Identification Of Proteins Research Articles

Comparative Analysis of Digestion Methods for Bile Proteomics: The Key to Unlocking Biliary Biomarker Potential.

Bile's potential to reflect the health of the biliary system has led to increased attention, with proteomic analysis offering deeper understanding of biliary diseases and potential biomarkers. With the emergence of normothermic machine perfusion (NMP), bile can be easily collected and analyzed. However, the composition of bile can make the application of proteomics challenging. This study systematically evaluated various trypsin digestion methods to optimize proteomics of bile from human NMP livers. Bile was collected from 12 human donor livers that were accepted for transplantation after the NMP viability assessment. We performed tryptic digestion using six different methods: in-gel, in-solution, S-Trap, SMART, EasyPep, and filter-aided sample purification, with or without additional precipitation before digestion. Proteins were analyzed using untargeted proteomics. Methods were assessed for total protein IDs, variation, and protein characteristics to determine the most optimal method. Methods involving precipitation surpassed crude methods in protein identifications (4500 vs 3815) except for in-gel digestion. Filtered data (40%) resulted in 3192 versus 2469 for precipitated and crude methods, respectively. We found minimal differences in mass, cellular components, or hydrophobicity of proteins between methods. Intermethod variability was notably diverse, with in-gel, in-solution, and EasyPep outperforming others. Age-related biological comparisons revealed upregulation of metabolic-related processes in younger donors and immune response and cell cycle-related processes in older donors. Variability between methods emphasizes the importance of cross-validation across multiple analytical approaches to ensure robust analysis. We recommend the in-gel crude method for its simplicity and efficiency, avoiding additional precipitation steps. Sample processing speed, cost, cleanliness, and reproducibility should be considered when a digestion method is selected for bile proteomics.

Comparative genome-wide identification and characterization of SET domain-containing and JmjC domain-containing proteins in piroplasms

BackgroundSET domain-containing histone lysine methyltransferases (HKMTs) and JmjC domain-containing histone demethylases (JHDMs) are essential for maintaining dynamic changes in histone methylation across parasite development and infection. However, information on the HKMTs and JHDMs in human pathogenic piroplasms, such as Babesia duncani and Babesia microti, and in veterinary important pathogens, including Babesia bigemina, Babesia bovis, Theileria annulata and Theileria parva, is limited.ResultsA total of 38 putative KMTs and eight JHDMs were identified using a comparative genomics approach. Phylogenetic analysis revealed that the putative KMTs can be divided into eight subgroups, while the JHDMs belong to the JARID subfamily, except for BdJmjC1 (BdWA1_000016) and TpJmjC1 (Tp Muguga_02g00471) which cluster with JmjC domain only subfamily members. The motifs of SET and JmjC domains are highly conserved among piroplasm species. Interspecies collinearity analysis provided insight into the evolutionary duplication events of some SET domain and JmjC domain gene families. Moreover, relative gene expression analysis by RT‒qPCR demonstrated that the putative KMT and JHDM gene families were differentially expressed in different intraerythrocytic developmental stages of B. duncani, suggesting their role in Apicomplexa parasite development.ConclusionsOur study provides a theoretical foundation and guidance for understanding the basic characteristics of several important piroplasm KMT and JHDM families and their biological roles in parasite differentiation.

Identification of Novel Bromodomain-Containing Protein 4 (BRD4) Binders through 3D Pharmacophore-Based Repositioning Screening Campaign.

A 3D structure-based pharmacophore model built for bromodomain-containing protein 4 (BRD4) is reported here, specifically developed for investigating and identifying the key structural features of the (+)-JQ1 known inhibitor within the BRD4 binding site. Using this pharmacophore model, 273 synthesized and purchased compounds previously considered for other targets but yielding poor results were screened in a drug repositioning campaign. Subsequently, only six compounds showed potential as BRD4 binders and were subjected to further biophysical and biochemical assays. Compounds 2, 5, and 6 showed high affinity for BRD4, with IC50 values of 0.60 ± 0.25 µM, 3.46 ± 1.22 µM, and 4.66 ± 0.52 µM, respectively. Additionally, these compounds were tested against two other bromodomains, BRD3 and BRD9, and two of them showed high selectivity for BRD4. The reported 3D structure-based pharmacophore model proves to be a straightforward and useful tool for selecting novel BRD4 ligands.

