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Analysis of the role of PANoptosis in intervertebral disk degeneration via integrated bioinformatics analysis and experimental validation

Intervertebral disc degeneration (IVDD) is an age-related orthopedic degenerative disease characterized by recurrent episodes of lower back pain, and death of nucleus pulposus cells (NPCs) has been identified as a key factor in the pathophysiological process of IVDD episodes. Recent studies have shown that " PANapoptosis ", a newly characterized form of cell death, has emerged as an important factor contributing to the development of several diseases. However, studies on the specific mechanisms of its role in the development of IVDD are lacking. The aim of this study was to explore the characterization of PANoptosis in IVDD and to identify potential biomarkers and therapeutic targets as well as therapeutic agents. We constructed a PANoptosis gene set, based on the GEO database, and used weighted gene co-expression network analysis (WGCNA) and differential expression analysis to identify PANoptosis genes associated with the pathophysiological process of IVDD episodes by Gene Set Enrichment Analysis (GSEA), immune infiltration, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to explore the underlying biological mechanisms of PANoptosis and its role in IVDD. Comprehensive bioinformatics analysis showed that seven key genes (APAF1, MEFV, NLRP3, TNF, GSDMD, AIM2, and IRF1) of PANoptosis have good diagnostic value. In addition, we predicted potential therapeutic agents, among which Andrographolide (AG) had the highest correlation and binding affinity to the target. Finally, we performed Western blotting and quantitative real-time polymerase chain reaction (qRT-PCR) assays, molecular docking, and cell flow to validate the expression of PANoptosis-related genes and the therapeutic effect of AG. We further divided SD rats into sham-operated, IVDD model, and Andrographolide-treated groups, administered AG at 50 mg/kg via gavage for one month, and observed significant therapeutic effects through HE staining. This study identifies key PANoptosis genes and demonstrates the potential of AG as a therapeutic agent for IVDD.

Identification of Protein Networks and Biological Pathways Driving the Progression of Atherosclerosis in Human Carotid Arteries Through Mass Spectrometry-Based Proteomics

Vulnerable atherosclerotic plaques, especially hemorrhaged lesions, are the major cause of mortalities related to vascular pathologies. The early identification of vulnerable plaques helps to stratify patients at risk of developing acute vascular events. In this study, proteomics analyses of human carotid artery samples collected from patients with atheromatous plaques and complicated lesions, respectively, as well as from healthy controls were performed. The proteins isolated from the carotid artery samples were analyzed by a bottom-up shotgun approach that relied on nanoflow liquid chromatography-tandem mass spectrometry analyses (LC-MS/MS) using both data-dependent (DDA) and data-independent (DIA) acquisitions. The data obtained by high-resolution DIA analyses displayed a stronger distinction among groups compared to DDA analyses. Differentially expressed proteins were further examined using Ingenuity Pathway Analysis® with focus on pathological and molecular processes driving atherosclerosis. From the more than 150 significantly regulated canonical pathways, atherosclerosis signaling and neutrophil extracellular trap signaling were verified by protein-targeted data extraction. The results of our study are expected to facilitate a better understanding of the disease progression's molecular drivers and provide inspiration for further multiomics and hypothesis-driven studies.

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

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

Phosphorylation in the Plasmodium falciparum Proteome: A Meta-Analysis of Publicly Available Data Sets

Malaria is a deadly disease caused by Apicomplexan parasites of the Plasmodium genus. Several species of the Plasmodium genus are known to be infectious to humans, of which P. falciparum is the most virulent. Post-translational modifications (PTMs) of proteins coordinate cell signaling and hence regulate many biological processes in P. falciparum homeostasis and host infection, of which the most highly studied is phosphorylation. Phosphosites on proteins can be identified by tandem mass spectrometry (MS) performed on enriched samples (phosphoproteomics), followed by downstream computational analyses. We have performed a large-scale meta-analysis of 11 publicly available phosphoproteomics data sets to build a comprehensive atlas of phosphosites in the P. falciparum proteome, using robust pipelines aimed at strict control of false identifications. We identified a total of 26,609 phosphorylated sites on P. falciparum proteins, split across three categories of data reliability (gold/silver/bronze). We identified significant sequence motifs, likely indicative of different groups of kinases responsible for different groups of phosphosites. Conservation analysis identified clusters of phosphoproteins that are highly conserved and others that are evolving faster within the Plasmodium genus, and implicated in different pathways. We were also able to identify over 180,000 phosphosites within Plasmodium species beyond falciparum, based on orthologue mapping. We also explored the structural context of phosphosites, identifying a strong enrichment for phosphosites on fast-evolving (low conservation) intrinsically disordered regions (IDRs) of proteins. In other species, IDRs have been shown to have an important role in modulating protein-protein interactions, particularly in signaling, and thus warranting further study for their roles in host-pathogen interactions. All data have been made available via UniProtKB, PRIDE, and PeptideAtlas, with visualization interfaces for exploring phosphosites in the context of other data on Plasmodium proteins.

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

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

Identifying critical modules and biomarkers of intervertebral disc degeneration by using weighted gene co-expression network

Background

Intervertebral disc degeneration (IVDD) is an age-related orthopedic degenerative disease characterized by recurrent episodes of lower back pain, the pathogenesis of which is not fully understood. This study aimed to identify key biomarkers of IVDD and its causes.

Methods

We acquired three gene expression profiles from the Gene Expression Omnibus (GEO) database, GSE56081, GSE124272, and GSE153761, and used limma fast differential analysis to identify differentially expressed genes (DEGs) between normal and IVDD samples after removing batch effects. We applied weighted gene co-expression network (WGCNA) to identify the key modular genes in GSE124272 and intersected these with DEGs. Next, A protein-protein interaction network (PPI) was constructed, and Cytoscape was used to identify the Top 10 hub genes. Functional enrichment analyses were performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Three key genes were validated using Western Blot (WB) and qRT-PCR. Additionally, we predicted miRNAs involved in hub gene co-regulation and analyzed miRNA microarray data from GSE116726 to identify four differentially expressed miRNAs.

Results

We identified 10 hub genes using bioinformatics analysis, gene function enrichment analysis revealed that they were primarily enriched in pathways, such as the TNF signaling pathway. We chose JUNB, SOCS3, and CEBPB as hub genes and used WB and qRT-PCR to confirm their expression. All three genes were overexpressed in the IVDD model group compared to the control group. Furthermore, we identified four miRNAs involved in the co-regulation of the hub genes using miRNet prediction: mir-191-5p, mir-20a-5p, mir-155-5p, and mir-124-3p. Using limma difference analysis, we discovered that mir-191-5p, mir-20a-5p, and mir-155-5p were all down-regulated and expressed in IVDD samples, but mir-124-3p showed no significant change.

Conclusion

JUNB, SOCS3, and CEBPB were identified as key genes in IVDD, regulated by specific miRNAs, providing potential biomarkers for early diagnosis and therapeutic targets.

Influence of different sample preparation approaches on proteoform identification by top-down proteomics

Top-down proteomics using mass spectrometry facilitates the identification of intact proteoforms, that is, all molecular forms of proteins. Multiple past advances have lead to the development of numerous sample preparation workflows. Here we systematically investigated the influence of different sample preparation steps on proteoform and protein identifications, including cell lysis, reduction and alkylation, proteoform enrichment, purification and fractionation. We found that all steps in sample preparation influence the subset of proteoforms identified (for example, their number, confidence, physicochemical properties and artificially generated modifications). The various sample preparation strategies resulted in complementary identifications, substantially increasing the proteome coverage. Overall, we identified 13,975 proteoforms from 2,720 proteins of human Caco-2 cells. The results presented can serve as suggestions for designing and adapting top-down proteomics sample preparation strategies to particular research questions. Moreover, we expect that the sampling bias and modifications identified at the intact protein level will also be useful in improving bottom-up proteomics approaches.

