Journal of Proteome Research最新文献

Identifying how drugs interact with proteins is fundamental to understanding their therapeutic effects and side effects. While numerous chemical proteomics methods exist for determining protein targets of drugs, each exhibits "blind spots," necessitating complementary approaches. We introduce Above-Filter Digestion Proteomics (AFDIP), which monitors trypsin digestion rates that decrease at ligand-binding sites, while potentially increasing elsewhere. Molecular dynamics simulations showed that these changes relate to backbone flexibility. Using AFDIP, we identified targets of various drugs and metabolites, allowing two-dimensional analysis with the drug concentration as the second dimension. The method identifies binding sites within ≤10 Å of crystallography-determined locations with improved resolution (≤5 Å) for larger proteins. Compared with existing proteolysis approaches, AFDIP offers simpler sample preparation, deeper proteome analysis, and broader sequence coverage. AFDIP addresses the blind spots of current techniques and provides structural insights, enhancing the chemical proteomics toolkit.

Data-independent acquisition (DIA) mass spectrometry is a technique used in proteomics to identify and quantify proteins in complex biological samples. While this comprehensive approach yields more complete and reproducible protein profiles than data-independent acquisition (DDA), the resulting data are substantially larger and more complex, presenting significant challenges for data analysis and interpretation. These challenges can be effectively addressed using dedicated workflow managers that support parallel execution of complex analysis pipelines on high-performance computing infrastructure. Nextflow, in particular, is well-suited for streamlining data analysis, as it automates key aspects of workflow management, allowing researchers to efficiently analyze large-scale data sets with minimal manual intervention. Here, we describe glaDIAtor-nf, a Nextflow version of our software package glaDIAtor for untargeted analysis of DIA mass spectrometry proteomics data. We first demonstrate its technical accuracy through rigorous testing on gold standard data sets. Building on this, we then reveal known proteome patterns from public breast cancer data that remained hidden in the processed data of the original study. This illustrates the potential of reanalyzing the accumulating public data, but also highlights the need for convenient tools to facilitate such reanalysis in large-scale.

With the increasing adoption of discovery -omics in the life sciences, a large number of analysis tools for differential expression analysis (DEA) have been introduced over the years. While such tools tend to be developed with one particular -omics modality in mind, they can often be applied across technologies to solve common issues. This is particularly the case when -omics data share statistical and distributional properties. Herein, we showcase how tools originally developed for transcriptomics analysis are especially well-suited to solving problems in discovery proteomics and metabolomics. Using data from our own experimental work as examples of real-world implementation, we demonstrate how these methods can be used to tackle common DEA issues, such as variable sample quality, hidden batch effects, normalization, and small sample size. We believe this can be useful to novices and seasoned practitioners alike by expanding their toolkits. As multiomic and integrative analyses become commonplace, it is especially useful to capitalize on the similarities of otherwise different -omics.

To explore systemic contributors to central serous chorioretinopathy (CSCR) pathogenesis, we performed untargeted serum proteomics in 60 male CSCR patients (30 acute, 30 chronic) and 60 age-matched controls using label-free LC-MS/MS with stringent statistical pairing. Among 242 abundant proteins identified, 27 (11.5%) were significantly different in CSCR, converging on pathways of complement activation, coagulation, oxidative stress, immune regulation, and response to external stimuli. Complement cascade components (C1QA, C1S, C3, C4B, C8A/B/G, CFB) were upregulated, while the regulators CFHR1 and CFHR2 were decreased, contrary to age-related macular degeneration. Oxidative stress-related proteins (haptoglobin, hemoglobin subunits, peroxiredoxin-2) were elevated, consistent with prior evidence of systemic redox imbalance in CSCR. Tetranectin (CLEC3B) decreased and attractin (ATRN) increased in CSCR were validated by ELISA. Multiplex immunofluorescence on the human retina localized tetranectin to Müller cells, including the outer limiting membrane, and to the RPE and attractin to photoreceptor segments, retinal pigment epithelium, Bruch's membrane, and the choriocapillaris, supporting potential roles of both proteins at the retina-choroid interface. A distinct systemic proteomic signature in patients with CSCR highlights complement dysregulation, oxidative stress, and stress responses to external stimuli and identifies tetranectin and attractin as candidate biomarkers, which should further be validated in other cohorts.