Identification of Isoform p53 Protein by ELISA Method of Failed Cases of Chronic Lymphocytic Leukemia Resistant to Conventional Treatment

Identification of Isoform p53 Protein by ELISA Method of Failed Cases of Chronic Lymphocytic Leukemia Resistant to Conventional Treatment

A Chemoenzymatic Method Enables Global Enrichment and Characterization of Protein Arginine Methylation.

Arginine methylation is one of the most important post-translational modifications involved in the regulation of numerous biological processes. To better understand the biological significance of arginine methylation, enrichment methods need to be developed to analyze the methylated proteome at large-scale. Unfortunately, the prevailing enrichment method based on immunoaffinity purification can only enrich a subset of them due to the lack of pan-specific antibodies. Therefore, it is crucial to develop a stable and efficient antibody-free approach for the global analysis of arginine methylation. In this study, we developed a chemoenzymatic method for the simultaneous identification of mono- and dimethylated arginine. Totally, we identified 1006 arginine methylation events in Jurkat T cells, corresponding to 645 dimethylated sites and 361 monomethylated sites. We further applied the developed approach to global identification of the substrate proteins regulated by type I protein arginine methyltransferases (PRMTs) and identified 49 substrate proteins of type I PRMTs, which will facilitate a better understanding of PRMTs-regulated biological processes. Given the robust performance of this method, it would have broad application in methylproteomics analysis.

Identification of proteins involved in intracellular ubiquinone trafficking in Saccharomyces cerevisiae using synthetic ubiquinone probe

Identification of proteins involved in intracellular ubiquinone trafficking in Saccharomyces cerevisiae using synthetic ubiquinone probe

Expression characteristics of TBC1D4 activating protein molecule and identification of key module genes for preventing thyroid cancer progression

Endocrine tumors like thyroid carcinoma are becoming more frequent. No clinically informative predictors were found. Thus, effective gene networks and representative biomarkers can illuminate thyroid cancer prevention molecular mechanisms. TBC1D4 is an activating protein molecule that plays an important role in regulating cell metabolism and signal transduction. The aim of this study was to investigate the expression characteristics of TBC1D4 activating protein molecules and identify key module genes that prevent thyroid cancer progression. GSE65144 data were downloaded from GEO. “limma” in R found DEGs with a false discovery rate < 0.05 and a log2 fold change <1. WGCNA builds gene co-expression networks, screens key modules, and filters hub genes. Overlapping genes become hub genes. Hub genes underwent GO and KEGG pathway enrichment analysis. We used Lasso to extract hub gene expression results' distinctive genes. Key genes. GEPIA database determined expression and survival impact. A total of 3220 DEGs. Thyroid cancer was mostly associated with darkred, darkturquoise, and green modules. Venn screened 639 hub genes. Cytokine-cytokine receptor interaction was the primary KEGG enrichment. Hub genes were 14. Finally, ARHGAP6, TBC1D4, and TC2N were important genes. Through gene screening and functional enrichment analysis, we identified a group of genes related to TBC1D4 activating protein and constructed the corresponding protein interaction network.

Exploring maize proteins: Resistance to storage fungi and postharvest insects

Abstract Maize is among the most essential crops produced worldwide. It goes through multiple stages of processing before becoming edible or consumed. During storage, maize is exposed to the attack of different biological agents, such as fungi and insects, which often result in significant quantitative and qualitative losses. Several physical, chemical, and biological strategies have been developed to combat this problem, and the study and identification of proteins with activity correlated to maize resistance becomes relevant. However, most of these studies are focused on the preharvest stages of the crop. Our review summarizes the latest knowledge of maize proteins associated with fungal and insect resistance during storage and the underlying mechanisms. Furthermore, we provide future perspectives on postharvest proteomics and the challenges of breeding storage-resistant maize.

Photoinduced Electron-Transfer-Mediated Differential Recognition of Proteins on Plasmonic Surfaces.