S-allylmercaptocysteine inhibits TLR4-mediated inflammation through enhanced formation of inhibitory MyD88 splice variant in mammary epithelial cells

Mastitis is an inflammatory disease affecting mammary tissues caused by bacterial infection that negatively affects milk quality and quantity. S-Allylmercaptocysteine (SAMC), a sulfur compound in aged garlic extract (AGE), suppresses lipopolysaccharide (LPS)-induced inflammation in mouse models and cell cultures. However, the mechanisms underlying this anti-inflammatory effect remain unclear. In this study, we demonstrated that oral administration of AGE suppressed the LPS-induced immune response in a mastitis mouse model and that SAMC inhibited LPS-induced interleukin-6 production and nuclear factor κB p65 subunit activation in HC11 mammary epithelial cells. Global phosphoproteomic analysis revealed that SAMC treatment downregulated 910 of the 1,304 phosphorylation sites upregulated by LPS stimulation in mammary cells, including those associated with toll-like receptor 4 (TLR4) signaling. Additionally, SAMC decreased the phosphorylation of 26 proteins involved in pre-mRNA splicing, particularly the U2 small nuclear ribonucleoprotein complex. Furthermore, we found that SAMC increased the production of the myeloid differentiation factor 88 short form (MyD88-S), an alternatively spliced form of MyD88 that negatively regulates TLR4 signaling. These findings suggest that SAMC inhibits TLR4-mediated inflammation via alternative pre-mRNA splicing, thus promoting MyD88-S production in mammary epithelial cells. Therefore, SAMC may alleviate various inflammatory diseases, such as mastitis, by modulating immune responses.

IL-1β promotes glutamate excitotoxicity: indications for the link between inflammatory and synaptic vesicle cycle in Ménière's disease

Ménière's disease (MD) is a complex inner ear disorder characterized by a range of symptoms, with its pathogenesis linked to immune-related mechanisms. Our previous research demonstrated that IL-1β maturation and release can trigger cell pyroptosis, exacerbating the severity of the endolymphatic hydrops in a mouse model; however, the specific mechanism through which IL-1β influences MD symptoms remains unclear. This study conducted on patients with MD examined changes in protein signatures in the vestibular end organs (VO) and endolymphatic sac (ES) using mass spectrometry. Gene ontology and protein pathway analyses showed that differentially expressed proteins in the ES are closely related to adhesion, whereas those in the VO are related to synapse processes. Additionally, the study found elevated expression of Glutaminase (GLS) in the VO of MD patients compared to controls. Further investigations revealed that IL-1β increased glutamate levels by upregulating GLS expression in HEI-OC1 cells. Treatment with a GLS inhibitor or an IL-1β receptor antagonist alleviated auditory-vestibular dysfunction and reduced glutamate levels in mice with endolymphatic hydrops. These findings collectively suggest that imbalanced neurotransmitter release and immune responses contribute to the pathology of MD, potentially explaining the hearing loss and vertigo associated with the disease and offering new avenues for therapeutic interventions.

Protein aggregation is a consequence of the dormancy-inducing membrane toxin TisB in Escherichia coli

Bacterial dormancy is a valuable strategy to survive stressful conditions. Toxins from chromosomal toxin-antitoxin systems have the potential to halt cell growth, induce dormancy, and eventually promote a stress-tolerant persister state. Due to their potential toxicity when overexpressed, sophisticated expression systems are needed when studying toxin genes. Here, we present a moderate expression system for toxin genes based on an artificial 5' untranslated region. We applied the system to induce expression of the toxin gene tisB from the chromosomal type I toxin-antitoxin system tisB/istR-1 in Escherichia coli. TisB is a small hydrophobic protein that targets the inner membrane, resulting in depolarization and ATP depletion. We analyzed TisB-producing cells by RNA-sequencing and revealed several genes with a role in recovery from TisB-induced dormancy, including the chaperone genes ibpAB and spy. The importance of chaperone genes suggested that TisB-producing cells are prone to protein aggregation, which was validated by an in vivo fluorescent reporter system. We moved on to show that TisB is an essential factor for protein aggregation upon DNA damage mediated by the fluoroquinolone antibiotic ciprofloxacin in E. coli wild-type cells. The occurrence of protein aggregates correlates with an extended dormancy duration, which underscores their importance for the life cycle of TisB-dependent persister cells.

IMPORTANCE

Protein aggregates occur in all living cells due to misfolding of proteins. In bacteria, protein aggregation is associated with cellular inactivity, which is related to dormancy and tolerance to stressful conditions, including exposure to antibiotics. In Escherichia coli, the membrane toxin TisB is an important factor for dormancy and antibiotic tolerance upon DNA damage mediated by the fluoroquinolone antibiotic ciprofloxacin. Here, we show that TisB provokes protein aggregation, which, in turn, promotes an extended state of cellular dormancy. Our study suggests that protein aggregation is a consequence of membrane toxins with the potential to affect the duration of dormancy and the outcome of antibiotic therapy.

What is the real value of omics data? Enhancing research outcomes and securing long-term data excellence

A wealth of high-throughput biological data, of which omics constitute a significant fraction, has been made publicly available in repositories over the past decades. These data come in various formats and cover a range of species and research areas providing insights into the complexities of biological systems; the public repositories hosting these data serve as multifaceted resources. The potentially greater value of these data lies in their secondary utilization as the deployment of data science and artificial intelligence in biology advances. Here, we critically evaluate challenges in secondary data use, focusing on omics data of human embryonic kidney cell lines available in public repositories. The emerging issues are obstacles faced by secondary data users across diverse domains as they concern platforms and repositories, which accept deposition of data irrespective of their species type. The evolving landscape of data-driven research in biology prompts re-evaluation of open access data curation and submission procedures to ensure that these challenges do not impede novel research opportunities through data exploitation. This paper aims to draw attention to widespread issues with data reporting and encourages data owners to meticulously curate submissions to maximize not only their immediate research impact but also the long-term legacy of datasets.

Mass Spectrometry Advances in Analysis of Glioblastoma

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

Identification of Estrogen-Responsive Proteins in Mouse Seminal Vesicles Through Mass Spectrometry-Based Proteomics

Background: Although estrogenic compounds promise therapeutic potential in treating various conditions, concerns regarding their endocrine-disrupting effects have been raised. Current methodologies for screening estrogenicity in rodent models are limited to the female-specific uterotrophic bioassay. Studies have reported enlargement of the seminal vesicles in orchiectomized males treated with estrogens. However, identifying estrogenicity strictly through changes in wet weights is uninformative regarding the molecular mechanisms of these agents. Therefore, protein-based biomarkers can complement and improve the sensitivity of weight-based assessments. To this end, we present a discovery-driven proteomic analysis of 17β-estradiol's effects on the seminal vesicles. Methods: We treated orchidectomized mice with the hormone for five days and used the vehicle-treated group as a control. Seminal vesicles were analyzed by shotgun approach using data-dependent nanoflow liquid chromatography-tandem mass spectrometry and label-free quantification. Proteins found to be differentially expressed between the two groups were processed through a bioinformatics pipeline focusing on pathway analyses and assembly of protein interaction networks. Results: Out of 668 identified proteins that passed rigorous validation criteria, 133 were regulated significantly by 17β-estradiol. Ingenuity Pathway Analysis® linked them to several hormone-affected pathways, including those associated with immune function such as neutrophil degranulation. The altered protein interaction networks were also related to functions including endocrine disruption, abnormal metabolism, and therapeutic effects. Conclusions: We identified several potential biomarkers for estrogenicity in mouse seminal vesicles, many of them not previously linked with exogenous 17β-estradiol exposure.

