Identification Of Proteins Research Articles

Evolution of thaumatin-like proteins in rosaceae and rapid response to cold stimulation coordinated with PmEOBⅡ in the floral scent formation process of Prunus mume

Prunus mume has a long history of cultivation in China as the ornamental plant. It has been observed for a long time that the colder weather the weather appear, the sweeter the flowers produce, coldness stress may contribute to the formation of its floral scents. Here, in previous transcription matrix during scent formation period, we recognized thaumatin-like proteins from the core co-expression members. Thus, we performed the identification of thaumatin-like proteins in the Rosaceae genomes, characterized by conserved cysteine residues and tag sequences to explain the relationship between abiotic stress and floral metabolism. The numbers of TLPs ranged from 22 to 34. Most of the TLP members in Group 9 displayed congregated and expanded. A total of seven tandem duplication events occurred in 27 PmTLPs, which could be the primary driving force behind PmTLP gene expansion. The promoters of the PmTLPs contained various types of cis-elements. Additionally, there existed several miRNAs for certain PmTLPs. As a result, PmTLPs displayed tissue-specific expression trends, and expressions varied across different developmental stages of flowers. For highly activated members, PmTLP19 and 23 increased sharply after 4 h under chilling induction compared with a slow increase by ABA treatment. PmTLPs, PmEOBII, and PmMYB4 owned a positive expression correlation in both responces. Finally, the yeast two-hybrid results also indicated a strong interaction between PmEOBII and PmTLP19. Our results establish the foundation for a comprehensive investigation into the molecular mechanism of PmTLPs involved in the cold-resistant defense response of Prunus mume. Additionally, it will facilitate the identification of genes associated with regulating floral compounds in P. mume.

Contact-dependent growth inhibition (CDI) systems deploy a large family of polymorphic ionophoric toxins for inter-bacterial competition.

Contact-dependent growth inhibition (CDI) is a widespread form of inter-bacterial competition mediated by CdiA effector proteins. CdiA is presented on the inhibitor cell surface and delivers its toxic C-terminal region (CdiA-CT) into neighboring bacteria upon contact. Inhibitor cells also produce CdiI immunity proteins, which neutralize CdiA-CT toxins to prevent auto-inhibition. Here, we describe a diverse group of CDI ionophore toxins that dissipate the transmembrane potential in target bacteria. These CdiA-CT toxins are composed of two distinct domains based on AlphaFold2 modeling. The C-terminal ionophore domains are all predicted to form five-helix bundles capable of spanning the cell membrane. The N-terminal "entry" domains are variable in structure and appear to hijack different integral membrane proteins to promote toxin assembly into the lipid bilayer. The CDI ionophores deployed by E. coli isolates partition into six major groups based on their entry domain structures. Comparative sequence analyses led to the identification of receptor proteins for ionophore toxins from groups 1 & 3 (AcrB), group 2 (SecY) and groups 4 (YciB). Using forward genetic approaches, we identify novel receptors for the group 5 and 6 ionophores. Group 5 exploits homologous putrescine import proteins encoded by puuP and plaP, and group 6 toxins recognize di/tripeptide transporters encoded by paralogous dtpA and dtpB genes. Finally, we find that the ionophore domains exhibit significant intra-group sequence variation, particularly at positions that are predicted to interact with CdiI. Accordingly, the corresponding immunity proteins are also highly polymorphic, typically sharing only ~30% sequence identity with members of the same group. Competition experiments confirm that the immunity proteins are specific for their cognate ionophores and provide no protection against other toxins from the same group. The specificity of this protein interaction network provides a mechanism for self/nonself discrimination between E. coli isolates.

Urinary Proteomics and Systems Biology Link Eight Proteins to the Higher Risk of Hypertension and Related Complications in Blacks Versus Whites.

