade. The combination of CBL-B-specific small molecule inhibitors with anti-PD-1/anti-LAG-3 immunotherapies demonstrated notable therapeutic efficacy in models of lung cancer refractory to immunotherapies, overcoming PD-1/LAG-3 mediated resistance.

Neuronal expression of human amyloid-β and Tau drives global phenotypic and multi-omic changes in C. elegans

Alzheimer's disease (AD) and Alzheimer's related diseases (ADRD) are prevalent age-related neurodegenerative disorders characterized by the accumulation of amyloid-β (Aβ) plaques and Tau neurofibrillary tangles. The nematode Caenorhabditis elegan s ( C. elegans ) serves as an invaluable model organism in diseases of old age-due to its rapid aging. Here we performed an unbiased systems analysis of a C. elegans strain expressing both Aβ and Tau proteins within neurons. We set out to determine if there was a phenotypic interaction between Aβ and Tau. In addition, we were interested in determining the temporal order of the phenotypic and multi-omic (geromic) outcomes. At an early stage of adulthood, we observed reproductive impairments and mitochondrial dysfunction consistent with disruptions in mRNA transcript abundance, protein solubility, and metabolite levels. Notably, the expression of these neurotoxic proteins exhibited a synergistic effect, leading to accelerated aging. Our findings shed light on the close relationship between normal aging and ADRD. Specifically, we demonstrate alterations to metabolic functions preceding age-related neurotoxicity, offering a resource for the development of new therapeutic strategies.

High-Resolution Mass Spectrometry for Human Exposomics: Expanding Chemical Space Coverage

In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.

The mouse multi-organ proteome from infancy to adulthood

The early-life organ development and maturation shape the fundamental blueprint for later-life phenotype. However, a multi-organ proteome atlas from infancy to adulthood is currently not available. Herein, we present a comprehensive proteomic analysis of ten mouse organs (brain, heart, lung, liver, kidney, spleen, stomach, intestine, muscle and skin) at three crucial developmental stages (1-, 4- and 8-weeks after birth) acquired using data-independent acquisition mass spectrometry. We detect and quantify 11,533 protein groups across the ten organs and obtain 115 age-related differentially expressed protein groups that are co-expressed in all organs from infancy to adulthood. We find that spliceosome proteins prevalently play crucial regulatory roles in the early-life development of multiple organs, and detect organ-specific expression patterns and sexual dimorphism. This multi-organ proteome atlas provides a fundamental resource for understanding the molecular mechanisms underlying early-life organ development and maturation.

Proteome Alterations and Nucleosome Activation in Rat Myoblasts Treated with Cerium Oxide Nanoparticles

Oxidative stress is a widespread causative agent of disease. Together with its general relevance for biomedicine, such a dynamic is recognizably detrimental to space exploration. Among other solutions, cerium oxide nanoparticles (or nanoceria, NC) display a long-lasting, self-renewable antioxidant activity. In a previous experiment, we evaluated oxidative imbalance in rat myoblasts in space, aboard the International Space Station, and unveiled possible protective effects from NC through RNA sequencing. Here, we focus on the myoblast response to NC on land by means of proteomics, defining a list of proteins that putatively react to NC and confirming nucleosomes/histones as likely mediators of its molecular action. The proteomics data set we present here and its counterpart from the space study share four factors. These are coherently either up- (Hist1h4b) or down-regulated (Gnl3, Mtdh, Trip12) upon NC exposure.