BAG3 regulates cilia homeostasis of glioblastoma via its WW domain

The multidomain protein BAG3 exerts pleiotropic oncogenic functions in many tumor entities including glioblastoma (GBM). Here, we compared BAG3 protein-protein interactions in either adherently cultured or stem-like cultured U251 GBM cells. In line with BAG3's putative role in regulating stem-like properties, identified interactors in sphere-cultured cells included different stem cell markers (SOX2, OLIG2, and NES), while interactomes of adherent BAG3-proficient cells indicated a shift toward involvement of BAG3 in regulation of cilium assembly (ACTR3 and ARL3). Applying a set of BAG3 deletion constructs we could demonstrate that none of the domains except the WW domain are required for suppression of cilia formation by full-length BAG3 in U251 and U343 cells. In line with the established regulation of the Hippo pathway by this domain, we could show that the WW mutant fails to rescue YAP1 nuclear translocation. BAG3 depletion reduced activation of a YAP1/AURKA signaling pathway and induction of PLK1. Collectively, our findings point to a complex interaction network of BAG3 with several pathways regulating cilia homeostasis, involving processes related to ciliogenesis and cilium degradation.

Computational Strategies for Assessing Adverse Outcome Pathways: Hepatic Steatosis as a Case Study

The evolving landscape of chemical risk assessment is increasingly focused on developing tiered, mechanistically driven approaches that avoid the use of animal experiments. In this context, adverse outcome pathways have gained importance for evaluating various types of chemical-induced toxicity. Using hepatic steatosis as a case study, this review explores the use of diverse computational techniques, such as structure-activity relationship models, quantitative structure-activity relationship models, read-across methods, omics data analysis, and structure-based approaches to fill data gaps within adverse outcome pathway networks. Emphasizing the regulatory acceptance of each technique, we examine how these methodologies can be integrated to provide a comprehensive understanding of chemical toxicity. This review highlights the transformative impact of in silico techniques in toxicology, proposing guidelines for their application in evidence gathering for developing and filling data gaps in adverse outcome pathway networks. These guidelines can be applied to other cases, advancing the field of toxicological risk assessment.

Metabolomic Profiling Reveals Potential of Fatty Acids as Regulators of Stem-like Exhausted CD8 T Cells During Chronic Viral Infection

Chronic infections drive a CD8 T cell program termed T cell exhaustion, characterized by reduced effector functions. While cell-intrinsic mechanisms underlying CD8 T cell exhaustion have been extensively studied, the impact of the metabolic environment in which exhausted CD8 T cells (Tex) operate remains less clear. Using untargeted metabolomics and the murine lymphocytic choriomeningitis virus infection model we investigated systemic metabolite changes early and late following acute versus chronic viral infections. We identified distinct short-term and persistent metabolite shifts, with the most significant differences occurring transiently during the acute phase of the sustained infection. This included nutrient changes that were independent of viral loads and partially associated with CD8 T cell-induced anorexia and lipolysis. One remarkable observation was the elevation of medium- and long-chain fatty acid (FA) and acylcarnitines during the early phase after chronic infection. During this time, virus-specific CD8 T cells from chronically infected mice exhibited increased lipid accumulation and uptake compared to their counterparts from acute infection, particularly stem-like Tex (Tex STEM ), a subset that generates effector-like Tex INT which directly limit viral replication. Notably, only Tex STEM increased oxidative metabolism and ATP production upon FA exposure. Consistently, short-term reintroduction of FA during late chronic infection exclusively improved Tex STEM mitochondrial fitness, percentages and numbers. This treatment, however, also reduced Tex INT , resulting in compromised viral control. Our study offers a valuable resource for investigating the role of specific metabolites in regulating immune responses during acute and chronic viral infections and highlights the potential of long-chain FA to influence Tex STEM and viral control during a protracted infection.

Significance

This study examines systemic metabolite changes during acute and chronic viral infections. Notably, we identified an early, transient nutrient shift in chronic infection, marked by an increase in medium- and long-chain fatty acid related species. Concomitantly, a virus-specific stem-like T cell population, essential for maintaining other T cells, displayed high lipid avidity and was capable of metabolizing exogenous fatty acids. Administering fatty acids late in chronic infection, when endogenous lipid levels had normalized, expanded this stem-like T cell population and enhanced their mitochondrial fitness. These findings highlight the potential role of fatty acids in regulating stem-like T cells in chronic settings and offer a valuable resource for studying other metabolic signatures in both acute and persistent infections.

Uncovering the small proteome of Methanosarcina mazei using Ribo-seq and peptidomics under different nitrogen conditions

The mesophilic methanogenic archaeal model organism Methanosarcina mazei strain Gö1 is crucial for climate and environmental research due to its ability to produce methane. Here, we establish a Ribo-seq protocol for M. mazei strain Gö1 under two growth conditions (nitrogen sufficiency and limitation). The translation of 93 previously annotated and 314 unannotated small ORFs, coding for proteins ≤ 70 amino acids, is predicted with high confidence based on Ribo-seq data. LC-MS analysis validates the translation for 62 annotated small ORFs and 26 unannotated small ORFs. Epitope tagging followed by immunoblotting analysis confirms the translation of 13 out of 16 selected unannotated small ORFs. A comprehensive differential transcription and translation analysis reveals that 29 of 314 unannotated small ORFs are differentially regulated in response to nitrogen availability at the transcriptional and 49 at the translational level. A high number of reported small RNAs are emerging as dual-function RNAs, including sRNA154, the central regulatory small RNA of nitrogen metabolism. Several unannotated small ORFs are conserved in Methanosarcina species and overproducing several (small ORF encoded) small proteins suggests key physiological functions. Overall, the comprehensive analysis opens an avenue to elucidate the function(s) of multitudinous small proteins and dual-function RNAs in M. mazei.

The global phosphorylation landscape of mouse oocytes during meiotic maturation

Phosphorylation is a key post-translational modification regulating protein function and biological outcomes. However, the phosphorylation dynamics orchestrating mammalian oocyte development remains poorly understood. In the present study, we apply high-resolution mass spectrometry-based phosphoproteomics to obtain the first global in vivo quantification of mouse oocyte phosphorylation. Of more than 8000 phosphosites, 75% significantly oscillate and 64% exhibit marked upregulation during meiotic maturation, indicative of the dominant regulatory role. Moreover, we identify numerous novel phosphosites on oocyte proteins and a few highly conserved phosphosites in oocytes from different species. Through functional perturbations, we demonstrate that phosphorylation status of specific sites participates in modulating critical events including metabolism, translation, and RNA processing during meiosis. Finally, we combine inhibitor screening and enzyme-substrate network prediction to discover previously unexplored kinases and phosphatases that are essential for oocyte maturation. In sum, our data define landscape of the oocyte phosphoproteome, enabling in-depth mechanistic insights into developmental control of germ cells.

