Using iRT, a normalized retention time for more targeted measurement of peptides

Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer

Mass spectrometry based targeted proteomics methods provide a sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semistochastic sampling, or empirical measurements. These strategies require extensive testing and method refinement due to the difficulties associated with prediction of the peptide response in the biological matrix of interest. Gas-phase fractionated (GPF) narrow window data-independent acquisition (DIA) aids in the development of reproducible selected reaction monitoring (SRM) assays by providing matrix-specific information on peptide detectability and quantification by mass spectrometry. To demonstrate the suitability of DIA data for selecting peptide targets, we reimplement a portion of an existing assay to measure 98 Alzheimer's disease proteins in cerebrospinal fluid (CSF). Peptides were selected from GPF-DIA based on signal intensity and reproducibility. The resulting SRM assay exhibits a quantitative precision similar to that of published data, despite the inclusion of different peptides between the assays. This workflow enables development of new assays without additional upfront data acquisition, demonstrated here through generation of a separate assay for an unrelated set of proteins in CSF from the same data set.

Peptide Property Prediction for Mass Spectrometry Using AI: An Introduction to State of the Art Models

This review explores state of the art machine learning and deep learning models for peptide property prediction in mass spectrometry-based proteomics, including, but not limited to, models for predicting digestibility, retention time, charge state distribution, collisional cross section, fragmentation ion intensities, and detectability. The combination of these models enables not only the in silico generation of spectral libraries but also finds many additional use cases in the design of targeted assays or data-driven rescoring. This review serves as both an introduction for newcomers and an update for experienced researchers aiming to develop accessible and reproducible models for peptide property predictions. Key limitations of the current models, including difficulties in handling diverse post-translational modifications and instrument variability, highlight the need for large-scale, harmonized datasets, and standardized evaluation metrics for benchmarking.

Multiple Classes of Antigen Contribute to the Antigenic Landscape of Mesothelioma

Mesothelioma is an incurable, asbestos-exposure-related cancer that typically affects the lining or pleura of the lungs. Symptoms typically develop many decades after initial asbestos exposure, leaving an enduring legacy of disease. The current disease burden is peaking worldwide and thus there is a massive unmet clinical need for curative therapies. Recently, immune checkpoint blockade-based therapy has been adopted as a first-line of treatment for mesothelioma. Vaccine-induced augmentation of immune responses unleashed during checkpoint blockade may provide further clinical benefit in mesothelioma. In this study, we explore the human leukocyte antigen class I landscape (or immunopeptidome) of mesothelioma in patient-derived cell lines and clinical material (pleural effusion samples). We identify a range of peptide antigens derived from targets including cancer testis antigens, endogenous retroviruses as well as novel post-translational modification of peptides. This information will facilitate the characterization of the immune response to these antigens to determine which class of antigen is most immunogenic and has the potential to be tested in future vaccine studies.

Massively parallel assessment of designed protein solution properties using mass spectrometry and peptide barcoding

Library screening and selection methods can determine the binding activities of individual members of large protein libraries given a physical link between protein and nucleotide sequence, which enables identification of functional molecules by DNA sequencing. However, the solution properties of individual protein molecules cannot be probed using such approaches because they are completely altered by DNA attachment. Mass spectrometry enables parallel evaluation of protein properties amenable to physical fractionation such as solubility and oligomeric state, but current approaches are limited to libraries of 1,000 or fewer proteins. Here, we improved mass spectrometry barcoding by co-synthesizing proteins with barcodes optimized to be highly multiplexable and minimally perturbative, scaling to libraries of >5,000 proteins. We use these barcodes together with mass spectrometry to assay the solution behavior of libraries of de novo-designed monomeric scaffolds, oligomers, binding proteins and nanocages, rapidly identifying design failure modes and successes.

Microflow LC-MS Bottom-Up Proteomics Using 1.5 mm Internal Diameter Columns

Microbore columns with a 1.0 mm inner diameter (i.d.) have gained popularity in microflow liquid chromatography-mass spectrometry (LC-MS) workflows for exploratory proteomics applications due to their high throughput, robustness, and reproducibility. However, obtaining highly efficient separation using these columns remains unachievable, primarily due to significant radial flow heterogeneity caused by uneven particle packing density across the column cross-section. In this study, we evaluated the integration of a 1.5 mm i.d. column, which offers greater packing uniformity and reduced radial flow dispersion, into a microflow LC-MS setup for bottom-up proteomics analysis. The performance of the 1.5 mm i.d. column was compared with that of the 1.0 mm i.d. column using protein samples of varying complexity. The results demonstrate that 1.5 mm i.d. columns provide superior chromatographic separation and better compatibility with conventional-flow LC systems, yielding higher reproducibility and comparable protein and peptide identifications to the 1.0 mm i.d. columns at higher sample amounts. These findings suggest that 1.5 mm i.d. columns could be a suitable alternative to 1.0 mm i.d. columns for microflow LC-MS/MS proteomic analysis, particularly in laboratories with only conventional-flow LC systems.

Blood proteomics and multimodal risk profiling of human volunteers after incision injury: A translational study for advancing personalized pain management after surgery

A significant number of patients develop chronic pain after surgery, but prediction of those who are at risk is currently not possible. Thus, prognostic prediction models that include bio-psycho-social and physiological factors in line with the complex nature of chronic pain would be urgently required. Here, we performed a translational study in male volunteers before and after an experimental incision injury. We determined multi-modal features ranging from pain characteristics and psychological questionnaires to blood plasma proteomics. Outcome measures included pain intensity ratings and the extent of the area of hyperalgesia to mechanical stimuli surrounding the incision, as a proxy of central sensitization. A multi-step logistic regression analysis was performed to predict outcome measures based on feature combinations using data-driven cross-validation and prognostic model development. Phenotype-based stratification resulted in the identification of low and high responders for both outcome measures. Regression analysis revealed prognostic proteomic, specific psychophysical, and psychological features. A combinatorial set of distinct features enabled us to predict outcome measures with increased accuracy compared to using single features. Remarkably, in high responders, protein network analysis suggested a protein signature characteristic of low-grade inflammation. Alongside, in silico drug repurposing highlighted potential treatment options employing antidiabetic and anti-inflammatory drugs. Taken together, we present here an integrated pipeline that harnesses bio-psycho-physiological data for prognostic prediction in a translational approach. This pipeline opens new avenues for clinical application with the goal of stratifying patients and identifying potential new targets, as well as mechanistic correlates, for postsurgical pain.