Anti-tumor efficacy of HRS-4642 and its potential combination with proteasome inhibition in KRAS G12D-mutant cancer

KRAS G12D is the most frequently mutated oncogenic KRAS subtype in solid tumors and remains undruggable in clinical settings. Here, we developed a high affinity, selective, long-acting, and non-covalent KRAS G12D inhibitor, HRS-4642, with an affinity constant of 0.083 nM. HRS-4642 demonstrated robust efficacy against KRAS G12D-mutant cancers both in vitro and in vivo. Importantly, in a phase 1 clinical trial, HRS-4642 exhibited promising anti-tumor activity in the escalating dosing cohorts. Furthermore, the sensitization and resistance spectrum for HRS-4642 was deciphered through genome-wide CRISPR-Cas9 screening, which unveiled proteasome as a sensitization target. We further observed that the proteasome inhibitor, carfilzomib, improved the anti-tumor efficacy of HRS-4642. Additionally, HRS-4642, either as a single agent or in combination with carfilzomib, reshaped the tumor microenvironment toward an immune-permissive one. In summary, this study provides potential therapies for patients with KRAS G12D-mutant cancers, for whom effective treatments are currently lacking.

Comparison of the Proteome of Huh7 Cells Transfected with Hepatitis B Virus Subgenotype A1, with or without G1862T

HBeAg is a non-structural, secreted protein of hepatitis B virus (HBV). Its p25 precursor is post-translationally modified in the endoplasmic reticulum. The G1862T precore mutation leads to the accumulation of P25 in the endoplasmic reticulum and activation of unfolded protein response. Using mass spectrometry, comparative proteome profiling of Huh-7 cells transfected with wildtype (WT) or G1862T revealed significantly differentially expressed proteins resulting in 12 dysregulated pathways unique to WT-transfected cells and 7 shared between cells transfected with either WT or G1862T. Except for the p38 MAPK signalling pathway, WT showed a higher number of DEPs than G1862T-transfected cells in all remaining six shared pathways. Two signalling pathways: oxidative stress and cell cycle signalling were differentially expressed only in cells transfected with G1862T. Fifteen pathways were dysregulated in G1862T-transfected cells compared to WT. The 15 dysregulated pathways were involved in the following processes: MAPK signalling, DNA synthesis and methylation, and extracellular matrix organization. Moreover, proteins involved in DNA synthesis signalling (replication protein A (RPA) and DNA primase (PRIM2)) were significantly upregulated in G1862T compared to WT. This upregulation was confirmed by mRNA quantification of both genes and immunofluorescent confocal microscopy for RPA only. The dysregulation of the pathways involved in these processes may lead to immune evasion, persistence, and uncontrolled proliferation, which are hallmarks of cancer.

Succinylation of Park7 activates a protective metabolic response to acute kidney injury

Acute kidney injury (AKI) is extremely prevalent among hospitalizations and presents a significant risk for the development of chronic kidney disease and increased mortality. Ischemia caused by shock, trauma, and transplant are common causes of AKI. To attenuate ischemic AKI therapeutically, we need a better understanding of the physiological and cellular mechanisms underlying damage. Instances of ischemia are most damaging in proximal tubule epithelial cells (PTECs) where hypoxic signaling cascades, and perhaps more rapidly, posttranslational modifications (PTMs), act in concert to change cellular metabolism. Here, we focus on the effects of the understudied PTM, lysine succinylation. We have previously shown a protective effect of protein hypersuccinylation on PTECs after depletion of the desuccinylase sirtuin5. General trends in the results suggested that hypersuccinylation led to upregulation of peroxisomal activity and was protective against kidney injury. Included in the list of changes was the Parkinson's-related deglycase Park7. There is little known about any links between peroxisome activity and Park7. In this study, we show in vitro and in vivo that Park7 has a crucial role in protection from AKI and upregulated peroxisome activity. These data in combination with published results of Park7's protective role in cardiovascular damage and chronic kidney disease lead us to hypothesize that succinylation of Park7 may ameliorate oxidative damage resulting from AKI and prevent disease progression. This novel mechanism provides a potential therapeutic mechanism that can be targeted.NEW & NOTEWORTHY Succinylation is an understudied posttranslational modification that has been shown to increase peroxisomal activity. Furthermore, increased peroxisomal activity has been shown to reduce oxidative stress and protect proximal tubules after acute kidney injury. Analysis of mass spectrometry succinylomic and proteomic data reveals a novel role for Parkinson's related Park7 in mediating Nrf2 antioxidant response after kidney injury. This novel protection pathway provides new insights for kidney injury prevention and development of novel therapeutics.

Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials

Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics reference materials of matched DNA, RNA, protein and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters. These references provide built-in truth defined by relationships among the family members and the information flow from DNA to RNA to protein. We demonstrate how using a ratio-based profiling approach that scales the absolute feature values of a study sample relative to those of a concurrently measured common reference sample produces reproducible and comparable data suitable for integration across batches, labs, platforms and omics types. Our study identifies reference-free 'absolute' feature quantification as the root cause of irreproducibility in multi-omics measurement and data integration and establishes the advantages of ratio-based multi-omics profiling with common reference materials.

Characterization of the plasma proteomic profile of Fabry disease: Potential sex- and clinical phenotype-specific biomarkers

Fabry disease (FD) is a X-linked rare lysosomal storage disorder caused by deficient α-galactosidase A (α-GalA) activity. Early diagnosis and the prediction of disease course are complicated by the clinical heterogeneity of FD, as well as by the frequently inconclusive biochemical and genetic test results that do not correlate with clinical course. We sought to identify potential biomarkers of FD to better understand the underlying pathophysiology and clinical phenotypes. We compared the plasma proteomes of 50 FD patients and 50 matched healthy controls using DDA and SWATH-MS. The >30 proteins that were differentially expressed between the 2 groups included proteins implicated in processes such as inflammation, heme and haemoglobin metabolism, oxidative stress, coagulation, complement cascade, glucose and lipid metabolism, and glycocalyx formation. Stratification by sex revealed that certain proteins were differentially expressed in a sex-dependent manner. Apolipoprotein A-IV was upregulated in FD patients with complications, especially those with chronic kidney disease, and apolipoprotein C-III and fetuin-A were identified as possible markers of FD with left ventricular hypertrophy. All these proteins had a greater capacity to identify the presence of complications in FD patients than lyso-GB3, with apolipoprotein A-IV standing out as being more sensitive and effective in differentiating the presence and absence of chronic kidney disease in FD patients than renal markers such as creatinine, glomerular filtration rate and microalbuminuria. Identification of these potential biomarkers can help further our understanding of the pathophysiological processes that underlie the heterogeneous clinical manifestations associated with FD.

Exosomes Released from Senescent Cells and Circulatory Exosomes Isolated from Human Plasma Reveal Aging-associated Proteomic and Lipid Signatures

Senescence emerged as a significant mechanism of aging and age-related diseases, offering an attractive target for clinical interventions. Senescent cells release a senescence-associated secretory phenotype (SASP), including exosomes that may act as signal transducers between distal tissues, propagating secondary or bystander senescence and signaling throughout the body. However, the composition of exosome SASP remains underexplored, presenting an opportunity for novel unbiased discovery. Here, we present a detailed proteomic and lipidomic analysis of exosome SASP using mass spectrometry from human plasma from young and older individuals and from tissue culture of senescent primary human lung fibroblasts. We identified ~1,300 exosome proteins released by senescent fibroblasts induced by three different senescence inducers causing most exosome proteins to be differentially regulated with senescence. In parallel, a human plasma cohort from young and old individuals revealed over 1,350 exosome proteins and 171 plasma exosome proteins were regulated when comparing old vs young individuals. Of the age-regulated plasma exosome proteins, we observed 52 exosome SASP factors that were also regulated in exosomes from the senescent fibroblasts, including serine protease inhibitors (SERPINs), Prothrombin, Coagulation factor V, Plasminogen, and Reelin. In addition, 247 lipids were identified with high confidence in all exosome samples. Following the senescence inducers, a majority of the identified phosphatidylcholine, phosphatidylethanolamine, and sphingomyelin species increased significantly indicating cellular membrane changes. The most notable categories of significantly changed proteins were related to extracellular matrix remodeling and inflammation, both potentially detrimental pathways that can damage surrounding tissues and even induce secondary or bystander senescence. Our findings reveal mechanistic insights and potential senescence biomarkers, enabling a better approach to surveilling the senescence burden in the aging population and offering promising therapeutic targets for interventions.