How processing affects marker peptide quantification - A comprehensive estimation on bovine material relevant for food and feed control

Processing food and feed challenges official control e.g. by modifying proteins, which leads to significant underestimation in targeted, MS-based protein quantification. Whereas numerous studies identified processing-induced changes on proteins in various combinations of matrices and processing conditions, studying their impact semi-quantitatively on specific protein sequences might unveil approaches to improve protein quantification accuracy. Thus, 335 post-translational modifications (e.g. oxidation, deamidation, carboxymethylation, Amadori, acrolein adduction) were identified by bottom-up proteomic analysis of 37 bovine materials relevant in food and feed (meat, bone, blood, milk) with varying processing degrees (raw, spray-dried, pressure-sterilized). To mimic protein recovery in a targeted analysis, peak areas of marker and reference peptides were compared to those of their modified versions, which revealed peptide-specific recoveries and variances across all samples. Detailed analysis suggests that incorporating two modified versions additionally to the unmodified marker may significantly improve quantification accuracy in targeted MS-based food and feed control in processed matrices.

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

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

Insights into the Role of VPS39 and Its Interaction with CP204L and A137R in ASFV Infection

The African swine fever virus (ASFV) is a large and complex DNA virus that causes a highly lethal disease in swine, for which no antiviral drugs or vaccines are currently available. Studying viral-host protein-protein interactions advances our understanding of the molecular mechanisms underlying viral replication and pathogenesis and can facilitate the discovery of antiviral therapeutics. In this study, we employed affinity tagging and purification mass spectrometry to characterize the interactome of VPS39, an important cellular factor during the early phase of ASFV replication. The interaction network of VPS39 revealed associations with mitochondrial proteins involved in membrane contact sites formation and cellular respiration. We show that the ASFV proteins CP204L and A137R target VPS39 by interacting with its clathrin heavy-chain functional domain. Furthermore, we elaborate on the potential mechanisms by which VPS39 may contribute to ASFV replication and prioritize interactions for further investigation into mitochondrial protein function in the context of ASFV infection.

Nphos: Database and Predictor of Protein N-phosphorylation

Protein N-phosphorylation is widely present in nature and participates in various biological processes. However, current knowledge on N-phosphorylation is extremely limited compared to that on O-phosphorylation. In this study, we collected 11,710 experimentally verified N-phosphosites of 7344 proteins from 39 species and subsequently constructed the database Nphos to share up-to-date information on protein N-phosphorylation. Upon these substantial data, we characterized the sequential and structural features of protein N-phosphorylation. Moreover, after comparing hundreds of learning models, we chose and optimized gradient boosting decision tree (GBDT) models to predict three types of human N-phosphorylation, achieving mean area under the receiver operating characteristic curve (AUC) values of 90.56%, 91.24%, and 92.01% for pHis, pLys, and pArg, respectively. Meanwhile, we discovered 488,825 distinct N-phosphosites in the human proteome. The models were also deployed in Nphos for interactive N-phosphosite prediction. In summary, this work provides new insights and points for both flexible and focused investigations of N-phosphorylation. It will also facilitate a deeper and more systematic understanding of protein N-phosphorylation modification by providing a data and technical foundation. Nphos is freely available at http://www.bio-add.org/Nphos/ and http://ppodd.org.cn/Nphos/.

Infant Milk Formula Enriched in Dairy Cream Brings Its Digestibility Closer to Human Milk and Supports Intestinal Health in Pre-Clinical Studies

Human breast milk (HBM) is the "gold standard" for infant nutrition. When breast milk is insufficient or unavailable, infant milk formula (IMF) can provide a safe and nutritious alternative. However, IMFs differ considerably from HBM in composition and health function. We compared the digestibility and potential health functions of IMF containing low cream (LC-) or high cream (HC-) with pooled HBM. After simulated infant digestion of these samples, the bioavailability of key nutrients and immunomodulatory activities were determined via cell-based in vitro assays. A Caenorhabditis elegans leaky gut model was established to investigate cream effects on gut health. Distinct differences were observed in peptide diversity and sequences released from HC-IMF compared with LC-IMF during simulated digestion (p < 0.05). Higher levels of free fatty acids were absorbed through 21-day differentiated Caco-2/HT-29MTX monolayers from HC-IMF, compared with LC-IMF and HBM (p < 0.05). Furthermore, the immune-modulating properties of HC-IMF appeared to be more similar to HBM than LC-IMF, as observed by comparable secretion of cytokines IL-10 and IL-1β from THP-1 macrophages (p > 0.05). HC-IMF also supported intestinal recovery in C. elegans following distortion versus LC-IMF (p < 0.05). These observations suggest that cream as a lipid source in IMF may provide added nutritional and functional benefits more aligned with HBM.

High-quality peptide evidence for annotating non-canonical open reading frames as human proteins

A major scientific drive is to characterize the protein-coding genome as it provides the primary basis for the study of human health. But the fundamental question remains: what has been missed in prior genomic analyses? Over the past decade, the translation of non-canonical open reading frames (ncORFs) has been observed across human cell types and disease states, with major implications for proteomics, genomics, and clinical science. However, the impact of ncORFs has been limited by the absence of a large-scale understanding of their contribution to the human proteome. Here, we report the collaborative efforts of stakeholders in proteomics, immunopeptidomics, Ribo-seq ORF discovery, and gene annotation, to produce a consensus landscape of protein-level evidence for ncORFs. We show that at least 25% of a set of 7,264 ncORFs give rise to translated gene products, yielding over 3,000 peptides in a pan-proteome analysis encompassing 3.8 billion mass spectra from 95,520 experiments. With these data, we developed an annotation framework for ncORFs and created public tools for researchers through GENCODE and PeptideAtlas. This work will provide a platform to advance ncORF-derived proteins in biomedical discovery and, beyond humans, diverse animals and plants where ncORFs are similarly observed.

Concerted SUMO-targeted ubiquitin ligase activities of TOPORS and RNF4 are essential for stress management and cell proliferation

Protein SUMOylation provides a principal driving force for cellular stress responses, including DNA-protein crosslink (DPC) repair and arsenic-induced PML body degradation. In this study, using genome-scale screens, we identified the human E3 ligase TOPORS as a key effector of SUMO-dependent DPC resolution. We demonstrate that TOPORS promotes DPC repair by functioning as a SUMO-targeted ubiquitin ligase (STUbL), combining ubiquitin ligase activity through its RING domain with poly-SUMO binding via SUMO-interacting motifs, analogous to the STUbL RNF4. Mechanistically, TOPORS is a SUMO1-selective STUbL that complements RNF4 in generating complex ubiquitin landscapes on SUMOylated targets, including DPCs and PML, stimulating efficient p97/VCP unfoldase recruitment and proteasomal degradation. Combined loss of TOPORS and RNF4 is synthetic lethal even in unstressed cells, involving defective clearance of SUMOylated proteins from chromatin accompanied by cell cycle arrest and apoptosis. Our findings establish TOPORS as a STUbL whose parallel action with RNF4 defines a general mechanistic principle in crucial cellular processes governed by direct SUMO-ubiquitin crosstalk.