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.

Intracerebroventricular administration of a modified hexosaminidase ameliorates late-stage neurodegeneration in a GM2 mouse model

The GM2 gangliosidoses, Tay-Sachs disease and Sandhoff disease, are devastating neurodegenerative disorders caused by β-hexosaminidase A (HexA) deficiency. In the Sandhoff disease mouse model, rescue potential was severely reduced when HexA was introduced after disease onset. Here, we assess the effect of recombinant HexA and HexD3, a newly engineered mimetic of HexA optimized for the treatment of Tay-Sachs disease and Sandhoff disease. Enzyme replacement therapy was administered by repeat intracerebroventricular injections in Sandhoff disease model mice with dosing beginning before and after signs of neurodegeneration. As previously observed, HexA effectively increased the lifespan of Sandhoff disease mice by 3.5-fold only when treatment was started before onset of neurodegeneration. In contrast, HexD3 halted motor decline and ameliorated late-stage disease severity even when dosing began late, after neurodegeneration onset. Additionally, HexD3 had advantages over HexA in enzyme stability, distribution potential, and homodimer activity. Overall, our data indicate that advanced therapeutics may widen the treatment window for neurodegenerative disorders.

Proteomic analysis of non-muscle invasive and muscle invasive bladder cancer highlights distinct subgroups with metabolic, matrisomal, and immune hallmarks and emphasizes importance of the stromal compartment

We present the proteomic profiling of 79 bladder cancers, including treatment-naïve non-muscle-invasive bladder cancer (NMIBC, n = 17), muscle-invasive bladder cancer (MIBC, n = 51), and neoadjuvant-treated MIBC (n = 11). Proteins were extracted from formalin-fixed, paraffin-embedded samples and analyzed using data-independent acquisition, yielding >8,000 quantified proteins. MIBC, compared to NMIBC, shows an extracellular matrix (ECM) and immune response signature as well as alteration of the metabolic proteome together with concomitant depletion of proteins involved in cell-cell adhesion and lipid metabolism. Neoadjuvant treatment did not consistently impact the proteome of the residual tumor mass. NMIBC presents two proteomic subgroups that correlate with histological grade and feature signatures of cell adhesion or lipid/DNA metabolism. Treatment-naïve MIBC presents three proteomic subgroups with resemblance to the basal-squamous, stroma-rich, or luminal subtypes and signatures of metabolism, immune functionality, or ECM. The metabolic subgroup presents an immune-depleted microenvironment, whereas the ECM and immune subgroups are enriched for markers of M2-like tumor-associated macrophages and dendritic cells. Markers for natural killer cells are exclusive for the ECM subgroup, and markers for cytotoxic T cells are a hallmark of the immune subgroup. Endogenous proteolysis is increased in MIBC alongside upregulation of matrix metalloproteases, including MMP-14. Genomic panel sequencing yielded the prototypical profile of prevalent FGRF3 alterations in NMIBC and TP53 alterations in MIBC. Tumor-stroma interactions of MIBC were investigated by proteomic analysis of patient-derived xenografts, highlighting specific tumor and stroma contributions to the matrisome and tumor-induced stromal proteome phenotypes. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

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.

Polyhexamethylene guanidine aerosol causes irreversible changes in blood proteins that associated with the severity of lung injury

Polyhexamethylene guanidine (PHMG) is a positively charged polymer used as a disinfectant that kills microbes but can cause pulmonary fibrosis if inhaled. After the long-term risks were confirmed in South Korea, it became crucial to measure toxicity through diverse surrogate biomarkers, not only proteins, especially after these hazardous chemicals had cleared from the body. These biomarkers, identified by their biological functions rather than simple numerical calculations, effectively explained the imbalance of pulmonary surfactant caused by fibrosis from PHMG exposure. These long-term studies on children exposed to PHMG has shown that blood protein indicators, primarily related to apolipoproteins and extracellular matrix, can distinguish the degree of exposure to humidifier disinfectants (HDs). We defined the extreme gradient boosting models and computed reflection scores based on just ten selected proteins, which were also verified in adult women exposed to HD. The reflection scores successfully discriminated between the HD-exposed and unexposed groups in both children and adult females (AUROC: 0.957 and 0.974, respectively) and had a strong negative correlation with lung function indicators. Even after an average of more than 10 years, blood is still considered a meaningful specimen for assessing the impact of environmental exposure to toxic substances, with proteins providing in identifying the pathological severity of such conditions.

A Framework for Quality Control in Quantitative Proteomics

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow, from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at the protein and peptide levels allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and ProteomeXchange under the identifier PXD051318.

metaExpertPro: A Computational Workflow for Metaproteomics Spectral Library Construction and Data-Independent Acquisition Mass Spectrometry Data Analysis

Analysis of large-scale data-independent acquisition mass spectrometry metaproteomics data remains a computational challenge. Here, we present a computational pipeline called metaExpertPro for metaproteomics data analysis. This pipeline encompasses spectral library generation using data-dependent acquisition MS, protein identification and quantification using data-independent acquisition mass spectrometry, functional and taxonomic annotation, as well as quantitative matrix generation for both microbiota and hosts. By integrating FragPipe and DIA-NN, metaExpertPro offers compatibility with both Orbitrap and timsTOF MS instruments. To evaluate the depth and accuracy of identification and quantification, we conducted extensive assessments using human fecal samples and benchmark tests. Performance tests conducted on human fecal samples indicated that metaExpertPro quantified an average of 45,000 peptides in a 60-min diaPASEF injection. Notably, metaExpertPro outperformed three existing software tools by characterizing a higher number of peptides and proteins. Importantly, metaExpertPro maintained a low factual false discovery rate of approximately 5% for protein groups across four benchmark tests. Applying a filter of five peptides per genus, metaExpertPro achieved relatively high accuracy (F-score = 0.67-0.90) in genus diversity and showed a high correlation (rSpearman = 0.73-0.82) between the measured and true genus relative abundance in benchmark tests. Additionally, the quantitative results at the protein, taxonomy, and function levels exhibited high reproducibility and consistency across the commonly adopted public human gut microbial protein databases IGC and UHGP. In a metaproteomic analysis of dyslipidemia patients, metaExpertPro revealed characteristic alterations in microbial functions and potential interactions between the microbiota and the host.

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.