Photoinduced enhanced Raman spectroscopy (PIERS) has emerged as an efficient technique for enhancing the vibrational modes of analyte molecules adsorbed on a plasmonic nanoparticle-semiconductor hybrid material through chemical enhancement governed by electron transfer from the semiconductor to the plasmonic nanoparticles under an additional ultraviolet (UV) preirradiation step. The increase in chemical enhancement is imperative in analyzing and detecting pharmaceutically important moieties, such as amino acids and proteins, with a low Raman scattering cross section, even in complex biological environments. Herein, we demonstrate that UV preirradiation induced the creation of additional oxygen vacancies by introducing a low concentration (≈1%) of Ni as a dopant in the 2D platelike morphology of the BiOCl semiconductor; i.e., defect states in the semiconductor can induce charge transfer from the semiconductor to the plasmonic nanoparticles. This phenomenon facilitates electron transfer to the adsorbed analyte on the plasmonic surface. Additionally, we have shown the usefulness of this method in protein immobilization on the substrate surface, followed by the identification of a specific protein in the mixture of proteins. Proteins containing cysteine residues capture these electrons to form a surface-bound thiol group via a transient disulfide electron adduct radical. This allows differential binding of the protein molecules to the semiconductor plasmonic hybrid depending on the concentration of surface cysteine residues in proteins. Through PIERS and principal component analysis, we demonstrate the possibility of probing and distinguishing biomolecules based on their surface composition and secondary structure components even in their mixtures, thus paving the way for efficient analysis of complex biological systems.

Differences in Protein Capture by SP3 and SP4 Demonstrate Mechanistic Insights of Proteomics Cleanup Techniques.

The goal of proteomics experiments is to identify proteins to observe changes in cellular processes and diseases. One challenge in proteomics is the removal of contaminants following protein extraction, which can limit protein identifications. Single-pot, solid-phase-enhanced sample preparation (SP3) is a cleanup technique in which proteins are captured on carboxylate-modified particles through a proposed hydrophilic-interaction-liquid-chromatography (HILIC)-like mechanism. Recent results have suggested that proteins are captured in SP3 due to a protein-aggregation mechanism. Solvent precipitation, single-pot, solid-phase-enhanced sample preparation (SP4) is a newer cleanup technique that employs protein aggregation to capture proteins without modified particles. We hypothesize that differences in capture mechanisms of SP3 and SP4 affect which proteins are identified by each cleanup technique. Herein, we assess the proteins identified and enriched using SP3 versus SP4 for MCF7 subcellular fractions and correlate protein capture in each method to protein hydrophobicity. Our results indicate that SP3 captures more hydrophilic proteins through a combination of HILIC-like and protein-aggregation mechanisms, while SP4 captures more hydrophobic proteins through a protein-aggregation mechanism. Ultimately, we demonstrate that protein-capture mechanisms are distinct, and the selection of a cleanup technique that yields high proteome coverage is dependent on protein-sample hydrophobicity. Data has been deposited into MassIVE (MSV000094130) and ProteomeXchange (PXD049965).

Pleomorphic adenoma and carcinoma ex-pleomorphic adenoma tumorigenesis: A proteomic analysis.

To conduct a comprehensive proteomic analysis of normal salivary gland tissue, pleomorphic adenoma (PA), and carcinoma ex-pleomorphic adenoma (CXPA), and validate the proteomic findings using immunohistochemistry. Six normal salivary gland tissues, seven PA and seven CXPA samples underwent laser microdissection followed by liquid chromatography coupled to mass spectrometry. Protein identification and quantification were performed using MaxQuant software. Statistical analysis and functional enrichment were conducted using the Perseus platform and STRING tool, respectively. Immunohistochemistry was used for validation. Comparative proteomic analysis revealed 2680 proteins across the three tissue types, with 799 significantly altered between groups. Translocation protein SEC63 homolog, Annexin A6 and Biglycan were up-regulated in CXPA compared to PA. Decorin was markedly up-regulated in both PA and CXPA compared to normal salivary gland (log2 fold changes of 7.58 and 7.38, respectively). Validation confirmed elevated levels of Biglycan and Decorin in the extracellular matrix of CXPA compared to PA. Proteomic analysis identified differential protein expression patterns associated with malignant transformation of PA into CXPA. Findings indicate a crucial role for extracellular matrix proteins, specifically Biglycan and Decorin, in the tumorigenic progression of PA and CXPA.