A role for the S4-domain containing protein YlmH in ribosome-associated quality control in Bacillus subtilis

Ribosomes trapped on mRNAs during protein synthesis need to be rescued for the cell to survive. The most ubiquitous bacterial ribosome rescue pathway is trans-translation mediated by tmRNA and SmpB. Genetic inactivation of trans-translation can be lethal, unless ribosomes are rescued by ArfA or ArfB alternative rescue factors or the ribosome-associated quality control (RQC) system, which in Bacillus subtilis involves MutS2, RqcH, RqcP and Pth. Using transposon sequencing in a trans-translation-incompetent B. subtilis strain we identify a poorly characterized S4-domain-containing protein YlmH as a novel potential RQC factor. Cryo-EM structures reveal that YlmH binds peptidyl-tRNA-50S complexes in a position analogous to that of S4-domain-containing protein RqcP, and that, similarly to RqcP, YlmH can co-habit with RqcH. Consistently, we show that YlmH can assume the role of RqcP in RQC by facilitating the addition of poly-alanine tails to truncated nascent polypeptides. While in B. subtilis the function of YlmH is redundant with RqcP, our taxonomic analysis reveals that in multiple bacterial phyla RqcP is absent, while YlmH and RqcH are present, suggesting that in these species YlmH plays a central role in the RQC.

Covalent penicillin-protein conjugates elicit anti-drug antibodies that are clonally and functionally restricted

Many archetypal and emerging classes of small-molecule therapeutics form covalent protein adducts. In vivo, both the resulting conjugates and their off-target side-conjugates have the potential to elicit antibodies, with implications for allergy and drug sequestration. Although β-lactam antibiotics are a drug class long associated with these immunological phenomena, the molecular underpinnings of off-target drug-protein conjugation and consequent drug-specific immune responses remain incomplete. Here, using the classical β-lactam penicillin G (PenG), we probe the B and T cell determinants of drug-specific IgG responses to such conjugates in mice. Deep B cell clonotyping reveals a dominant murine clonal antibody class encompassing phylogenetically-related IGHV1, IGHV5 and IGHV10 subgroup gene segments. Protein NMR and x-ray structural analyses reveal that these drive structurally convergent binding modes in adduct-specific antibody clones. Their common primary recognition mechanisms of the penicillin side-chain moiety (phenylacetamide in PenG)-regardless of CDRH3 length-limits cross-reactivity against other β-lactam antibiotics. This immunogenetics-guided discovery of the limited binding solutions available to antibodies against side products of an archetypal covalent inhibitor now suggests future potential strategies for the 'germline-guided reverse engineering' of such drugs away from unwanted immune responses.

Numbers of Exchangeable Hydrogens from LC-MS Data of Heavy Water Metabolically Labeled Samples

Labeling with deuterium oxide (D2O) has emerged as one of the preferred approaches for measuring the synthesis of individual proteins in vivo. In these experiments, the synthesis rates of proteins are determined by modeling mass shifts in peptides during the labeling period. This modeling depends on a theoretical maximum enrichment determined by the number of labeling sites (NEH) of each amino acid in the peptide sequence. Currently, NEH is determined from one set of published values. However, it has been demonstrated that NEH can differ between species and potentially tissues. The goal of this work was to determine the number of NEH for each amino acid within a given experiment to capture the conditions unique to that experiment. We used four methods to compute the NEH values. To test these approaches, we used two publicly available data sets. In a de novo approach, we compute NEH values and the label enrichment from the abundances of three mass isotopomers. The other three methods use the complete isotope profiles and body water enrichment in deuterium as an input parameter. They determine the NEH values by (1) minimizing the residual sum of squares, (2) from the mole percent excess of labeling, and (3) the time course profile of the depletion of the relative isotope abundance of monoisotope. In the test samples, the method using residual sum of squares performed the best. The methods are implemented in a tool for determining the NEH for each amino acid within a given experiment to use in the determination of protein synthesis rates using D2O.

Full Native timsTOF PASEF-Enabled Quantitative Proteomics with the i2MassChroQ Software Package

Ion mobility mass spectrometry has become popular in proteomics lately, in particular because the Bruker timsTOF instruments have found significant adoption in proteomics facilities. The Bruker's implementation of the ion mobility dimension generates massive amounts of mass spectrometric data that require carefully designed software both to extract meaningful information and to perform processing tasks at reasonable speed. In a historical move, the Bruker company decided to harness the skills of the scientific software development community by releasing to the public the timsTOF data file format specification. As a proteomics facility that has been developing Free Open Source Software (FOSS) solutions since decades, we took advantage of this opportunity to implement the very first FOSS proteomics complete solution to natively read the timsTOF data, low-level process them, and explore them in an integrated quantitative proteomics software environment. We dubbed our software i2MassChroQ because it implements a (peptide)identification-(protein)inference-mass-chromatogram-quantification processing workflow. The software benchmarking results reported in this paper show that i2MassChroQ performed better than competing software on two critical characteristics: (1) feature extraction capability and (2) protein quantitative dynamic range. Altogether, i2MassChroQ yielded better quantified protein numbers, both in a technical replicate MS runs setting and in a differential protein abundance analysis setting.

The Influence of the FFAR4 Agonist TUG-891 on Liver Steatosis in ApoE-Knockout Mice

BACKGROUND

Nonalcoholic fatty liver disease (NAFLD) constitutes an independent risk factor for the development of coronary heart disease. Low-grade inflammation has been shown to play an important role in the development of atherosclerosis and NAFLD. Free fatty acid receptor 4 (FFAR4/GPR120), which is involved in damping inflammatory reactions, may represent a promising target for the treatment of inflammatory diseases. Our objective was to evaluate the effect of TUG-891, the synthetic agonist of FFAR4/GPR120, on fatty liver in vivo.

METHODS

The effect of TUG-891 on fatty liver was investigated in apoE-/- mice fed a high-fat diet (HFD), using microscopic, biochemical, molecular, and proteomic methods.

RESULTS

Treatment with TUG-891 inhibited the progression of liver steatosis in apoE-/- mice, as evidenced by histological analysis, and reduced the accumulation of TG in the liver. This action was associated with a decrease in plasma AST levels. TUG-891 decreased the expression of liver genes and proteins involved in de novo lipogenesis (Srebp-1c, Fasn and Scd1) and decreased the expression of genes related to oxidation and uptake (Acox1, Ehhadh, Cd36, Fabp1). Furthermore, TUG-891 modified the levels of selected factors related to glucose metabolism (decreased Glut2, Pdk4 and Pklr, and increased G6pdx).

CONCLUSION

Pharmacological stimulation of FFAR4 may represent a promising lead in the search for drugs that inhibit NAFLD.

Multi-layered metabolic effects of trehalose on the liver proteome in apoE-knockout mice model of liver steatosis

BACKGROUND

Metabolic dysfunction-associated fatty liver disease has been well documented as a key independent risk factor for the development of atherosclerosis. A growing body of evidence suggests that due to its numerous favorable molecular effects, trehalose may exert beneficial effects in counteracting liver steatosis. In our previous study, we described the antiatherosclerotic and antisteatotic properties of trehalose, which we attributed to the induction of autophagy. Considering the pleiotropic activities of trehalose, our present study aimed to extend our preliminary results with the comprehensive examination of proteome-wide changes in the livers of high-fat-fed apoE-/- mice.

METHODS

Thus, we applied modern, next-generation proteomic methodology to comprehensively analyze the effects of trehalose on the alterations of liver proteins in apoE-/- mice.

RESULTS

Our proteomic analysis showed that the administration of trehalose elicited profound changes in the liver proteome of apoE-/- mice. The collected data allowed the identification and quantitation of 3 681 protein groups of which 129 were significantly regulated in the livers of trehalose-treated apoE-/- mice.

CONCLUSIONS

The presented results are the first to highlight the effects of disaccharide on the induction of proteins mainly related to the metabolism and elimination of lipids, especially by peroxisomal β-oxidation. Our study provides evidence for the pleiotropic activity of trehalose, extending our initial observations of its potential mechanisms responsible for mitigating of liver steatosis, which paves the way for new pharmacological strategies in fatty liver disease.