Label-Free Multiple Reaction Monitoring-Mass Spectrometry for Quantifying Phosphopeptides from Extracellular Vesicles

Increasing efforts have been made to develop proteins in circulating extracellular vesicles (EVs) as potential disease markers. It is in particular intriguing to measure post-translational modifications (PTMs) such as phosphorylation, preserved and stable in EVs. To facilitate the quantitative measurement of EV protein phosphorylation for potential clinical use, a label-free (LF) multiple reaction monitoring (MRM) strategy is introduced by utilizing a synthetic phosphopeptide set (phos-iRT) as the internal standards and a local normalization method. The quantitation method was investigated in terms of its linear dynamic range, sensitivity, accuracy, precision, and matrix effect, with a dynamic range spanning from 10 to 1000 ng/mL and an accuracy ranging from 82.4 to 116.8% for EV samples. Then, the LF-MRM-based local normalization method was utilized to evaluate and optimize our recently developed EVTOP method for the enrichment of phosphopeptides from EVs. Finally, we applied the optimized EV enrichment approach and the LF-MRM-based local normalization method to quantify phosphopeptides in urine EVs from patients with prostate cancer (PCa) and healthy individuals, showcasing the strategy's superiority in quantifying phosphopeptides without isotopic internal standards and validating that the method is generally applicable in MRM-based EV phosphopeptide quantification.

Mitigating In-Column Artificial Modifications in High-Temperature LC-MS for Bottom-Up Proteomics and Quality Control of Protein Biopharmaceuticals

Elevating the column temperature is an effective strategy for improving the chromatographic separation of peptides. However, high temperatures induce artificial modifications that compromise the quality of the peptide analysis. Here, we present a novel high-temperature LC-MS method that retains the benefits of a high column temperature while significantly reducing peptide modification and degradation during reversed-phase liquid chromatography. Our approach leverages a short inline trap column maintained at a near-ambient temperature installed upstream of a separation column. The retentivity and dimensions of the trap column were optimized to shorten the residence time of peptides in the heated separation column without compromising the separation performance. This easy-to-implement approach increased peak capacity by 1.4-fold within a 110 min peptide mapping of trastuzumab and provided 10% more peptide identifications in exploratory LC-MS proteomic analyses compared with analyses conducted at 30 °C while maintaining the extent of modifications close to the background level. In the peptide mapping of biopharmaceuticals, where in-column modifications can falsely elevate the levels of some critical quality attributes, the method reduced temperature-related artifacts by 66% for N-terminal pyroGlu and 63% for oxidized Met compared to direct injection at 60 °C, thus improving reliability in quality control of protein drugs. Our findings represent a promising advancement in LC-MS methodology, providing researchers and industry professionals with a valuable tool for improving the chromatographic separation of peptides while significantly reducing the unwanted modifications.

Mapping the immunopeptidome of seven SARS-CoV-2 antigens across common HLA haplotypes

Most COVID-19 vaccines elicit immunity against the SARS-CoV-2 Spike protein. However, Spike protein mutations in emerging strains and immune evasion by the SARS-CoV-2 virus demonstrates the need to develop more broadly targeting vaccines. To facilitate this, we use mass spectrometry to identify immunopeptides derived from seven relatively conserved structural and non-structural SARS-CoV-2 proteins (N, E, Nsp1/4/5/8/9). We use two different B-lymphoblastoid cell lines to map Human Leukocyte Antigen (HLA) class I and class II immunopeptidomes covering some of the prevalent HLA types across the global human population. We employ DNA plasmid transfection and direct antigen delivery approaches to sample different antigens and find 248 unique HLA class I and HLA class II bound peptides with 71 derived from N, 12 from E, 28 from Nsp1, 19 from Nsp4, 73 from Nsp8 and 45 peptides derived from Nsp9. Over half of the viral peptides are unpublished. T cell reactivity tested against 56 of the detected peptides shows CD8+ and CD4+ T cell responses against several peptides from the N, E, and Nsp9 proteins. Results from this study will aid the development of next-generation COVID vaccines targeting epitopes from across a number of SARS-CoV-2 proteins.

Evaluating C18 stationary phases with a positively charged surface for proteomic LC-MS applications using mobile phase acidified with reduced formic acid concentration

We have recently demonstrated the ability of a C18 stationary phase with a positively charged surface (PCS-C18) to provide superior chromatographic separation of peptides using mobile phase acidified with a mere 0.01 % formic acid, significantly improving MS sensitivity. Here, we examined three columns packed with different PCS-C18 phases using the MS-favorable mobile phase acidified with low formic acid concentrations to establish the impact of separation performance and better MS sensitivity on peptide identifications. The surface charge interaction was evaluated using the retention of nitrate. The highest interaction was observed for the AdvanceBio Peptide Plus column. A surface charge-dependent shift in the retention time of peptides was confirmed with a change in formic acid concentration in the mobile phase. The separation performance of the columns with MS-favorable mobile phase acidified with low concentrations of formic acid was evaluated using well-characterized peptides. The loading capacity was assessed using a basic peptide with three lysine residues. Good chromatographic peak shapes and high loading capacity were observed for the Acquity Premier CSH C18 column, even when using a mobile phase acidified with 0.01 % formic acid. The extent of improvement in peptide identification when using reduced formic acid concentration was evaluated by analyzing the tryptic digest of trastuzumab and tryptic digest of whole bacteria cell lysate. Each column provided improved MS signal intensity and peptide identification when using the mobile phase with 0.01 % formic acid. The ability of the Acquity Premier CSH C18 column to provide better separation of peptides, even with a reduced formic acid concentration in the mobile phase, boosted MS signal intensity by 65 % and increased the number of identified peptides from the bacterial sample by 19 %. Our study confirms that significant improvement in the proteomic outputs can be achieved without additional costs only by tailoring the chemistry of the stationary phase to the composition of the mobile phase. Our results can help researchers understand the retention mechanism of peptides on the PCS-C18 stationary phases using low-ionic strength mobile phases and, more importantly, select the best-suited stationary phases for their LC-MS proteomic applications.

A framework for quality control in quantitative proteomics

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share vignettes applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis (Skyline), longitudinal QC metrics (AutoQC), and server-based data deposition (PanoramaWeb). We propose that this integrated approach to QC is a useful starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible. Data are available on Panorama Public and on ProteomeXchange under the identifier PXD051318.