Using long columns to quantify over 9200 unique protein groups from brain tissue in a single injection on an Orbitrap Exploris 480 mass spectrometer

The most exciting advancement in LC-MS/MS-based bottom-up proteomics has centered around enhancing mass spectrometers. Among these, the latest and most advanced mass spectrometer for bottom-up proteomics is the Orbitrap Astral that has the highest scan rate to accelerate throughput and the highest sensitivity to handle a very small amount of peptide samples and to achieve deeper proteomics. However, its affordability remains a challenge for most laboratories. While significant strides have been made in improving mass spectrometry, advancing liquid chromatography (LC) to achieve deeper proteomics has not achieved significant successes since the innovation of Multidimensional Protein Identification Technology (MudPIT) in 2001. To achieve deeper proteomics in a less labor-intensive and more reproducible approach while using a more cost-effective mass spectrometer, such as the Orbitrap Exploris 480, we evaluated trap columns as long as 40 cm and analytical column as long as 600 cm besides sample loading amount, gradient time, and analytical column particle size to enable a fractionation-free method for a single injection to obtain deeper proteomics. The length of trap and analytic columns is the key factor. Using a 30 cm trap column and 250 cm analytical column with other optimized LC conditions, we quantified over 9200 unique protein groups from brain tissue in a single injection using a 24-h gradient on an Orbitrap Exploris 480 mass spectrometer.

Review of the Proteomics and Metabolic Properties of Corynebacterium glutamicum.

Corynebacterium glutamicum (C. glutamicum) has become industrially important in producing glutamic acid and lysine since its discovery and has been the subject of proteomics and central carbon metabolism studies. The proteome changes depending on environmental conditions, nutrient availability, and stressors. Post-translational modification (PTMs), such as phosphorylation, methylation, and glycosylation, alter the function and activity of proteins, allowing them to respond quickly to environmental changes. Proteomics techniques, such as mass spectrometry and two-dimensional gel electrophoresis, have enabled the study of proteomes, identification of proteins, and quantification of the expression levels. Understanding proteomes and central carbon metabolism in microorganisms provides insight into their physiology, ecology, and biotechnological applications, such as biofuels, pharmaceuticals, and industrial enzyme production. Several attempts have been made to create efficient production strains to increase productivity in several research fields, such as genomics and proteomics. In addition to amino acids, C. glutamicum is used to produce vitamins, nucleotides, organic acids, and alcohols, expanding its industrial applications. Considerable information has been accumulated, but recent research has focused on proteomes and central carbon metabolism. The development of genetic engineering technologies, such as CRISPR-Cas9, has improved production efficiency by allowing precise manipulation of the metabolic pathways of C. glutamicum. In addition, methods for designing new metabolic pathways and developing customized strains using synthetic biology technology are gradually expanding. This review is expected to enhance the understanding of C. glutamicum and its industrial potential and help researchers identify research topics and design studies.

Funnel graph neural networks with multi-granularity cascaded fusing for protein–protein interaction prediction

The identification of potential protein–protein interactions (PPIs) between humans and viruses is crucial for comprehending viral infection and disease mechanisms at the molecular level. Recently, graph neural networks (GNNs) have emerged as a promising approach to expedite PPI identification. However, GNNs often suffer from over-smoothing when capturing high-order neighbor information. To tackle this issue and effectively capture implicit collaborative information from multi-hop neighbors, we propose FGNN, Funnel Graph Neural Networks with Multi-Granularity Cascaded Fusing, facilitating the distillation of information in a funnel-like manner. Specifically, it enables the mapping of information flow from the full graph to subgraphs and ultimately to nodes. By regarding subgraphs as bridges connecting higher-order neighbors, we ensure the projection of multi-hop neighbors into the same subspace, thereby achieving a comprehensive mapping of the full graph into subgraphs. Moreover, we employ an encoder equipped with a multi-head attention mechanism to effectively map subgraphs onto nodes, facilitating further refinement and compression of information derived from high-order neighbors. FGNN can effectively capture high-order neighbor information whilst relieving over-smoothing. Extensive experiments demonstrate FGNN is superior to the state-of-the-art methods in terms of AUC value. The achieved improvements in the four cardiovascular disease datasets are 7.96 %, 2.3 %, 2.49 %, and 0.82 %, respectively.