Traumatic brain injury (TBI) constitutes a health burden, with outcomes shaped by the primary injury and the progressive secondary injury cascades leading to the impairment of neuronal integrity, brain homeostasis, and cognitive functions. In the absence of therapies targeting the molecular aftermath of TBIs and the conventional limitations associated with the H₂S donors, the novel H₂S-releasing peptides (SVRN-4) with potent neuroprotective effects provide a rational and promising therapeutic option. In the present study, we evaluated the therapeutic efficacy of SVRN-4 in a mouse model of weight loss TBI (WD-TBI). Our results revealed that SVRN-4 administration significantly reduced TBI-induced tissue disruption and nitric oxide-induced tissue damage and restored mitochondrial integrity. Additionally, neurobehavioral assessments indicated improved neurocognitive functions and motor performance. Furthermore, the global proteomic analysis of WD-TBI revealed altered molecular pathways associated with energy metabolism, apoptosis, neurodevelopment, and protein turnover. Interestingly, SVRN-4 treatment restored alterations in the pathological protein expression involved in mitochondrial function and ATP production and normalized the inflammatory markers. In summary, the proteomic landscape of the H₂S-releasing peptide, SVRN-4-mediated neuroprotection in WD-TBIs revealed its ameliorative effect on the progressive secondary injuries and underscored its potential as a promising therapeutic candidate for promoting functional recovery in TBIs.

We have developed a novel algorithm termed GoldenHaystack (GH) that was designed for enhanced peptide quantification of data-independent acquisition liquid-mass spectrometry (DIA-LC-MS) data files regardless of whether the amino acid sequences are subsequently assigned to the quantified peptide. The two central ideas behind GH are: (a) for sufficiently sized projects (e.g., ≥∼30 LC-MS files), pairs of peptides that coelute exactly in one subset of LC-MS files do not necessarily coelute exactly in a different subset of files, and (b) the ion intensity ratios between MS2 ions for any given peptide tend to stay the same across samples, but the ion intensity ratios of MS2 ions between different peptides tend to differ substantially across different samples. GH thus analyzes a project holistically: It uses multi-partite matching to match both MS2 (primarily) and MS1 (secondarily) ions across all samples, separates and regroups the MS ions into unique analyte quantifiable signatures (UAQS), reduces stochastic noise, and then quantifies those UAQS. In this paper, GH is compared to DIA-NN, a common algorithm used in DIA-MS proteomic analysis, and we demonstrate that GH (a) quantifies and identifies with better FDR accuracy known peptides found in FASTA search spaces (∼5-25% of analytes in DIA-MS data sets), (b) quantifies the remaining ∼75-95% of unassigned peptides that would be typically unquantified and unreported, and (c) runs ∼40-200× faster (or ∼1-10× faster than the LC-MS). Specifically, without a FASTA or spectral library, GH can deconvolute and accurately quantify chimeric LC-MS spectra. The use of a FASTA file occurs during an optional peptide identification step and is deployed only after the analytes in the MS files have already been quantified. We provide details of GH performance on several existing proteomics data sets, including plasma, cerebrospinal fluid, and cells.

Microglia maintain brain homeostasis through coordinated pathways, including cell migration, phagocytosis, and secretion of immune-related signaling factors. Microglial reactivity is associated with a variety of functional outcomes that are highly context-dependent withepigenetic regulation through DNA methylation and histone modifications implicated in this complex control of microglial plasticity. Specifically, in relation to histone methylation, lysine-specific demethylase 5B (KDM5B) has been associated with several pathophysiological states, including neurodevelopmental and inflammatory disorders, cancer, and alcohol use disorder (AUD); however, the cell-type-specific role of KDM5B in microglial reactivity has not been investigated. In this study, transcriptomic and proteomic analyses were used to characterize the effects of KDM5B depletion on microglial pathways in clustered regularly interspaced short palindromic repeats (CRISPR)-edited adult-derived murine microglial cells. Additionally, various immunomodulatory stimuli, including lipopolysaccharide (LPS), interleukin-4, and alcohol, were used to study the effects of KDM5B depletion on immune reactivity in microglia using deep proteomics and bioinformatic analysis. Through this comprehensive characterization, KDM5B-depleted microglia exhibited broad remodeling of immune reactivity, including reduced intracellular and secreted inflammatory responses to lipopolysaccharide as well as distinct modulation of alcohol- and interleukin-4-induced pathways, that was functionally demonstrated by altered cytokine secretion profiles. Results from this study provide critical insight into KDM5B-mediated immunological effects on microglial function.