Spatial proteomics of skeletal muscle using thin cryosections reveals metabolic adaptation at the muscle-tendon transition zone

Morphological studies of skeletal muscle tissue provide insights into the architecture of muscle fibers, the surrounding cells, and the extracellular matrix (ECM). However, a spatial proteomics analysis of the skeletal muscle including the muscle-tendon transition zone is lacking. Here, we prepare cryotome muscle sections of the mouse soleus muscle and measure each slice using short liquid chromatography-mass spectrometry (LC-MS) gradients. We generate 3,000 high-resolution protein profiles that serve as the basis for a network analysis to reveal the complex architecture of the muscle-tendon junction. Among the protein profiles that increase from muscle to tendon, we find proteins related to neuronal activity, fatty acid biosynthesis, and the renin-angiotensin system (RAS). Blocking the RAS in cultured mouse tenocytes using losartan reduces the ECM synthesis. Overall, our analysis of thin cryotome sections provides a spatial proteome of skeletal muscle and reveals that the RAS acts as an additional regulator of the matrix within muscle-tendon junctions.

Calib-RT: an open source python package for peptide retention time calibration in DIA mass spectrometry data

MOTIVATION

The data independent acquisition (DIA) mass spectrometry (MS) method is increasingly popular in the field of proteomics. But the loss of the correspondence between peptide ions and their spectra in DIA makes the identification challenging. One effective approach to reduce false positive identification is to calculate the deviation between the peptide's estimated retention time (RT) and measured RT. During this process, scaling the spectral library RT into the estimated RT, known as the RT calibration, is a prerequisite for calculating the deviation. Currently, within the DIA algorithm ecosystem, there is a lack of engine-independent and readily usable RT calibration toolkits.

RESULTS

In this work, we introduce Calib-RT, a RT calibration method tailored to the characteristics of RT data. This method can achieve the nonlinear calibration across various data scales and tolerate a certain level of noise interference. Calib-RT is expected to enrich the open source DIA algorithm toolchain and assist in the development of DIA identification algorithms.

AVAILABILITY AND IMPLEMENTATION

Calib-RT is released as an open source software under the MIT license and can be installed from PyPi as a python module. The source code is available on GitHub at https://github.com/chenghui03/Calib_RT.

VPBrowse: Genome-based representation of MS/MS spectra to quantify 10,000 bovine proteins

SWATH is a data acquisition strategy acclaimed for generating quantitatively accurate and consistent measurements of proteins across multiple samples. Its utility for proteomics studies in nonlaboratory animals, however, is currently compromised by the lack of sufficiently comprehensive and reliable public libraries, either experimental or predicted, and relevant platforms that support their sharing and utilization in an intuitive manner. Here we describe the development of the Veterinary Proteome Browser, VPBrowse (http://browser.proteo.cloud/), an on-line platform for genome-based representation of the Bos taurus proteome, which is equipped with an interactive database and tools for searching, visualization, and building quantitative mass spectrometry assays. In its current version (VPBrowse 1.0), it contains high-quality fragmentation spectra acquired on QToF instrument for over 36,000 proteotypic peptides, the experimental evidence for over 10,000 proteins. Data can be downloaded in different formats to enable analysis using popular software packages for SWATH data processing whilst normalization to iRT scale ensures compatibility with diverse chromatography systems. When applied to published blood plasma dataset from the biomarker discovery study, the resource supported label-free quantification of additional proteins not reported by the authors previously including PSMA4, a tissue leakage protein and a promising candidate biomarker of animal's response to dehorning-related injury.

ProPept-MT: A Multi-Task Learning Model for Peptide Feature Prediction

In the realm of quantitative proteomics, data-independent acquisition (DIA) has emerged as a promising approach, offering enhanced reproducibility and quantitative accuracy compared to traditional data-dependent acquisition (DDA) methods. However, the analysis of DIA data is currently hindered by its reliance on project-specific spectral libraries derived from DDA analyses, which not only limits proteome coverage but also proves to be a time-intensive process. To overcome these challenges, we propose ProPept-MT, a novel deep learning-based multi-task prediction model designed to accurately forecast key features such as retention time (RT), ion intensity, and ion mobility (IM). Leveraging advanced techniques such as multi-head attention and BiLSTM for feature extraction, coupled with Nash-MTL for gradient coordination, ProPept-MT demonstrates superior prediction performance. Integrating ion mobility alongside RT, mass-to-charge ratio (m/z), and ion intensity forms 4D proteomics. Then, we outline a comprehensive workflow tailored for 4D DIA proteomics research, integrating the use of 4D in silico libraries predicted by ProPept-MT. Evaluation on a benchmark dataset showcases ProPept-MT's exceptional predictive capabilities, with impressive results including a 99.9% Pearson correlation coefficient (PCC) for RT prediction, a median dot product (DP) of 96.0% for fragment ion intensity prediction, and a 99.3% PCC for IM prediction on the test set. Notably, ProPept-MT manifests efficacy in predicting both unmodified and phosphorylated peptides, underscoring its potential as a valuable tool for constructing high-quality 4D DIA in silico libraries.

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.

Analysis of Tandem Mass Spectrometry Data with CONGA: Combining Open and Narrow Searches with Group-Wise Analysis

Searching for tandem mass spectrometry proteomics data against a database is a well-established method for assigning peptide sequences to observed spectra but typically cannot identify peptides harboring unexpected post-translational modifications (PTMs). Open modification searching aims to address this problem by allowing a spectrum to match a peptide even if the spectrum's precursor mass differs from the peptide mass. However, expanding the search space in this way can lead to a loss of statistical power to detect peptides. We therefore developed a method, called CONGA (combining open and narrow searches with group-wise analysis), that takes into account results from both types of searches─a traditional "narrow window" search and an open modification search─while carrying out rigorous false discovery rate control. The result is an algorithm that provides the best of both worlds: the ability to detect unexpected PTMs without a concomitant loss of power to detect unmodified peptides.