Saccharomyces cerevisiae β-glucan improves the response of trained macrophages to severe P. aeruginosa infections

OBJECTIVE P. AERUGINOSA: (PA), the major pathogen of lung cystic fibrosis (CF), polarizes macrophages into hyperinflammatory tissue damaging phenotype. The main aim of this study was to verify whether training of macrophages with β-glucan might improve their response to P. aeruginosa infections.

METHODS

To perform this task C57BL/6 mice sensitive to infections with P. aeruginosa were used. Peritoneal macrophages were trained with Saccharomyces cerevisiae β-glucan and exposed to PA57, the strong biofilm-forming bacterial strain isolated from the patient with severe lung CF. The release of cytokines and the expression of macrophage phenotypic markers were measured. A quantitative proteomic approach was used for the characterization of proteome-wide changes in macrophages. The effect of in vivo β-glucan-trained macrophages in the air pouch model of PA57 infection was investigated. In all experiments the effect of trained and naïve macrophages was compared.

RESULTS

Trained macrophages acquired a specific phenotype with mixed pro-inflammatory and pro-resolution characteristics, however they retained anti-bacterial properties. Most importantly, transfer of trained macrophages into infected air pouches markedly ameliorated the course of infection. PA57 bacterial growth and formation of biofilm were significantly suppressed. The level of serum amyloid A (SAA), a systemic inflammation biomarker, was reduced.

CONCLUSIONS

Training of murine macrophages with S. cerevisiae β-glucan improved macrophage defense properties along with inhibition of secretion of some detrimental inflammatory agents. We suggest that training of macrophages with such β-glucans might be a new therapeutic strategy in P. aeruginosa biofilm infections, including CF, to promote eradication of pathogens and resolution of inflammation.

MIB2 Functions in Oocyte Meiosis by Modulating Chromatin Configuration

Chromatin configuration serves as a principal indicator of GV (germinal vesicle)-stage oocyte quality. However, the underlying mechanisms governing the chromatin configuration transition from NSN (non-surrounded nucleolus) to SN (surrounded nucleolus) remain unclear. In this study, by conducting a quantitative proteomic analysis, we identified an increased expression of the MIB2 (MIB E3 ubiquitin protein ligase 2) protein in SN oocytes. Specific depletion of MIB2 in SN oocytes not only leads to severe disruption of the meiotic apparatus and a higher incidence of aneuploidy but also adversely affects meiotic maturation and early embryo development. Notably, overexpression of MIB2 in NSN oocytes facilitates the chromatin configuration transition. Meantime, we observed that forced expression of MIB2 in NSN oocytes significantly mitigates spindle/chromosome disorganization and aneuploidy. In summary, our results suggest that chromatin configuration transition regulated by MIB2 is crucial for oocytes to acquire developmental competence.

DNA O-MAP uncovers the molecular neighborhoods associated with specific genomic loci

The accuracy of crucial nuclear processes such as transcription, replication, and repair, depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed "DNA O-MAP", which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with sample multiplexed quantitative proteomics and next-generation sequencing to quantify DNA-protein and DNA-DNA interactions at specific genomic loci.

Computational methods and biomarker discovery strategies for spatial proteomics: a review in immuno-oncology

Advancements in imaging technologies have revolutionized our ability to deeply profile pathological tissue architectures, generating large volumes of imaging data with unparalleled spatial resolution. This type of data collection, namely, spatial proteomics, offers invaluable insights into various human diseases. Simultaneously, computational algorithms have evolved to manage the increasing dimensionality of spatial proteomics inherent in this progress. Numerous imaging-based computational frameworks, such as computational pathology, have been proposed for research and clinical applications. However, the development of these fields demands diverse domain expertise, creating barriers to their integration and further application. This review seeks to bridge this divide by presenting a comprehensive guideline. We consolidate prevailing computational methods and outline a roadmap from image processing to data-driven, statistics-informed biomarker discovery. Additionally, we explore future perspectives as the field moves toward interfacing with other quantitative domains, holding significant promise for precision care in immuno-oncology.

Characterization of a lipid-based jumbo phage compartment as a hub for early phage infection

Viral genomes are most vulnerable to cellular defenses at the start of the infection. A family of jumbo phages related to phage ΦKZ, which infects Pseudomonas aeruginosa, assembles a protein-based phage nucleus to protect replicating phage DNA, but how it is protected prior to phage nucleus assembly is unclear. We find that host proteins related to membrane and lipid biology interact with injected phage protein, clustering in an early phage infection (EPI) vesicle. The injected virion RNA polymerase (vRNAP) executes early gene expression until phage genome separation from the vRNAP and the EPI vesicle, moving into the nascent proteinaceous phage nucleus. Enzymes involved in DNA replication and CRISPR/restriction immune nucleases are excluded by the EPI vesicle. We propose that the EPI vesicle is rapidly constructed with injected phage proteins, phage DNA, host lipids, and host membrane proteins to enable genome protection, early transcription, localized translation, and to ensure faithful genome transfer to the proteinaceous nucleus.

Directional integration and pathway enrichment analysis for multi-omics data

Omics techniques generate comprehensive profiles of biomolecules in cells and tissues. However, a holistic understanding of underlying systems requires joint analyses of multiple data modalities. We present DPM, a data fusion method for integrating omics datasets using directionality and significance estimates of genes, transcripts, or proteins. DPM allows users to define how the input datasets are expected to interact directionally given the experimental design or biological relationships between the datasets. DPM prioritises genes and pathways that change consistently across the datasets and penalises those with inconsistent directionality. To demonstrate our approach, we characterise gene and pathway regulation in IDH-mutant gliomas by jointly analysing transcriptomic, proteomic, and DNA methylation datasets. Directional integration of survival information in ovarian cancer reveals candidate biomarkers with consistent prognostic signals in transcript and protein expression. DPM is a general and adaptable framework for gene prioritisation and pathway analysis in multi-omics datasets.

Identifying PE2 and PE5 Proteins from Existing Mass Spectrometry Data Using pFind

The Chromosome-Centric Human Proteome Project (C-HPP) aims to identify all proteins encoded by the human genome. Currently, the human proteome still contains approximately 2000 PE2-PE5 proteins, referring to annotated coding genes that lack sufficient protein-level evidence. During the past 10 years, it has been increasingly difficult to identify PE2-PE5 proteins in C-HPP approaches due to the limited occurrence. Therefore, we proposed that reanalyzing massive MS data sets in repository with newly developed algorithms may increase the occurrence of the peptides of these proteins. In this study, we downloaded 1000 MS data sets via the ProteomeXchange database. Using pFind software, we identified peptides referring to 1788 PE2-PE5 proteins. Among them, 11 PE2 and 16 PE5 proteins were identified with at least 2 peptides, and 12 of them were identified using 2 peptides in a single data set, following the criteria of the HPP guidelines. We found translation evidence for 16 of the 11 PE2 and 16 PE5 proteins in our RNC-seq data, supporting their existence. The properties of the PE2 and PE5 proteins were similar to those of the PE1 proteins. Our approach demonstrated that mining PE2 and PE5 proteins in massive data repository is still worthy, and multidata set peptide identifications may support the presence of PE2 and PE5 proteins or at least prompt additional studies for validation. Extremely high throughput could be a solution to finding more PE2 and PE5 proteins.