Blacks are more prone to salt-sensitive hypertension than Whites. This cross-sectional analysis of a multi-ethnic cohort aimed to search for proteins potentially involved in the susceptibility to salt sensitivity, hypertension, and hypertension-related complications. The study included individuals enrolled in African Prospective Study on the Early Detection and Identification of Cardiovascular Disease and Hypertension (African-PREDICT), Flemish Study of the Environment, Genes and Health Outcomes (FLEMENGHO), Prospective Cohort Study in Patients with Type 2 Diabetes Mellitus for Validation of Biomarkers (PROVALID)-Austria, and Urinary Proteomics Combined with Home Blood Pressure Telemonitoring for Health Care Reform Trial (UPRIGHT-HTM). Sequenced urinary peptides detectable in 70% of participants allowed the identification of parental proteins and were compared between Blacks and Whites. Of 513 urinary peptides, 300 had significantly different levels among healthy Black (n=476) and White (n=483) South Africans sharing the same environment. Analyses contrasting 582 Blacks versus 1731 Whites, and Sub-Saharan Blacks versus European Whites replicated the findings. COL4A1, COL4A2, FGA, PROC, MGP, MYOCD, FYXD2, and UMOD were identified as the most likely candidates underlying the racially different susceptibility to salt sensitivity, hypertension, and related complications. Enriched pathways included hemostasis, platelet activity, collagens, biology of the extracellular matrix, and protein digestion and absorption. Our study suggests that MGP and MYOCD being involved in cardiovascular function, FGA and PROC in coagulation, FYXD2 and UMOD in salt homeostasis, and COL4A1 and COL4A2 as major components of the glomerular basement membrane are among the many proteins potentially incriminated in the higher susceptibility of Blacks compared to Whites to salt sensitivity, hypertension, and its complication. Nevertheless, these eight proteins and their associated pathways deserve further exploration in molecular and human studies as potential targets for intervention to reduce the excess risk of hypertension and cardiovascular complications in Blacks versus Whites.

ProtPipe: A Multifunctional Data Analysis Pipeline for Proteomics and Peptidomics.

Mass spectrometry (MS) is a technique widely employed for the identification and characterization of proteins, with personalized medicine, systems biology, and biomedical applications. The application of MS-based proteomics advances our understanding of protein function, cellular signaling, and complex biological systems. MS data analysis is a critical process that includes identifying and quantifying proteins and peptides and then exploring their biological functions in downstream analysis. To address the complexities associated with MS data analysis, we developed ProtPipe to streamline and automate the processing and analysis of high-throughput proteomics and peptidomics datasets with DIA-NN preinstalled. The pipeline facilitates data quality control, sample filtering, and normalization, ensuring robust and reliable downstream analyses. ProtPipe provides downstream analyses, including protein and peptide differential abundance identification, pathway enrichment analysis, protein-protein interaction analysis, and Major histocompatibility complex (MHC) -peptide binding affinity analysis. ProtPipe generates annotated tables and visualizations by performing statistical postprocessing and calculating fold changes between predefined pairwise conditions in an experimental design. It is an open-source, well-documented tool available online at https://github.com/NIH-CARD/ProtPipe, with a user-friendly web interface.

Systematic Optimization of Activity-Based Protein Profiling for Identification of Polysorbate-Degradative Enzymes in Biotherapeutic Drug Substance down to 10 ppb.

The identification and control of high-risk host cell proteins (HCPs) in biotherapeutics development are crucial for ensuring product quality and shelf life. Specifically, HCPs with hydrolase activity can cause the degradation of excipient polysorbates (PS), leading to a decrease in the shelf life of the drug product. In this study, we systematically optimized every step of an activity-based protein profiling (ABPP) workflow to identify trace amounts of active polysorbate-degradative enzymes (PSDEs) in biotherapeutic process intermediates. Evaluation of various parameters during sample preparation pinpointed the optimal pH level and fluorophosphonate (FP)-biotin concentration. Moreover, the combined use of a short liquid chromatography gradient and the fast-scanning parallel accumulation-serial fragmentation (PASEF) methodology increased sample throughput without compromising identification coverage. Tuning the trapped ion mobility spectrometry (TIMS) parameters further enhanced sensitivity. In addition, we evaluated various data acquisition modes, including PASEF combined with data-dependent acquisition (DDA PASEF), data-independent acquisition (diaPASEF), or parallel reaction monitoring (prm-PASEF). By employing the newly optimized ABPP workflow, we successfully identified PSDEs at a concentration as low as 10 ppb in a drug substance sample. Finally, the new workflow enabled us to detect a PSDE that could not be detected with the original workflow during a PS degradation root-cause investigation.

Subcellular Proteomic Mapping of Lysine Lactylation.