Inflammatory proteins and neutrophil extracellular traps increase in burn blister fluid 24h after burn

Burn wound blister fluid is a valuable matrix for understanding the biological pathways associated with burn injury. In this study, 152 blister fluid samples collected from paediatric burn wounds at three different hospitals were analysed using mass spectrometry proteomic techniques. The protein abundance profile at different days after burn indicated more proteins were associated with cellular damage/repair in the first 24 h, whereas after this point more proteins were associated with antimicrobial defence. The inflammatory proteins persisted at a high level in the blister fluid for more than 7 days. This may indicate that removal of burn blisters prior to two days after burn is optimal to prevent excessive or prolonged inflammation in the wound environment. Additionally, many proteins associated with the neutrophil extracellular trap (NET) pathway were increased after burn, further implicating NETs in the post-burn inflammatory response. NET inhibitors may therefore be a potential treatment to reduce post-burn inflammation and coagulation pathology and enhance burn wound healing outcomes.

Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer

Mass spectrometry based targeted proteomics methods provide sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semi-stochastic sampling, or by empirical measurements. These strategies require extensive testing and method refinement due to the difficulties associated with prediction of peptide response in the biological matrix of interest. Gas-phase fractionated (GPF) narrow window data-independent acquisition (DIA) aids in the development of reproducible selected reaction monitoring (SRM) assays by providing matrix-specific information on peptide detectability and quantification by mass spectrometry. To demonstrate the suitability of DIA data for selecting peptide targets, we reimplement a portion of an existing assay to measure 98 Alzheimer's disease proteins in cerebrospinal fluid (CSF). Peptides were selected from GPF-DIA based on signal intensity and reproducibility. The resulting SRM assay exhibits similar quantitative precision to published data, despite the inclusion of different peptides between the assays. This workflow enables development of new assays without additional up-front data acquisition, demonstrated here through generation of a separate assay for an unrelated set of proteins in CSF from the same dataset.

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.

Assessment of Kinome-Wide Activity Remodeling upon Picornavirus Infection

Picornaviridae represent a large family of single-stranded positive RNA viruses of which different members can infect both humans and animals. These include the enteroviruses (e.g., poliovirus, coxsackievirus, and rhinoviruses) as well as the cardioviruses (e.g., encephalomyocarditis virus). Picornaviruses have evolved to interact with, use, and/or evade cellular host systems to create the optimal environment for replication and spreading. It is known that viruses modify kinase activity during infection, but a proteome-wide overview of the (de)regulation of cellular kinases during picornavirus infection is lacking. To study the kinase activity landscape during picornavirus infection, we here applied dedicated targeted mass spectrometry-based assays covering ∼40% of the human kinome. Our data show that upon infection, kinases of the MAPK pathways become activated (e.g., ERK1/2, RSK1/2, JNK1/2/3, and p38), while kinases involved in regulating the cell cycle (e.g., CDK1/2, GWL, and DYRK3) become inactivated. Additionally, we observed the activation of CHK2, an important kinase involved in the DNA damage response. Using pharmacological kinase inhibitors, we demonstrate that several of these activated kinases are essential for the replication of encephalomyocarditis virus. Altogether, the data provide a quantitative understanding of the regulation of kinome activity induced by picornavirus infection, providing a resource important for developing novel antiviral therapeutic interventions.

Quantification of Adaptive Immune Responses Against Protein-Binding Interfaces in the Streptococcal M1 Protein

Bacterial or viral antigens can contain subdominant protein regions that elicit weak antibody responses upon vaccination or infection although there is accumulating evidence that antibody responses against subdominant regions can enhance the protective immune response. One proposed mechanism for subdominant protein regions is the binding of host proteins that prevent antibody production against epitopes hidden within the protein binding interfaces. Here, we used affinity purification combined with quantitative mass spectrometry (AP-MS) to examine the level of competition between antigen-specific antibodies and host-pathogen protein interaction networks using the M1 protein from Streptococcus pyogenes as a model system. As most humans have circulating antibodies against the M1 protein, we first used AP-MS to show that the M1 protein interspecies protein network formed with human plasma proteins is largely conserved in naïve mice. Immunizing mice with the M1 protein generated a time-dependent increase of anti-M1 antibodies. AP-MS analysis comparing the composition of the M1-plasma protein network from naïve and immunized mice showed significant enrichment of 292 IgG peptides associated with 56 IgG chains in the immune mice. Despite the significant increase of bound IgGs, the levels of interacting plasma proteins were not significantly reduced in the immune mice. The results indicate that the antigen-specific polyclonal IgG against the M1 protein primarily targets epitopes outside the other plasma protein binding interfaces. In conclusion, this study demonstrates that AP-MS is a promising strategy to determine the relationship between antigen-specific antibodies and host-pathogen interaction networks that could be used to define subdominant protein regions of relevance for vaccine development.

CD8+ T-cell responses towards conserved influenza B virus epitopes across anatomical sites and age

Influenza B viruses (IBVs) cause substantive morbidity and mortality, and yet immunity towards IBVs remains understudied. CD8+ T-cells provide broadly cross-reactive immunity and alleviate disease severity by recognizing conserved epitopes. Despite the IBV burden, only 18 IBV-specific T-cell epitopes restricted by 5 HLAs have been identified currently. A broader array of conserved IBV T-cell epitopes is needed to develop effective cross-reactive T-cell based IBV vaccines. Here we identify 9 highly conserved IBV CD8+ T-cell epitopes restricted to HLA-B*07:02, HLA-B*08:01 and HLA-B*35:01. Memory IBV-specific tetramer+CD8+ T-cells are present within blood and tissues. Frequencies of IBV-specific CD8+ T-cells decline with age, but maintain a central memory phenotype. HLA-B*07:02 and HLA-B*08:01-restricted NP30-38 epitope-specific T-cells have distinct T-cell receptor repertoires. We provide structural basis for the IBV HLA-B*07:02-restricted NS1196-206 (11-mer) and HLA-B*07:02-restricted NP30-38 epitope presentation. Our study increases the number of IBV CD8+ T-cell epitopes, and defines IBV-specific CD8+ T-cells at cellular and molecular levels, across tissues and age.

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.

Proteomic changes induced by longevity-promoting interventions in mice

Using mouse models and high-throughput proteomics, we conducted an in-depth analysis of the proteome changes induced in response to seven interventions known to increase mouse lifespan. This included two genetic mutations, a growth hormone receptor knockout (GHRKO mice) and a mutation in the Pit-1 locus (Snell dwarf mice), four drug treatments (rapamycin, acarbose, canagliflozin, and 17α-estradiol), and caloric restriction. Each of the interventions studied induced variable changes in the concentrations of proteins across liver, kidney, and gastrocnemius muscle tissue samples, with the strongest responses in the liver and limited concordance in protein responses across tissues. To the extent that these interventions promote longevity through common biological mechanisms, we anticipated that proteins associated with longevity could be identified by characterizing shared responses across all or multiple interventions. Many of the proteome alterations induced by each intervention were distinct, potentially implicating a variety of biological pathways as being related to lifespan extension. While we found no protein that was affected similarly by every intervention, we identified a set of proteins that responded to multiple interventions. These proteins were functionally diverse but tended to be involved in peroxisomal oxidation and metabolism of fatty acids. These results provide candidate proteins and biological mechanisms related to enhancing longevity that can inform research on therapeutic approaches to promote healthy aging.