Benzoylation (Kbz) is a physiologically relevant post-translational modification derived from the food additive sodium benzoate. While Kbz has been implicated in unique cellular regulatory processes, its substrate landscape and functional consequences remain poorly characterized. Conventional antibody-based enrichment methods for Kbz detection suffer from affinity bias and limited specificity. Here, we developed AyBz3, a bioorthogonal chemical probe enabling the unbiased mapping of Kbz across the proteome. Implementation of AyBz3 in HepG2 cells revealed 688 unique Kbz sites, significantly expanding the known benzoylome. Functional analysis revealed that Kbz-modified proteins are enriched in pathways related to protein translation and cell adhesion. Notably, we demonstrated that Kbz modification of nucleophosmin 1 (NPM1) impairs its molecular chaperone function toward p53, resulting in accelerated p53 degradation. Together, this study establishes AyBz3 as a powerful probe for unbiased benzoylome profiling and provides new insights into the regulatory roles of Kbz in cellular processes.

Acinetobacter baumannii causes severe nosocomial opportunistic infections and is rapidly emerging as a global health threat. Despite reports on the rare pigment production in A. baumannii and genomic insights, the molecular mechanisms and their functional implications in virulence driving this rare phenotype remain inadequately characterized. Recognizing this limitation, we performed comparative proteomic profiling of six clinical pyomelanin-producing A. baumannii isolates with four nonpyomelanin-producing isolates. Among the total proteins detected, 66 were up-regulated, and 52 were down-regulated, forming a highly interactive regulatory network in pyomelanin production. Comparative proteomics identified perturbed pathways, including activation of amino acid and pyruvate metabolism, cell membrane biosynthesis, stress response, and virulence factor association, such as biofilm formation, T6 secretion system, highlighting their roles in host adaptation and pathogenicity. Nevertheless, no significant change was noticed in terms of adhesion, cytotoxicity in A549 cell lines, and virulence in Galleria mellonella. Overall, this study expands our understanding of pyomelanin-driven proteomic perturbations in clinical isolates of A. baumannii and helps us to monitor the marked alterations in pigment-producing phenotype, which may provide critical insights for diagnostic and treatment approaches.

Cardiac rehabilitation (CR) is highly beneficial in postmyocardial infarction (MI) patients; however, its metabolic impact remains underexplored. This study investigated metabolic and lipidomic adaptations to an intensive CR program in 25 nondiabetic male patients (<75 years) following a first uncomplicated ST-elevation MI (STEMI). CR involved 24 ± 3 sessions, with baseline and final clinical assessments, and, in a subgroup of 17 patients, longitudinal dried blood spots (DBS) were collected, and metabolomics/lipidomics analysis was also performed. CR significantly improved clinical outcomes, including the 6 min walk test, B-type natriuretic peptide (BNP), left ventricular ejection fraction (LVEF%), C-reactive protein (CRP), and homocysteine levels. Metabolomic analysis showed sustained metabolic adaptations, notably increased N-acetyl-l-tyrosine (NAT), suggesting a mitohormesis response to exercise-induced mitochondrial stress. The third training session exhibited the highest metabolic adaptation, primarily in energy metabolism pathways like the TCA cycle, indicating enhanced oxidative energy generation and improved exercise performance. The lipidome displayed an acute response to the first training, with upregulation of phosphatidylserines (PS). Predicted increased activity of phosphatidylserine synthase-1 (PSS1), enzymes vital for PS synthesis, underscores PS's protective role in myocardial damage and its contribution to muscle activity. These findings highlight CR's beneficial metabolic adaptations, potentially via mitohormesis, and suggest possible mechanistic targets and candidate biomarkers requiring investigation in future controlled intervention studies.