Protein lactylation is a novel post-translational modification (PTM) involved in many important physiological processes such as macrophage polarization, immune regulation, and tumor cell growth. However, traditional methodologies for studying lactylation have predominantly relied on peptide enrichment from whole-cell lysates, which tend to favor the detection of high-abundance peptides, thus limiting the identification of low-abundance lactylated peptides. To address this limitation, here, we employed subcellular fractionation to separate proteins and map lactylated peptides from each isolated subcellular fraction using a model cell line. In brief, we identified 1,217 lysine lactylation (Kla) sites on 553 proteins across four subcellular fractions. Subsequent pathway enrichment analysis revealed that Kla proteins participate in distinct pathways depending on the subcellular contexts. In addition, this subcellular fractionation method enabled the discovery of 36 previously unreported Kla proteins and 223 novel Kla sites, many of which are present in low abundance. Notably, several proteins contain multiple newly identified Kla sites, exemplified by the transcriptional regulator ATRX. Furthermore, our results indicate the possibility of PTM crosstalk between Kla and other PTMs such as ubiquitination and sumoylation. In conclusion, subcellular fractionation facilitates the identification of Kla proteins that have been previously uncovered and could be overlooked by affinity enrichment of whole-cell lysates.

Genome-Wide Identification and Stress Responses of Cowpea Thaumatin-like Proteins: A Comprehensive Analysis.

Cowpea (Vigna unguiculata (L.) Walp.) is an important legume cultivated mainly in regions with limited water availability across the African and American continents. Its productivity is significantly affected by environmental stresses. Thaumatin-like proteins (TLPs), which belong to the PR-5 (pathogenesis-related 5) protein family, are known to be responsive to both biotic and abiotic stresses. However, their role remains controversial, with some TLPs associated with plant defense (particularly against fungal infections) and others associated with abiotic stresses response. In this study, we evaluated the structural diversity and gene expression of TLPs in cowpea (VuTLPs) under different stress conditions, including biotic [mechanical injury followed by inoculation with Cowpea Aphid-borne Mosaic Virus (CABMV) or Cowpea Severe Mosaic Virus (CPSMV)] and abiotic (root dehydration). Genomic anchoring of VuTLPs revealed 34 loci encoding these proteins. Neighbor- joining analysis clustered the VuTLPs into three distinct groups. We identified 15 segmental duplication and 6 tandem duplication gene pairs, with the majority of VuTLP genes found to be under purifying selection. Promoter analysis associated VuTLPs with bHLH, Dof-type, and MYB- related transcription factors, supporting their diverse roles. Diversity in VuTLP function was also observed in their expression profiles under the studied stress conditions. Gene expression data showed that most VuTLPs are recruited within the first minutes after biotic stress imposition. For the root dehydration assay, the most transcripts were up-regulated 150 min post-stress. Moreover, the gene expression data suggested that VuTLPs exhibit functional specialization depending on the stress condition, highlighting their diverse roles and biotechnological potential.

Combined Mendelian randomization and quantitative proteomics analysis to study the influence of thyroid dysfunction on acute ischemic stroke

AbstractAcute ischemic stroke (AIS) is characterized by high morbidity and mortality, making it crucial to identify the risk factors that influence its occurrence and prognosis. Although individuals with thyroid dysfunction exhibit altered stroke patterns, evidence from observational studies remains inconsistent. Herein, we investigated the influence of thyroid dysfunction on stroke progression and prognosis. We combined Mendelian randomization (MR) and tandem mass tag (TMT)‐based quantitative proteomics analysis to study the influence of thyroid dysfunction on AIS. Differentially expression proteins (DEPs) were subsequently identified, functional enrichment analysis was performed, and a protein–protein interaction (PPI) network was constructed. Protein alterations were further validated by western blot. MR analysis revealed a causal association between thyroid disorders and ischemic stroke. DEP analysis identified 38 downregulated proteins and five upregulated proteins. Functional enrichment analysis and PPI network construction highlighted the importance of immune response activation and acute phase pathways, along with the suppression of focal adhesion, regulation of the actin cytoskeleton, and platelet activation pathways. Vasodilator‐stimulated phosphoprotein, MYL12B, MYL6, and TPM4 were identified as key DEPs significantly associated with pathological pathways and were verified by western blot. The identification of these key proteins and pathways provides new perspectives for investigating the progression and prognosis of AIS.