Protocol for mass spectrometric profiling of lysine malonylation by lysine acetyltransferase in CRISPRi K562 cell lines

Lysine malonylation is a protein posttranslational modification. We present a protocol to generate stable gene-knockdown K562 cell lines through lentiviral infection of a CRISPR interference (CRISPRi) system followed by lysine malonylation measurement using mass spectrometry (MS). We detail guide RNA (gRNA) vector cloning, lentiviral infection, cell line purification, protein digestion, malonyl-lysine enrichment, desalting, and MS acquisition and analysis. For complete details on the use and execution of this protocol, please refer to Zhang et al.1 and Bons et al.2.

Ketogenic diet administration later in life improves memory by modifying the synaptic cortical proteome via the PKA signaling pathway in aging mice

Aging compromises brain function leading to cognitive decline. A cyclic ketogenic diet (KD) improves memory in aged mice after long-term administration; however, short-term effects later in life and the molecular mechanisms that govern such changes remain unclear. Here, we explore the impact of a short-term KD treatment starting at elderly stage on brain function of aged mice. Behavioral testing and long-term potentiation (LTP) recordings reveal that KD improves working memory and hippocampal LTP. Furthermore, the synaptosome proteome of aged mice fed a KD long-term evidence changes predominantly at the presynaptic compartment associated to the protein kinase A (PKA) signaling pathway. These findings were corroborated in vivo by western blot analysis, with high BDNF abundance and PKA substrate phosphorylation. Overall, we show that a KD modifies brain function even when it is administered later in life and recapitulates molecular features of long-term administration, including the PKA signaling pathway, thus promoting synaptic plasticity at advanced age.

Application of Electro-Activated Dissociation Fragmentation Technique to Identifying Glucuronidation and Oxidative Metabolism Sites of Vepdegestrant by Liquid Chromatography-High Resolution Mass Spectrometry

Drug metabolite identification is an integrated part of drug metabolism and pharmacokinetics studies in drug discovery and development. Definitive identification of metabolic modification sides of test compounds such as screening metabolic soft spots and supporting metabolite synthesis are often required. Currently, liquid chromatography-high resolution mass spectrometry is the dominant analytical platform for metabolite identification. However, the interpretation of product ion spectra generated by commonly used collision-induced disassociation (CID) and higher-energy collisional dissociation (HCD) often fails to identify locations of metabolic modifications, especially glucuronidation. Recently, a ZenoTOF 7600 mass spectrometer equipped with electron-activated dissociation (EAD-HRMS) was introduced. The primary objective of this study was to apply EAD-HRMS to identify metabolism sites of vepdegestrant (ARV-471), a model compound that consists of multiple functional groups. ARV-471 was incubated in dog liver microsomes and 12 phase I metabolites and glucuronides were detected. EAD generated unique product ions via orthogonal fragmentation, which allowed for accurately determining the metabolism sites of ARV-471, including phenol glucuronidation, piperazine N-dealkylation, glutarimide hydrolysis, piperidine oxidation, and piperidine lactam formation. In contrast, CID and HCD spectral interpretation failed to identify modification sites of three O-glucuronides and three phase I metabolites. The results demonstrated that EAD has significant advantages over CID and HCD in definitive structural elucidation of glucuronides and phase I metabolites although the utility of EAD-HRMS in identifying various types of drug metabolites remains to be further evaluated. SIGNIFICANCE STATEMENT: Definitive identification of metabolic modification sites by liquid chromatography-high resolution mass spectrometry is highly needed in drug metabolism research, such as screening metabolic soft spots and supporting metabolite synthesis. However, commonly used collision-induced dissociation (CID) and higher-energy collisional dissociation (HCD) fragmentation techniques often fail to provide critical information for definitive structural elucidation. In this study, the electron-activated dissociation (EAD) was applied to identifying glucuronidation and oxidative metabolism sites of vepdegestrant, which generated significantly better results than CID and HCD.