DIP-MS: ultra-deep interaction proteomics for the deconvolution of protein complexes

Most proteins are organized in macromolecular assemblies, which represent key functional units regulating and catalyzing most cellular processes. Affinity purification of the protein of interest combined with liquid chromatography coupled to tandem mass spectrometry (AP-MS) represents the method of choice to identify interacting proteins. The composition of complex isoforms concurrently present in the AP sample can, however, not be resolved from a single AP-MS experiment but requires computational inference from multiple time- and resource-intensive reciprocal AP-MS experiments. Here we introduce deep interactome profiling by mass spectrometry (DIP-MS), which combines AP with blue-native-PAGE separation, data-independent acquisition with mass spectrometry and deep-learning-based signal processing to resolve complex isoforms sharing the same bait protein in a single experiment. We applied DIP-MS to probe the organization of the human prefoldin family of complexes, resolving distinct prefoldin holo- and subcomplex variants, complex-complex interactions and complex isoforms with new subunits that were experimentally validated. Our results demonstrate that DIP-MS can reveal proteome modularity at unprecedented depth and resolution.

DNAJB1-PRKACA fusion neoantigens elicit rare endogenous T cell responses that potentiate cell therapy for fibrolamellar carcinoma

Fibrolamellar carcinoma (FLC) is a liver tumor with a high mortality burden and few treatment options. A promising therapeutic vulnerability in FLC is its driver mutation, a conserved DNAJB1-PRKACA gene fusion that could be an ideal target neoantigen for immunotherapy. In this study, we aim to define endogenous CD8 T cell responses to this fusion in FLC patients and evaluate fusion-specific T cell receptors (TCRs) for use in cellular immunotherapies. We observe that fusion-specific CD8 T cells are rare and that FLC patient TCR repertoires lack large clusters of related TCR sequences characteristic of potent antigen-specific responses, potentially explaining why endogenous immune responses are insufficient to clear FLC tumors. Nevertheless, we define two functional fusion-specific TCRs, one of which has strong anti-tumor activity in vivo. Together, our results provide insights into the fragmented nature of neoantigen-specific repertoires in humans and indicate routes for clinical development of successful immunotherapies for FLC.

TYROBP/DAP12 knockout in Huntington's disease Q175 mice cell-autonomously decreases microglial expression of disease-associated genes and non-cell-autonomously mitigates astrogliosis and motor deterioration

INTRODUCTION

Huntington's disease (HD) is a fatal neurodegenerative disorder caused by an expansion of the CAG trinucleotide repeat in the Huntingtin gene (HTT). Immune activation is abundant in the striatum of HD patients. Detection of active microglia at presymptomatic stages suggests that microgliosis is a key early driver of neuronal dysfunction and degeneration. Recent studies showed that deletion of Tyrobp, a microglial protein, ameliorates neuronal dysfunction in Alzheimer's disease amyloidopathy and tauopathy mouse models while decreasing components of the complement subnetwork.

OBJECTIVE

While TYROBP/DAP12-mediated microglial activation is detrimental for some diseases such as peripheral nerve injury, it is beneficial for other diseases. We sought to determine whether the TYROBP network is implicated in HD and whether Tyrobp deletion impacts HD striatal function and transcriptomics.

METHODS

To test the hypothesis that Tyrobp deficiency would be beneficial in an HD model, we placed the Q175 HD mouse model on a Tyrobp-null background. We characterized these mice with a combination of behavioral testing, immunohistochemistry, transcriptomic and proteomic profiling. Further, we evaluated the gene signature in isolated Q175 striatal microglia, with and without Tyrobp.

RESULTS

Comprehensive analysis of publicly available human HD transcriptomic data revealed that the TYROBP network is overactivated in the HD putamen. The Q175 mice showed morphologic microglial activation, reduced levels of post-synaptic density-95 protein and motor deficits at 6 and 9 months of age, all of which were ameliorated on the Tyrobp-null background. Gene expression analysis revealed that lack of Tyrobp in the Q175 model does not prevent the decrease in the expression of striatal neuronal genes but reduces pro-inflammatory pathways that are specifically active in HD human brain, including genes identified as detrimental in neurodegenerative diseases, e.g. C1q and members of the Ccr5 signaling pathway. Integration of transcriptomic and proteomic data revealed that astrogliosis and complement system pathway were reduced after Tyrobp deletion, which was further validated by immunofluorescence analysis.

CONCLUSIONS

Our data provide molecular and functional support demonstrating that Tyrobp deletion prevents many of the abnormalities in the HD Q175 mouse model, suggesting that the Tyrobp pathway is a potential therapeutic candidate for Huntington's disease.

Substantial downregulation of mitochondrial and peroxisomal proteins during acute kidney injury revealed by data-independent acquisition proteomics

Acute kidney injury (AKI) manifests as a major health concern, particularly for the elderly. Understanding AKI-related proteome changes is critical for prevention and development of novel therapeutics to recover kidney function and to mitigate the susceptibility for recurrent AKI or development of chronic kidney disease. In this study, mouse kidneys were subjected to ischemia-reperfusion injury, and the contralateral kidneys remained uninjured to enable comparison and assess injury-induced changes in the kidney proteome. A ZenoTOF 7600 mass spectrometer was optimized for data-independent acquisition (DIA) to achieve comprehensive protein identification and quantification. Short microflow gradients and the generation of a deep kidney-specific spectral library allowed for high-throughput, comprehensive protein quantification. Upon AKI, the kidney proteome was completely remodeled, and over half of the 3945 quantified protein groups changed significantly. Downregulated proteins in the injured kidney were involved in energy production, including numerous peroxisomal matrix proteins that function in fatty acid oxidation, such as ACOX1, CAT, EHHADH, ACOT4, ACOT8, and Scp2. Injured kidneys exhibited severely damaged tissues and injury markers. The comprehensive and sensitive kidney-specific DIA-MS assays feature high-throughput analytical capabilities to achieve deep coverage of the kidney proteome, and will serve as useful tools for developing novel therapeutics to remediate kidney function.