Identification of potential antigenic proteins and epitopes for the development of a monkeypox virus vaccine: an in silico approach.

Virus assembly, budding, or surface proteins play important roles such as viral attachment to cells, fusion, and entry into cells. The present study aimed to identify potential antigenic proteins and epitopes that could be used to develop a vaccine or diagnostic assay against the Monkeypox virus (MPXV) which may cause a potential epidemic. To do this, 39 MPXV proteins (including assembly, budding, and surface proteins) were analyzed using an in silico approach. Of these 39 proteins, the F5L virus protein was found to be the best vaccine candidate due to its signal peptide properties, negative GRAVY value, low transmembrane helix content, moderate aliphatic index, large molecular weight, long-estimated half-life, beta wrap motifs, and being stable, soluble, and containing non-allergic features. Moreover, the F5L protein exhibited alpha-helical secondary structures, making it a potential "structural antigen" recognized by antibodies. The other viral protein candidates were A9 and A43, but A9 lacked beta wrap motifs, while A43 had a positive GRAVY value and was insoluble. These two proteins were not as suitable candidates as the F5L protein. The KRVNISLTCL epitope from the F5L protein demonstrated the highest antigen score (2.4684) for MHC-I, while the GRFGYVPYVGYKCI epitope from the A9 protein exhibited the highest antigenicity (1.754) for MHC-II. Both epitopes met the criteria for high antigenicity, non-toxicity, solubility, non-allergenicity, and the presence of cleavage sites. Molecular docking and dynamics (MD) simulations further validated their potential, revealing stable and energetically favorable interactions with MHC molecules. The immunogenicity assessment showed that GRFGYVPYVGYKCI could strongly induce immune responses through both IFN-γ and IL-4 pathways, suggesting its capacity to provoke a balanced Th1 and Th2 response. In contrast, KRVNISLTCL exhibited limited immunostimulatory potential. Overall, these findings lay the groundwork for future vaccine development, indicating that F5L, particularly the GRFGYVPYVGYKCI epitope, may serve as an effective candidate for peptide-based vaccine design against MPXV.

A Systematic Identification of RNA-Binding Proteins (RBPs) Driving Aberrant Splicing in Cancer.

Alternative Splicing (AS) is a post-transcriptional process that allows a single RNA to produce different mRNA variants and, in some cases, multiple proteins. Various processes, many yet to be discovered, regulate AS. This study focuses on regulation by RNA-binding proteins (RBPs), which are not only crucial for splicing regulation but also linked to cancer prognosis and are emerging as therapeutic targets for cancer treatment. CLIP-seq experiments help identify where RBPs bind on nascent transcripts, potentially revealing changes in splicing status that suggest causal relationships. Selecting specific RBPs for CLIP-seq experiments is often driven by a priori hypotheses. We developed an algorithm to detect RBPs likely related to splicing changes between conditions by integrating several CLIP-seq databases and a differential splicing detection algorithm. This work refines a previous study by improving splicing event prediction, testing different enrichment statistics, and performing additional validation experiments. The new method provides more accurate predictions and is included in the Bioconductor package EventPointer 3.14. We tested the algorithm in four experiments involving knockdowns of seven different RBPs. The algorithm accurately assessed the statistical significance of these RBPs using only splicing alterations. Additionally, we applied the algorithm to study sixteen cancer types from The Cancer Genome Atlas (TCGA) and three from TARGET. We identified relationships between RBPs and various cancer types, including alterations in CREBBP and MBNL2 in adenocarcinomas of the lung, liver, prostate, rectum, stomach, and colon. Some of these findings are validated in the literature, while others are novel. The developed algorithm enhances the ability to predict and understand RBP-related splicing changes, offering more accurate predictions and novel insights into cancer-related splicing alterations. This work highlights the potential of RBPs as therapeutic targets and contributes to the broader understanding of their roles in cancer biology.

NcPTP2, a polar tube protein, interacts with spore wall protein in the parasitic microsporidian Nosema ceranae.