Coupled nanopores for single-molecule detection.

Rapid sensing of molecules is increasingly important in many studies and applications, such as DNA sequencing and protein identification. Here, beyond atomically thin 2D nanopores, we conceptualize, simulate and experimentally demonstrate coupled, guiding and reusable bilayer nanopore platforms, enabling advanced ultrafast detection of unmodified molecules. The bottom layer can collimate and decelerate the molecule before it enters the sensing zone, and the top 2D pore (~2 nm) enables position sensing. We varied the number of pores in the bottom layer from one to nine while fixing one 2D pore in the top layer. When the number of pores in the bottom layer is reduced to one, sensing is performed by both layers, and distinct T- and W-shaped translocation signals indicate the precise position of molecules and are sensitive to fragment lengths. This is uniquely enabled by microsecond resolution capabilities and precision nanofabrication. Coupled nanopores represent configurable multifunctional systems with inter- and intralayer structures for improved electromechanical control and prolonged dwell times in a 2D sensing zone.

The Study of Metalloproteome of DNA Viruses: Identification, Functional Annotation, and Diversity Analysis of Viral Metal-Binding Proteins.

Metalloproteins are fundamental to diverse biological processes but still lack extensive investigation in viral contexts. This study reveals the prevalence and functional diversity of metal-binding proteins in DNA viruses. Among a subset of 1432 metalloproteins, zinc and magnesium-binding proteins are notably abundant, indicating their importance in viral biology. Furthermore, significant numbers of proteins binding to iron, manganese, copper, nickel, mercury, and cadmium were also detected. Human-infecting viral proteins displayed a rich landscape of metalloproteins, with MeBiPred (964 proteins) and Pfam (666) yielding the highest numbers. Interestingly, many essential viral proteins exhibited metal-binding capabilities, including polymerases, DNA binding proteins, helicases, dUPTase, thymidine kinase, and various structural and accessory proteins. This study sheds light on the ubiquitous presence of metalloproteins, their functional signatures, subcellular placements, and metal-utilization patterns, providing valuable insights into viral biology. A similar metal utilization pattern was observed in similar functional proteins across the various DNA viruses. Furthermore, these findings provide a foundation for identifying potential drug targets for combating viral infections.

AlphaFold2-based prediction of the co-condensation propensity of proteins

The process of protein phase separation into liquid condensates has been implicated in the formation of membraneless organelles (MLOs), which selectively concentrate biomolecules to perform essential cellular functions. Although the importance of this process in health and disease is increasingly recognized, the experimental identification of proteins forming MLOs remains a complex challenge. In this study, we addressed this problem by harnessing the power of AlphaFold2 to perform computational predictions of the conformational properties of proteins from their amino acid sequences. We thus developed the CoDropleT (co-condensation into droplet transformer) method of predicting the propensity of co-condensation of protein pairs. The method was trained by combining experimental datasets of co-condensing proteins from the CD-CODE database with curated negative datasets of non-co-condensing proteins. To illustrate the performance of the method, we applied it to estimate the propensity of proteins to co-condense into MLOs. Our results suggest that CoDropleT could facilitate functional and therapeutic studies on protein condensation by predicting the composition of protein condensates.