Proteomic insights into paediatric cancer: Unravelling molecular signatures and therapeutic opportunities

Survival rates in some paediatric cancers have improved greatly over recent decades, in part due to the identification of diagnostic, prognostic and predictive molecular signatures, and the development of risk-directed therapies. However, other paediatric cancers have proved difficult to treat, and there is an urgent need to identify novel biomarkers that reveal therapeutic opportunities. The proteome is the total set of expressed proteins present in a cell or tissue at a point in time, and is vastly more dynamic than the genome. Proteomics holds significant promise for cancer research, as proteins are ultimately responsible for cellular phenotype and are the target of most anticancer drugs. Here, we review the discoveries, opportunities and challenges of proteomic analyses in paediatric cancer, with a focus on mass spectrometry (MS)-based approaches. Accelerating incorporation of proteomics into paediatric precision medicine has the potential to improve survival and quality of life for children with cancer.

Role of the Senescence-Associated Factor Dipeptidyl Peptidase 4 in the Pathogenesis of SARS-CoV-2 Infection

During cellular senescence, persistent growth arrest and changes in protein expression programs are accompanied by a senescence-associated secretory phenotype (SASP). In this study, we detected the upregulation of the SASP-related protein dipeptidyl peptidase 4 (DDP4) in human primary lung cells rendered senescent by exposure to ionizing radiation. DPP4 is an exopeptidase that plays a crucial role in the cleavage of various proteins, resulting in the loss of N-terminal dipeptides and proinflammatory effects. Interestingly, our data revealed an association between severe coronavirus disease 2019 (COVID-19) and DDP4, namely that DPP4 levels increased in the plasma of patients with COVID-19 and were correlated with age and disease progression. Although we could not determine the direct effect of DDP4 on viral replication, mechanistic studies in cell culture revealed a negative impact on the expression of the tight junction protein zonula occludens-1 (ZO-1), which contributes to epithelial barrier function. Mass spectrometry analysis indicated that DPP4 overexpressing cells exhibited a decrease in ZO-1 and increased expression of pro-inflammatory cytokines and chemokines. By investigating the effect of DPP4 on the barrier function of human primary cells, we detected an increase in ZO-1 using DPP4 inhibitors. These results provide an important contribution to our understanding of DPP4 in the context of senescence, suggesting that DPP4 plays a major role as part of the SASP. Our results provide evidence that cellular senescence, a hallmark of aging, has an important impact on respiratory infections.

MassDash: A Web-Based Dashboard for Data-Independent Acquisition Mass Spectrometry Visualization

With the increased usage and diversity of methods and instruments being applied to analyze Data-Independent Acquisition (DIA) data, visualization is becoming increasingly important to validate automated software results. Here we present MassDash, a cross-platform DIA mass spectrometry visualization and validation software for comparing features and results across popular tools. MassDash provides a web-based interface and Python package for interactive feature visualizations and summary report plots across multiple automated DIA feature detection tools, including OpenSwath, DIA-NN, and dreamDIA. Furthermore, MassDash processes peptides on the fly, enabling interactive visualization of peptides across dozens of runs simultaneously on a personal computer. MassDash supports various multidimensional visualizations across retention time, ion mobility, m/z, and intensity, providing additional insights into the data. The modular framework is easily extendable, enabling rapid algorithm development of novel peak-picker techniques, such as deep-learning-based approaches and refinement of existing tools. MassDash is open-source under a BSD 3-Clause license and freely available at https://github.com/Roestlab/massdash, and a demo version can be accessed at https://massdash.streamlit.app.