Skeletal Muscle Proteome Modifications following Antibiotic-Induced Microbial Disturbances in Cancer Cachexia

Cancer cachexia is an involuntary loss of body weight, mostly of skeletal muscle. Previous research favors the existence of a microbiota-muscle crosstalk, so the aim of the study was to evaluate the impact of microbiota alterations induced by antibiotics on skeletal muscle proteins expression. Skeletal muscle proteome changes were investigated in control (CT) or C26 cachectic mice (C26) with or without antibiotic treatment (CT-ATB or C26-ATB, n = 8 per group). Muscle protein extracts were divided into a sarcoplasmic and myofibrillar fraction and then underwent label-free liquid chromatography separation, mass spectrometry analysis, Mascot protein identification, and METASCAPE platform data analysis. In C26 mice, the atrogen mafbx expression was 353% higher than CT mice and 42.3% higher than C26-ATB mice. No effect on the muscle protein synthesis was observed. Proteomic analyses revealed a strong effect of antibiotics on skeletal muscle proteome outside of cachexia, with adaptative processes involved in protein folding, growth, energy metabolism, and muscle contraction. In C26-ATB mice, proteome adaptations observed in CT-ATB mice were blunted. Differentially expressed proteins were involved in other processes like glucose metabolism, oxidative stress response, and proteolysis. This study confirms the existence of a microbiota-muscle axis, with a muscle response after antibiotics that varies depending on whether cachexia is present.

Meta-Analysis of Rice Phosphoproteomics Data to Understand Variation in Cell Signaling Across the Rice Pan-Genome

Phosphorylation is the most studied post-translational modification, and has multiple biological functions. In this study, we have reanalyzed publicly available mass spectrometry proteomics data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we identified 15,565 phosphosites on serine, threonine, and tyrosine residues on rice proteins. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation likely caused by different kinase groups. We cross-referenced phosphosites against the rice 3,000 genomes, to identify single amino acid variations (SAAVs) within or proximal to phosphosites that could cause loss of a site in a given rice variety and clustered the data to identify groups of sites with similar patterns across rice family groups. The data has been loaded into UniProt Knowledge-Base─enabling researchers to visualize sites alongside other data on rice proteins, e.g., structural models from AlphaFold2, PeptideAtlas, and the PRIDE database─enabling visualization of source evidence, including scores and supporting mass spectra.

The Chlamydia trachomatis Inc Tri1 interacts with TRAF7 to displace native TRAF7 interacting partners

Chlamydia trachomatis is the leading cause of bacterial sexually transmitted infections in the USA and of preventable blindness worldwide. This obligate intracellular pathogen replicates within a membrane-bound inclusion, but how it acquires nutrients from the host while avoiding detection by the innate immune system is incompletely understood. C. trachomatis accomplishes this in part through the translocation of a unique set of effectors into the inclusion membrane, the inclusion membrane proteins (Incs). Incs are ideally positioned at the host-pathogen interface to reprogram host signaling by redirecting proteins or organelles to the inclusion. Using a combination of co-affinity purification, immunofluorescence confocal imaging, and proteomics, we characterize the interaction between an early-expressed Inc of unknown function, Tri1, and tumor necrosis factor receptor-associated factor 7 (TRAF7). TRAF7 is a multi-domain protein with a RING finger ubiquitin ligase domain and a C-terminal WD40 domain. TRAF7 regulates several innate immune signaling pathways associated with C. trachomatis infection and is mutated in a subset of tumors. We demonstrate that Tri1 and TRAF7 specifically interact during infection and that TRAF7 is recruited to the inclusion. We further show that the predicted coiled-coil domain of Tri1 is necessary to interact with the TRAF7 WD40 domain. Finally, we demonstrate that Tri1 displaces the native TRAF7 binding partners, mitogen-activated protein kinase kinase kinase 2 (MEKK2), and MEKK3. Together, our results suggest that by displacing TRAF7 native binding partners, Tri1 has the capacity to alter TRAF7 signaling during C. trachomatis infection.IMPORTANCEChlamydia trachomatis is the leading cause of bacterial sexually transmitted infections in the USA and preventable blindness worldwide. Although easily treated with antibiotics, the vast majority of infections are asymptomatic and therefore go untreated, leading to infertility and blindness. This obligate intracellular pathogen evades the immune response, which contributes to these outcomes. Here, we characterize the interaction between a C. trachomatis-secreted effector, Tri1, and a host protein involved in innate immune signaling, TRAF7. We identified host proteins that bind to TRAF7 and demonstrated that Tri1 can displace these proteins upon binding to TRAF7. Remarkably, the region of TRAF7 to which these host proteins bind is often mutated in a subset of human tumors. Our work suggests a mechanism by which Tri1 may alter TRAF7 signaling and has implications not only in the pathogenesis of C. trachomatis infections but also in understanding the role of TRAF7 in cancer.

Elucidating hippocampal proteome dynamics in moderate hepatic encephalopathy rats: insights from high-resolution mass spectrometry

Hepatic encephalopathy (HE) is a debilitating neurological disorder associated with liver failure and characterized by impaired brain function. Decade-long studies have led to significant advances in our understanding of HE; however, effective therapeutic management of HE is lacking, and HE continues to be a significant cause of morbidity and mortality in patients, underscoring the need for continued research into its pathophysiology and treatment. Accordingly, the present study provides a comprehensive overview aimed at elucidating the molecular underpinnings of HE and identifying potential therapeutic targets. A moderate-grade HE model was induced in rats using thioacetamide, which simulates the liver damage observed in patients, and its impact on cognitive function, neuronal arborization, and cellular morphology was also evaluated. We employed label-free LC-MS/MS proteomics to quantitatively profile hippocampal proteins to explore the molecular mechanism of HE pathogenesis; 2175 proteins were identified, 47 of which exhibited significant alterations in moderate-grade HE. The expression of several significantly upregulated proteins, such as FAK1, CD9 and Tspan2, was further validated at the transcript and protein levels, confirming the mass spectrometry results. These proteins have not been previously reported in HE. Utilizing Metascape, a tool for gene annotation and analysis, we further studied the biological pathways integral to brain function, including gliogenesis, the role of erythrocytes in maintaining blood-brain barrier integrity, the modulation of chemical synaptic transmission, astrocyte differentiation, the regulation of organ growth, the response to cAMP, myelination, and synaptic function, which were disrupted during HE. The STRING database further elucidated the protein‒protein interaction patterns among the differentially expressed proteins. This study provides novel insights into the molecular mechanisms driving HE and paves the way for identifying novel therapeutic targets for improved disease management.

Interplay between photosynthetic electron flux and organic carbon sinks in sucrose-excreting Synechocystis sp. PCC 6803 revealed by omics approaches

BACKGROUND

Advancing the engineering of photosynthesis-based prokaryotic cell factories is important for sustainable chemical production and requires a deep understanding of the interplay between bioenergetic and metabolic pathways. Rearrangements in photosynthetic electron flow to increase the efficient use of the light energy for carbon fixation must be balanced with a strong carbon sink to avoid photoinhibition. In the cyanobacterium Synechocystis sp. PCC 6803, the flavodiiron protein Flv3 functions as an alternative electron acceptor of photosystem I and represents an interesting engineering target for reorganizing electron flow in attempts to enhance photosynthetic CO2 fixation and increase production yield.