Proteomic analysis of plasma proteins from patients with cardiac rupture after acute myocardial infarction using TMT-based quantitative proteomics approach

BACKGROUND

Cardiac rupture (CR) is a rare but catastrophic mechanical complication of acute myocardial infarction (AMI) that seriously threatens human health. However, the reliable biomarkers for clinical diagnosis and the underlying signaling pathways insights of CR has yet to be elucidated.

METHODS

In the present study, a quantitative approach with tandem mass tag (TMT) labeling and liquid chromatography-tandem mass spectrometry was used to characterize the differential protein expression profiles of patients with CR. Plasma samples were collected from patients with CR (n = 37), patients with AMI (n = 47), and healthy controls (n = 47). Candidate proteins were selected for validation by multiple reaction monitoring (MRM) and enzyme-linked immunosorbent assay (ELISA).

RESULTS

In total, 1208 proteins were quantified and 958 differentially expressed proteins (DEPs) were identified. The difference in the expression levels of the DEPs was more noticeable between the CR and Con groups than between the AMI and Con groups. Bioinformatics analysis showed most of the DEPs to be involved in numerous crucial biological processes and signaling pathways, such as RNA transport, ribosome, proteasome, and protein processing in the endoplasmic reticulum, as well as necroptosis and leukocyte transendothelial migration, which might play essential roles in the complex pathological processes associated with CR. MRM analysis confirmed the accuracy of the proteomic analysis results. Four proteins i.e., C-reactive protein (CRP), heat shock protein beta-1 (HSPB1), vinculin (VINC) and growth/differentiation factor 15 (GDF15), were further validated via ELISA. By receiver operating characteristic (ROC) analysis, combinations of these four proteins distinguished CR patients from AMI patients with a high area under the curve (AUC) value (0.895, 95% CI, 0.802-0.988, p < 0.001).

CONCLUSIONS

Our study highlights the value of comprehensive proteomic characterization for identifying plasma proteome changes in patients with CR. This pilot study could serve as a valid foundation and initiation point for elucidation of the mechanisms of CR, which might aid in identifying effective diagnostic biomarkers in the future.

MYC targeting by OMO-103 in solid tumors: a phase 1 trial

Among the 'most wanted' targets in cancer therapy is the oncogene MYC, which coordinates key transcriptional programs in tumor development and maintenance. It has, however, long been considered undruggable. OMO-103 is a MYC inhibitor consisting of a 91-amino acid miniprotein. Here we present results from a phase 1 study of OMO-103 in advanced solid tumors, established to examine safety and tolerability as primary outcomes and pharmacokinetics, recommended phase 2 dose and preliminary signs of activity as secondary ones. A classical 3 + 3 design was used for dose escalation of weekly intravenous, single-agent OMO-103 administration in 21-day cycles, encompassing six dose levels (DLs). A total of 22 patients were enrolled, with treatment maintained until disease progression. The most common adverse events were grade 1 infusion-related reactions, occurring in ten patients. One dose-limiting toxicity occurred at DL5. Pharmacokinetics showed nonlinearity, with tissue saturation signs at DL5 and a terminal half-life in serum of 40 h. Of the 19 patients evaluable for response, 12 reached the predefined 9-week time point for assessment of drug antitumor activity, eight of those showing stable disease by computed tomography. One patient defined as stable disease by response evaluation criteria in solid tumors showed a 49% reduction in total tumor volume at best response. Transcriptomic analysis supported target engagement in tumor biopsies. In addition, we identified soluble factors that are potential pharmacodynamic and predictive response markers. Based on all these data, the recommended phase 2 dose was determined as DL5 (6.48 mg kg-1).ClinicalTrials.gov identifier: NCT04808362 .

Prospective observational study on biomarkers of response in pancreatic ductal adenocarcinoma

Adjuvant chemotherapy benefits patients with resected pancreatic ductal adenocarcinoma (PDAC), but the compromised physical state of post-operative patients can hinder compliance. Biomarkers that identify candidates for prompt adjuvant therapy are needed. In this prospective observational study, 1,171 patients with PDAC who underwent pancreatectomy were enrolled and extensively followed-up. Proteomic profiling of 191 patient samples unveiled clinically relevant functional protein modules. A proteomics-level prognostic risk model was established for PDAC, with its utility further validated using a publicly available external cohort. More importantly, through an interaction effect regression analysis leveraging both clinical and proteomic datasets, we discovered two biomarkers (NDUFB8 and CEMIP2), indicative of the overall sensitivity of patients with PDAC to adjuvant chemotherapy. The biomarkers were validated through immunohistochemistry on an internal cohort of 386 patients. Rigorous validation extended to two external multicentic cohorts-a French multicentric cohort (230 patients) and a cohort from two grade-A tertiary hospitals in China (466 patients)-enhancing the robustness and generalizability of our findings. Moreover, experimental validation through functional assays was conducted on PDAC cell lines and patient-derived organoids. In summary, our cohort-scale integration of clinical and proteomic data demonstrates the potential of proteomics-guided prognosis and biomarker-aided adjuvant chemotherapy for PDAC.

Aging impairs the osteocytic regulation of collagen integrity and bone quality

Poor bone quality is a major factor in skeletal fragility in elderly individuals. The molecular mechanisms that establish and maintain bone quality, independent of bone mass, are unknown but are thought to be primarily determined by osteocytes. We hypothesize that the age-related decline in bone quality results from the suppression of osteocyte perilacunar/canalicular remodeling (PLR), which maintains bone material properties. We examined bones from young and aged mice with osteocyte-intrinsic repression of TGFβ signaling (TβRIIocy-/-) that suppresses PLR. The control aged bone displayed decreased TGFβ signaling and PLR, but aging did not worsen the existing PLR suppression in male TβRIIocy-/- bone. This relationship impacted the behavior of collagen material at the nanoscale and tissue scale in macromechanical tests. The effects of age on bone mass, density, and mineral material behavior were independent of osteocytic TGFβ. We determined that the decline in bone quality with age arises from the loss of osteocyte function and the loss of TGFβ-dependent maintenance of collagen integrity.