A proximity proteomics pipeline with improved reproducibility and throughput

Proximity labeling (PL) through biotinylation coupled with mass spectrometry (MS) has emerged as a powerful technique for capturing spatial proteomes within living cells. Large-scale sample processing for proximity proteomics requires a workflow that minimizes hands-on time while enhancing quantitative reproducibility. Here, we present a scalable PL pipeline integrating automated enrichment of biotinylated proteins in a 96-well plate format. By combining this pipeline with an optimized quantitative MS acquisition method based on data-independent acquisition (DIA), we not only significantly increased sample throughput but also improved the reproducibility of protein identification and quantification. We applied this pipeline to delineate subcellular proteomes across various cellular compartments, including endosomes, late endosomes/lysosomes, the Golgi apparatus, and the plasma membrane. Moreover, employing 5HT2A serotonin receptor as a model, we investigated temporal changes of proximal interaction networks induced by the receptor's activation with serotonin. Finally, to demonstrate the applicability of our PL pipeline across multiple experimental conditions, we further modified the PL pipeline for reduced sample input amounts to accommodate CRISPR-based gene knockout, and assessed the dynamics of the 5HT2A network in response to the perturbation of selected proximal interactors. Importantly, the presented PL approach is universally applicable to PL proteomics using biotinylation-based PL enzymes, increasing both throughput and reproducibility of standard protocols.

A review of analytical parameters in 'rapid' liquid chromatographic methods for bioanalysis: Can we do better?

Rapid bioanalysis is beneficial to many applications. However, how 'rapid' a method is, or could be, is often an unanswered question. In this statistical review, the authors have assessed multiple pre-analytical (i.e. sample preparation), and analytical method parameters specifically for liquid chromatography to assist researchers in developing and validating 'rapid' bioanalytical methods. We restricted the search to urine and plasma matrices only. Data were extracted from over 2,000 recent studies and evaluated to assess how these parameters affected the 'on-instrument' analysis time. In addition to methods using ultra-violet (UV) detection, there were a large number of mass spectrometric (MS) methods, allowing additional review of the differences between high- and low-resolution MS on analysis time. We observed that most (N = 922, 70 %) methods used 5 or 10 cm columns, and that whilst uptake of ultra-high performance (U)HPLC columns was good, the use of sub-5 cm columns and/or flow rates in excess of 1 mL/min was incredibly rare (N = 25, 3 %). The detector of choice for quantitative (U)HPLC-MS remains the triple quadrupole, although a number of groups report the use of high-resolution MS for such methods.

Senescent characteristics of human corneal endothelial cells upon ultraviolet-A exposure

PURPOSE

The objective of this study was to investigate the senescent phenotypes of human corneal endothelial cells (hCEnCs) upon treatment with ultraviolet (UV)-A.

METHODS

We assessed cell morphology, senescence-associated β-galactosidase (SA-β-gal) activity, cell proliferation and expression of senescence markers (p16 and p21) in hCEnCs exposed to UV-A radiation, and senescent hCEnCs induced by ionizing radiation (IR) were used as positive controls. We performed RNA sequencing and proteomics analyses to compare gene and protein expression profiles between UV-A- and IR-induced senescent hCEnCs, and we also compared the results to non-senescent hCEnCs.

RESULTS

Cells exposed to 5 J/cm2 of UV-A or to IR exhibited typical senescent phenotypes, including enlargement, increased SA-β-gal activity, decreased cell proliferation and elevated expression of p16 and p21. RNA-Seq analysis revealed that 83.9% of the genes significantly upregulated and 82.6% of the genes significantly downregulated in UV-A-induced senescent hCEnCs overlapped with the genes regulated in IR-induced senescent hCEnCs. Proteomics also revealed that 93.8% of the proteins significantly upregulated in UV-A-induced senescent hCEnCs overlapped with those induced by IR. In proteomics analyses, senescent hCEnCs induced by UV-A exhibited elevated expression levels of several factors part of the senescence-associated secretory phenotype.

CONCLUSIONS

In this study, where senescence was induced by UV-A, a more physiological stress for hCEnCs compared to IR, we determined that UV-A modulated the expression of many genes and proteins typically altered upon IR treatment, a more conventional method of senescence induction, even though UV-A also modulated specific pathways unrelated to IR.

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

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