RESULTS

We have shown that inactivation of Flv3 in engineered sucrose-excreting Synechocystis (S02:Δflv3) induces a transition from photoautotrophic sucrose production to mixotrophic growth sustained by sucrose re-uptake and the formation of intracellular carbon sinks such as glycogen and polyhydroxybutyrate. The growth of S02:Δflv3 exceeds that of the sucrose-producing strain (S02) and demonstrates unforeseen proteomic and metabolomic changes over the course of the nine-day cultivation. In the absence of Flv3, a down-regulation of proteins related to photosynthetic light reactions and CO2 assimilation occurred concomitantly with up-regulation of those related to glycolytic pathways, before any differences in sucrose production between S02 and S02:Δflv3 strains were observed. Over time, increased sucrose degradation in S02:Δflv3 led to the upregulation of respiratory pathway components, such as the plastoquinone reductase complexes NDH-11 and NDH-2 and the terminal respiratory oxidases Cyd and Cox, which transfer electrons to O2. While glycolytic metabolism is significantly up-regulated in S02:Δflv3 to provide energy for the cell, the accumulation of intracellular storage compounds and the increase in respiration serve as indirect sinks for photosynthetic electrons.

CONCLUSIONS

Our results show that the presence of strong carbon sink in the engineered sucrose-producing Synechocystis S02 strain, operating under high light, high CO2 and salt stress, cannot compensate for the lack of Flv3 by directly balancing the light transducing source and carbon fixing sink reactions. Instead, the cells immediately sense the imbalance, leading to extensive reprogramming of cellular bioenergetic, metabolic and ion transport pathways that favor mixotrophic growth rather than enhancing photoautotrophic sucrose production.

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.

SpecEncoder: deep metric learning for accurate peptide identification in proteomics

MOTIVATION

Tandem mass spectrometry (MS/MS) is a crucial technology for large-scale proteomic analysis. The protein database search or the spectral library search are commonly used for peptide identification from MS/MS spectra, which, however, may face challenges due to experimental variations between replicated spectra and similar fragmentation patterns among distinct peptides. To address this challenge, we present SpecEncoder, a deep metric learning approach to address these challenges by transforming MS/MS spectra into robust and sensitive embedding vectors in a latent space. The SpecEncoder model can also embed predicted MS/MS spectra of peptides, enabling a hybrid search approach that combines spectral library and protein database searches for peptide identification.

RESULTS

We evaluated SpecEncoder on three large human proteomics datasets, and the results showed a consistent improvement in peptide identification. For spectral library search, SpecEncoder identifies 1%-2% more unique peptides (and PSMs) than SpectraST. For protein database search, it identifies 6%-15% more unique peptides than MSGF+ enhanced by Percolator, Furthermore, SpecEncoder identified 6%-12% additional unique peptides when utilizing a combined library of experimental and predicted spectra. SpecEncoder can also identify more peptides when compared to deep-learning enhanced methods (MSFragger boosted by MSBooster). These results demonstrate SpecEncoder's potential to enhance peptide identification for proteomic data analyses.

AVAILABILITY AND IMPLEMENTATION

The source code and scripts for SpecEncoder and peptide identification are available on GitHub at https://github.com/lkytal/SpecEncoder. Contact: hatang@iu.edu.

MDDOmics: multi-omics resource of major depressive disorder

Major depressive disorder (MDD) is a pressing global health issue. Its pathogenesis remains elusive, but numerous studies have revealed its intricate associations with various biological factors. Consequently, there is an urgent need for a comprehensive multi-omics resource to help researchers in conducting multi-omics data analysis for MDD. To address this issue, we constructed the MDDOmics database (Major Depressive Disorder Omics, (https://www.csuligroup.com/MDDOmics/), which integrates an extensive collection of published multi-omics data related to MDD. The database contains 41 222 entries of MDD research results and several original datasets, including Single Nucleotide Polymorphisms, genes, non-coding RNAs, DNA methylations, metabolites and proteins, and offers various interfaces for searching and visualization. We also provide extensive downstream analyses of the collected MDD data, including differential analysis, enrichment analysis and disease-gene prediction. Moreover, the database also incorporates multi-omics data for bipolar disorder, schizophrenia and anxiety disorder, due to the challenge in differentiating MDD from similar psychiatric disorders. In conclusion, by leveraging the rich content and online interfaces from MDDOmics, researchers can conduct more comprehensive analyses of MDD and its similar disorders from various perspectives, thereby gaining a deeper understanding of potential MDD biomarkers and intricate disease pathogenesis. Database URL: https://www.csuligroup.com/MDDOmics/.

Antiangiogenic Potential of an Olive Oil Extract: Insights from a Proteomic Study

Extra virgin olive oil (EVOO), a staple of the Mediterranean diet, is rich in phenolic compounds recognized for their potent bioactive effects, including anticancer and anti-inflammatory properties. However, its effects on vascular health remain relatively unexplored. In this study, we examined the impact of a "picual" EVOO extract from Jaén, Spain, on endothelial cells. Proteomic analysis revealed the modulation of angiogenesis-related processes. In subsequent in vitro experiments, the EVOO extract inhibited endothelial cell migration, adhesion, invasion, ECM degradation, and tube formation while inducing apoptosis. These results provide robust evidence of the extract's antiangiogenic potential. Our findings highlight the potential of EVOO extracts in mitigating angiogenesis-related pathologies, such as cancer, macular degeneration, and diabetic retinopathy.

Integrated Proteomics Analysis of Baseline Protein Expression in Pig Tissues

The availability of an increasingly large amount of public proteomics data sets presents an opportunity for performing combined analyses to generate comprehensive organism-wide protein expression maps across different organisms and biological conditions. Sus scrofa, a domestic pig, is a model organism relevant for food production and for human biomedical research. Here, we reanalyzed 14 public proteomics data sets from the PRIDE database coming from pig tissues to assess baseline (without any biological perturbation) protein abundance in 14 organs, encompassing a total of 20 healthy tissues from 128 samples. The analysis involved the quantification of protein abundance in 599 mass spectrometry runs. We compared protein expression patterns among different pig organs and examined the distribution of proteins across these organs. Then, we studied how protein abundances were compared across different data sets and studied the tissue specificity of the detected proteins. Of particular interest, we conducted a comparative analysis of protein expression between pig and human tissues, revealing a high degree of correlation in protein expression among orthologs, particularly in brain, kidney, heart, and liver samples. We have integrated the protein expression results into the Expression Atlas resource for easy access and visualization of the protein expression data individually or alongside gene expression data.

Improved Data Acquisition Settings on Q Exactive HF-X and Fusion Lumos Tribrid Orbitrap-Based Mass Spectrometers for Proteomic Analysis of Limited Samples

Deep proteomic profiling of complex biological and medical samples available at low nanogram and subnanogram levels is still challenging. Thorough optimization of settings, parameters, and conditions in nanoflow liquid chromatography-tandem mass spectrometry (MS)-based proteomic profiling is crucial for generating informative data using amount-limited samples. This study demonstrates that by adjusting selected instrument parameters, e.g., ion injection time, automated gain control, and minimally altering the conditions for resuspending or storing the sample in solvents of different compositions, up to 15-fold more thorough proteomic profiling can be achieved compared to conventionally used settings. More specifically, the analysis of 1 ng of the HeLa protein digest standard by Q Exactive HF-X Hybrid Quadrupole-Orbitrap and Orbitrap Fusion Lumos Tribrid mass spectrometers yielded an increase from 1758 to 5477 (3-fold) and 281 to 4276 (15-fold) peptides, respectively, demonstrating that higher protein identification results can be obtained using the optimized methods. While the instruments applied in this study do not belong to the latest generation of mass spectrometers, they are broadly used worldwide, which makes the guidelines for improving performance desirable to a wide range of proteomics practitioners.