Microsporidia is an obligate intracellular eukaryote, which is capable of parasitizing vertebrates and invertebrates. Nosema ceranae, which can infect both Apis mellifera and Apis cerana, poses a serious threat and causes heavy losses to the worldwide apiculture. During infection, polar tube, a highly specialized invasion structure, ejected from the spore to deliver the sporoplasm into host cells to cause infection. Although seven different polar tube proteins (PTP1 ~ 7) have been reported from various microsporidia and showed key functions associated with spore invasion and proliferation, no systematic analysis on identification and characterization of polar tube proteins from N. ceranae was found. The polar tube proteins 2 (NcPTP2) was identified from the total polar tube proteins of N. ceranae by LC_MS/MS and the transcriptional profile was performed by RT-PCR. Sequence characterization analysis revealed that NcPTP2 was rich in lysine and had a signal peptide at the N-terminal. It had 3 potential O-glycosylation sites and 6 potential N-glycosylation sites. 25 phosphorylation sites were found on serine, tyrosine and threonine sites. Sequence alignment analysis revealed that NcPTP2 was homologous and had conserved cysteine residues with PTP2 proteins from other microsporidia. Indirect immunofuorescence analysis (IFA) and Immunoelectron Microscopy analysis (IEM) confirmed that NcPTP2 was localized on the polar tube of the germinated spores. The interaction between NcPTP2 and spore wall protein in N. ceranae indicated its potential function in anchoring and coiling of polar tube in spore. NcPTP2 was the first subcellular localized polar tube protein in N. ceranae and this work could provide an important basis for further analyzing the biological functions of polar tube proteins and uncovering the infection mechanism of N. ceranae to the host cells.

Comparative evaluation of methods for the prediction of protein–ligand binding sites

The accurate identification of protein–ligand binding sites is of critical importance in understanding and modulating protein function. Accordingly, ligand binding site prediction has remained a research focus for over three decades with over 50 methods developed and a change of paradigm from geometry-based to machine learning. In this work, we collate 13 ligand binding site predictors, spanning 30 years, focusing on the latest machine learning-based methods such as VN-EGNN, IF-SitePred, GrASP, PUResNet, and DeepPocket and compare them to the established P2Rank, PRANK and fpocket and earlier methods like PocketFinder, Ligsite and Surfnet. We benchmark the methods against the human subset of our new curated reference dataset, LIGYSIS. LIGYSIS is a comprehensive protein–ligand complex dataset comprising 30,000 proteins with bound ligands which aggregates biologically relevant unique protein–ligand interfaces across biological units of multiple structures from the same protein. LIGYSIS is an improvement for testing methods over earlier datasets like sc-PDB, PDBbind, binding MOAD, COACH420 and HOLO4K which either include 1:1 protein–ligand complexes or consider asymmetric units. Re-scoring of fpocket predictions by PRANK and DeepPocket display the highest recall (60%) whilst IF-SitePred presents the lowest recall (39%). We demonstrate the detrimental effect that redundant prediction of binding sites has on performance as well as the beneficial impact of stronger pocket scoring schemes, with improvements up to 14% in recall (IF-SitePred) and 30% in precision (Surfnet). Finally, we propose top-N+2 recall as the universal benchmark metric for ligand binding site prediction and urge authors to share not only the source code of their methods, but also of their benchmark.Scientific contributionsThis study conducts the largest benchmark of ligand binding site prediction methods to date, comparing 13 original methods and 15 variants using 10 informative metrics. The LIGYSIS dataset is introduced, which aggregates biologically relevant protein–ligand interfaces across multiple structures of the same protein. The study highlights the detrimental effect of redundant binding site prediction and demonstrates significant improvement in recall and precision through stronger scoring schemes. Finally, top-N+2 recall is proposed as a universal benchmark metric for ligand binding site prediction, with a recommendation for open-source sharing of both methods and benchmarks.

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.

Identification and Molecular Analysis of Proteins Associated with Non-spinning Disease in the Silkworm Bombyx mori L Induced by BmNPV and BmDNV