The new pattern for dual NOTCH pathway involving nuclear transcription and mitochondrial regulation supports therapeutic mechanism of 4-butyl benzophenone derivatives against SIRS

The systemic inflammatory response syndrome (SIRS) represents a self-amplifying cascade of inflammatory reactions and pathophysiological states triggered by infectious or non-infectious factors. The identification of disease targets and differential proteins in the liver (the unique and important immune organ) of SIRS mice treated with the lead compound D1 was conducted using the Genecards database and proteomic analysis, respectively. Subsequently, NOTCH1 was identified as the potential hub target via an intersection analysis between the aforementioned differentially expressed proteins and disease targets. Based on our previous research on the structure-activity relationship, we designed and synthesized a series of SIRS-related derivatives, wherein butyl, halogen, and ester groups were incorporated into benzophenone, aiming at exploring the anti-inflammatory protective action from the perspective of macrophage polarization. Notably, these derivatives exhibited a direct binding capability to the O-glucosylation site (SER496) or its vicinities (such as SER492, VAL485) of NOTCH1 using docking, SPR, DARTS, and CETSA techniques. Mechanistically, derivative D6 exerted anti-inflammatory effects via the dual NOTCH pathway. Firstly, it could inhibit NOTCH1 nuclear transcriptional activity, attenuate the interaction between NICD and RBPJK, concurrently suppress NF-κB and NLRP3 inflammasome (NLRP3, ASC, and cleaved CASP1) activation, and promote NICD (NOTCH1 active fragments) ubiquitination metabolism (the nuclear transcriptional pathway). Secondly, it might possess the ability to increase PGC1α level, subsequently, enhance ATP and MMP levels, mitigate ROS production, increase mitochondrial numbers, and ameliorate mitochondrial inflammatory damage (the mitochondrial pathway). Importantly, the activator Jagged1 could effectively reverse the aforementioned effects, while the inhibitor DAPT exhibited a synergistic effect, suggesting that the nuclear transcriptional regulation and mitochondrial regulation were both in a NOTCH1-dependent manner. Subsequently, it effectively alleviated the inflammatory response and preserved organ function as evidenced by up-regulating M2-type macrophage-related anti-inflammatory cytokines (IL10, TGFβ, CD206, and ARG1) and down-regulating M1-type macrophage-related pro-inflammatory cytokines (NO, IL6, IL18, iNOS, TNFα, CD86, and IL1β). In a word, derivative D6 modulated macrophage polarization and effectively mitigated SIRS by targeting inhibition of the dual NOTCH pathway.

In silico-driven identification and experimental confirmation of antifungal proteins (AFPs) against Candidaalbicans

Mycoses infect millions of people annually across the world. The most common mycosis agent, Candida albicans is responsible for a great deal of illness and death. C. albicans infection is becoming more widespread and the current antifungals polyenes, triazoles, and echinocandins are less efficient against it. Investigating antifungal peptides (AFPs) as therapeutic is gaining momentum. Therefore, we used MALDI-TOF/MS analysis to identify AFPs and protein-protein docking to analyze their interactions with the C. albicans target protein. Some microorganisms with strong antifungal action against C. albicans were selected for the isolation of AFPs. Using MALDI-TOF/MS, we identified 3 AFPs Chitin binding protein (ACW83017.1; Bacillus licheniformis), the bifunctional protein GlmU (BBQ13478.1; Stenotrophomonas maltophilia), and zinc metalloproteinase aureolysin (BBA25172.1; Staphylococcus aureus). These AFPs showed robust interactions with C. albicans target protein Sap5. We deciphered some important residues in identified APFs and highlighted interaction with Sap5 through hydrogen bonds, protein-protein interactions, and salt bridges using protein-protein docking and MD simulations. The three discovered AFPs-Sap5 complexes exhibit different levels of stability, as seen by the RMSD analysis and interaction patterns. Among protein-protein interactions, the remarkable stability of the BBQ25172.1-2QZX complex highlights the role of salt bridges and hydrogen bonds. Identified AFPs could be further studied for developing successful antifungal candidates and peptide-based new antifungal therapeutic strategies as fresh insights into addressing antifungal resistance also.

Alterations of the skeletal muscle nuclear proteome after acute exercise reveals a post-transcriptional influence.

Exercise plays a crucial role in promoting muscle health, but our understanding of nuclear proteins orchestrating exercise responses is limited. Isolation of skeletal muscle nuclei coupled with mass spectrometry enhanced the identification of nuclear proteins. This approach was used to investigate the effects of acute exercise, revealing changes in the muscle nuclear proteome 1-hour post-exercise, including proteins linked to post-transcriptional processing and splicing. Our findings offer insights into the exercise-induced changes within muscle nuclear proteins.