Dicarboxylic Acid Dietary Supplementation Protects against AKI

SIGNIFICANCE STATEMENT

In this study, we demonstrate that a common, low-cost compound known as octanedioic acid (DC 8 ) can protect mice from kidney damage typically caused by ischemia-reperfusion injury or the chemotherapy drug cisplatin. This compound seems to enhance peroxisomal activity, which is responsible for breaking down fats, without adversely affecting mitochondrial function. DC 8 is not only affordable and easy to administer but also effective. These encouraging findings suggest that DC 8 could potentially be used to assist patients who are at risk of experiencing this type of kidney damage.

BACKGROUND

Proximal tubules are rich in peroxisomes, which are damaged during AKI. Previous studies demonstrated that increasing peroxisomal fatty acid oxidation (FAO) is renoprotective, but no therapy has emerged to leverage this mechanism.

METHODS

Mice were fed with either a control diet or a diet enriched with dicarboxylic acids, which are peroxisome-specific FAO substrates, then subjected to either ischemia-reperfusion injury-AKI or cisplatin-AKI models. Biochemical, histologic, genetic, and proteomic analyses were performed.

RESULTS

Both octanedioic acid (DC 8 ) and dodecanedioic acid (DC 12 ) prevented the rise of AKI markers in mice that were exposed to renal injury. Proteomics analysis demonstrated that DC 8 preserved the peroxisomal and mitochondrial proteomes while inducing extensive remodeling of the lysine succinylome. This latter finding indicates that DC 8 is chain shortened to the anaplerotic substrate succinate and that peroxisomal FAO was increased by DC 8 .

CONCLUSIONS

DC 8 supplementation protects kidney mitochondria and peroxisomes and increases peroxisomal FAO, thereby protecting against AKI.

Acquisition and Analysis of DIA-Based Proteomic Data: A Comprehensive Survey in 2023

Data-independent acquisition (DIA) mass spectrometry (MS) has emerged as a powerful technology for high-throughput, accurate, and reproducible quantitative proteomics. This review provides a comprehensive overview of recent advances in both the experimental and computational methods for DIA proteomics, from data acquisition schemes to analysis strategies and software tools. DIA acquisition schemes are categorized based on the design of precursor isolation windows, highlighting wide-window, overlapping-window, narrow-window, scanning quadrupole-based, and parallel accumulation-serial fragmentation-enhanced DIA methods. For DIA data analysis, major strategies are classified into spectrum reconstruction, sequence-based search, library-based search, de novo sequencing, and sequencing-independent approaches. A wide array of software tools implementing these strategies are reviewed, with details on their overall workflows and scoring approaches at different steps. The generation and optimization of spectral libraries, which are critical resources for DIA analysis, are also discussed. Publicly available benchmark datasets covering global proteomics and phosphoproteomics are summarized to facilitate performance evaluation of various software tools and analysis workflows. Continued advances and synergistic developments of versatile components in DIA workflows are expected to further enhance the power of DIA-based proteomics.

Targeted Phosphoproteomics of Human Saliva Extracellular Vesicles via Multiple Reaction Monitoring Cubed (MRM3)

Oral squamous cell carcinoma (OSCC) has become a global health problem due to its increasing incidence and high mortality rate. Early intervention through monitoring of the diagnostic biomarker levels during OSCC treatment is critical. Extracellular vesicles (EVs) are emerging surrogates in intercellular communication through transporting biomolecule cargo and have recently been identified as a potential source of biomarkers such as phosphoproteins for many diseases. Here, we developed a multiple reaction monitoring cubed (MRM3) method coupled with a novel sample preparation strategy, extracellular vesicles to phosphoproteins (EVTOP), to quantify phosphoproteins using a minimal amount of saliva (50 μL) samples from OSCC patients with high specificity and sensitivity. Our results established differential patterns in the phosphopeptide content of healthy, presurgery, and postsurgery OSCC patient groups. Notably, we discovered significantly increased salivary phosphorylated alpha-amylase (AMY) in the postsurgery group compared to the presurgery group. We hereby present the first targeted MS method with extremely high sensitivity for measuring endogenous phosphoproteins in human saliva EVs.

Targeted Proteomics Reveals Quantitative Differences in Low-Abundance Glycosyltransferases of Patients with Congenital Disorders of Glycosylation

Protein glycosylation is an essential post-translational modification in all domains of life. Its impairment in humans can result in severe diseases named congenital disorders of glycosylation (CDGs). Most of the glycosyltransferases (GTs) responsible for proper glycosylation are polytopic membrane proteins that represent challenging targets in proteomics. We established a multiple reaction monitoring (MRM) assay to comprehensively quantify GTs involved in the processes of N-glycosylation and O- and C-mannosylation in the endoplasmic reticulum. High robustness was achieved by using an enriched membrane protein fraction of isotopically labeled HEK 293T cells as an internal protein standard. The analysis of primary skin fibroblasts from eight CDG type I patients with impaired ALG1, ALG2, and ALG11 genes, respectively, revealed a substantial reduction in the corresponding protein levels. The abundance of the other GTs, however, remained unchanged at the transcript and protein levels, indicating that there is no fail-safe mechanism for the early steps of glycosylation in the endoplasmic reticulum. The established MRM assay was shared with the scientific community via the commonly used open source Skyline software environment, including Skyline Batch for automated data analysis. We demonstrate that another research group could easily reproduce all analysis steps, even while using different LC-MS hardware.

OXR1 maintains the retromer to delay brain aging under dietary restriction

Dietary restriction (DR) delays aging, but the mechanism remains unclear. We identified polymorphisms in mtd, the fly homolog of OXR1, which influenced lifespan and mtd expression in response to DR. Knockdown in adulthood inhibited DR-mediated lifespan extension in female flies. We found that mtd/OXR1 expression declines with age and it interacts with the retromer, which regulates trafficking of proteins and lipids. Loss of mtd/OXR1 destabilized the retromer, causing improper protein trafficking and endolysosomal defects. Overexpression of retromer genes or pharmacological restabilization with R55 rescued lifespan and neurodegeneration in mtd-deficient flies and endolysosomal defects in fibroblasts from patients with lethal loss-of-function of OXR1 variants. Multi-omic analyses in flies and humans showed that decreased Mtd/OXR1 is associated with aging and neurological diseases. mtd/OXR1 overexpression rescued age-related visual decline and tauopathy in a fly model. Hence, OXR1 plays a conserved role in preserving retromer function and is critical for neuronal health and longevity.