Aims: The present study combines morphological and molecular biology investigations to uncover the underlying causes of the non-spinning syndrome in silkworms. To understand the molecular mechanism and immune mechanism after infection of viral pathogen in silkworm Bombyx mori L. Study Design: Infected silkworm samples were collected from the field and isolated the genomic DNA and total proteins. Analyzed the samples by using genomic tools and proteomic tools. Place and Duration of Study: Central Sericultural Research and Training Institute, Mysuru, Karnataka. 01.03.2023 to 31.07.2023 total 04 months. Methodology: Our findings indicate that infections of BmDNV and BmNPV are associated with abnormal growth of the silk gland, leading to the non-spinning phenotype. To confirm pathogen infection in non-spinning silkworms, we collected genomic DNA and conducted PCR analysis using specific primers for DNV and NPV. Results: Our results showed amplification of both viral infections in the isolated samples. SDS-PAGE analysis revealed differential regulation of several proteins involved in physiological and immunological processes in the hemolymph of non-spinning silkworms. MALDI-TOF/MS was used to identify an up-regulated protein of interest, which was found to be a Lepidopteran low molecular weight lipoprotein. This protein is known to play an important role in insect immune mechanisms. Conclusion: Major disease-causing agents such as BmDNV and BmNPV infections and investigate their impact on protein expression patterns in the hemolymph, shedding light on the factors contributing to non-spinning behavior in silkworms.

Differences in Uniquely Identified Peptides Between ddaPASEF and diaPASEF.

Recent advancements in mass spectrometry-based proteomics have made it possible to conduct comprehensive protein analysis. In particular, the emergence of the data-independent acquisition (DIA) method powered by machine learning has significantly improved protein identification efficiency. However, compared with the conventional data-dependent acquisition (DDA) method, the degree to which peptides are uniquely identified by DIA and DDA has not been thoroughly examined. In this study, we identified over 10,000 proteins using the DDA and DIA methods and analyzed the characteristics of unique peptides identified by each method. Results showed that the number of peptides uniquely identified by DDA and DIA using the same column type was 19% and 32%, respectively, with shorter peptides preferentially detected by the DIA method. In addition, more DIA-specific peptides were identified, especially during the first 10% of elution time, and the overall 1/K0 and m/z shifted toward smaller values than in the DDA method. Furthermore, comparing the phosphorylation and ubiquitination proteome profiles with those of whole-cell lysates by DDA showed that the enrichment of post-translationally modified peptides resulted in wider m/z and 1/K0 ranges. Notably, the ubiquitin peptide-enriched samples displayed lower m/z values than the phospho-proteome. These findings suggest a bias in the types of peptides identified by the acquisition method and the importance of setting appropriate ranges for DIA based on the post-translational modification of peptide characteristics.

Niclosamide attenuates calcification in human heart valvular interstitial cells through inhibition of the AMPK/mTOR signaling pathway

Calcific aortic valve disease (CAVD) is a considerable health burden with a lack of effective therapeutic options. There is an urgent need to develop interventions that inhibit the osteogenic transformation of valvular interstitial cells (VICs) and delay the calcification process. Niclosamide, an FDA-approved anti-helminthic drug, has emerged as a promising candidate that demonstrates a negative regulatory effect on porcine VICs calcification. However, its molecular mechanism in human VICs (hVICs) remains to be investigated. In this study, high-resolution mass spectrometry-based proteomics and phosphoproteomics were employed, and 8373 proteins and 3697 phosphosites were identified in hVICs treated with a pro-calcifying medium and niclosamide. The quantitative proteomic and phosphoproteomic analysis resulted in the identification of calcification markers and osteogenesis-associated proteins. Bioinformatic analysis of the protein–protein interaction network and affected kinase prediction revealed that the AMPK/mTOR/p70S6K signaling cascade was altered upon calcific induction and niclosamide treatment. Further validation indicated that niclosamide inhibited the calcification of hVICs by targeting the mammalian target of the rapamycin (mTOR) signaling pathway. This study provides the first evidence that niclosamide could prevent osteoblastic differentiation in hVICs partially through the inhibition of the AMPK/mTOR/p70S6k signaling pathway, thereby mitigating hVICs calcification. These findings present a foundation for potential therapeutic strategies to impede the progression of CAVD and provide valuable insights into the pharmacological effects of niclosamide on human VICs.

TPGPred: A Mixed-Feature-Driven Approach for Identifying Thermophilic Proteins Based on GradientBoosting.

Thermophilic proteins maintain their stability and functionality under extreme high-temperature conditions, making them of significant importance in both fundamental biological research and biotechnological applications. In this study, we developed a machine learning-based thermophilic protein GradientBoosting prediction model, TPGPred, designed to predict thermophilic proteins by leveraging a large-scale dataset of both thermophilic and non-thermophilic protein sequences. By combining various machine learning algorithms with feature-engineering methods, we systematically evaluated the classification performance of the model, identifying the optimal feature combinations and classification models. Trained on a large public dataset of 5652 samples, TPGPred achieved an Accuracy score greater than 0.95 and an Area Under the Receiver Operating Characteristic Curve (AUROC) score greater than 0.98 on an independent test set of 627 samples. Our findings offer new insights into the identification and classification of thermophilic proteins and provide a solid foundation for their industrial application development.

Optimization of protein identifications through the use of different chromatographic approaches and bioinformatic pipelines.

Selection of proteomic workflows for a given project can be a daunting task. This research provides a guide outlining the impact on protein identification of different steps such as chromatographic separation, data acquisition strategies, and bioinformatic pipelines. The data presented here will help experts and nonexpert proteomic users to increase proteome coverage and peptide identification. HeLa protein digests were analyzed through different C18 chromatographic columns (15 and 50 cm in length), using top 12 data-dependent acquisition (DDA), top 20 DDA, and data-independent acquisition (DIA) with a nanospray source in positive mode in a Thermo Q Exactive instrument. The raw data were analyzed using different search engines, rescoring approaches, and multi-engine searches. The results were analyzed in the context of peptide and protein identifications, precursor properties, and computation requirements to understand the differences between methods. Our results showed that higher column lengths and top N DDA approaches were able to significantly increase protein identifications. The use of multiple search engines yielded limited gains, whereas the use of rescoring methods clearly outperformed other strategies. Finally, DIA approaches, although successful at generating new identifications, had a limited performance influenced by the previous collection of DDA data, which could prohibitively increase instrument time. Nonetheless, the use of library-free methods showed promising results. Our results highlight the impact of different experimental approaches on proteome coverage. Changes in chromatographic columns, data acquisition, or bioinformatic analysis can significantly increase the number of protein identifications (>400%). Thus, this research provides a reference upon which to build a successful proteomic workflow with different considerations at every step.

Infrared Laser Ablation and Capture of Formalin-Fixed Paraffin-Embedded Tissue.

Formalin-fixed paraffin-embedded (FFPE) tissue is a ubiquitous and invaluable resource for biomedical research and clinical applications. However, FFPE tissue proteomics is challenging due to protein cross-linking and chemical modification. Laser ablation sampling allows precise removal of material from tissue sections with high spatial control and reproducibility for offline proteomics by liquid chromatography coupled with tandem mass spectrometry. In this work, we used a pulsed mid-infrared laser for microsampling of rat liver tissue for subsequent identification and quantification of proteins. It was found that more proteins were identified by FFPE tissue laser ablation sampling compared to fresh frozen (FF) tissue laser ablation sampling and that more proteins were identified by laser ablation than by manual dissection of FFPE tissue. In contrast to previous studies, no loss of hydrophilic proteins due to residual cross-linking was observed. The efficient capture of proteins by laser ablation microsampling is attributed to efficient laser breakup of the tissue which facilitates downstream processing of the proteins.

Identification and characterization of a rice expansin-like protein with metal-binding properties.

Heavy metal (HM) contamination poses significant threat to agricultural productivity. This study identified and characterized Os09g29690 (OsELP), a rice expansin-like protein. We demonstrated OsELP localizes to the cell wall and is upregulated under various abiotic stresses. Sequence analysis revealed a potential metal-binding CXXXC motif in its conserved domain. Heterologous expression of OsELP in yeast mutants (Δacr3 and Δycf1) enhanced metal tolerance under arsenate [As(V)], arsenite [As(III)], and cadmium [Cd] stress. Yeast cells expressing OsELP accumulated higher amounts of As and Cd, suggesting a potential metal-binding mechanism. This was confirmed through site-directed mutagenesis on the conserved cysteine and serine residues within OsELP. Mutants lacking cysteine residues (mutCS) reduced tolerance to As(III) and Cd but enhanced tolerance to As(V), indicating a role of cysteine in As(III) and Cd binding. Conversely, mutants lacking serine residues (mutSA) reduced tolerance to As(V), suggesting serine's involvement in As(V) binding. These findings reveal the roles of cysteine and serine residues in mediating HM tolerance and binding, confirming OsELP as a key player in HM detoxification through cell wall localization and chelation. This study provides novel insights into the molecular mechanisms of HM tolerance in plants, with potential applications in developing crops with enhanced resistance to HM toxicity.