Proteome Database Research Articles

OrgXenomics: an integrated proteomic knowledge base for patient-derived organoid and xenograft.

Patient-derived models (PDMs, particularly organoids and xenografts) are irreplaceable tools for precision medicine, from target development to lead identification, then to preclinical evaluation, and finally to clinical decision-making. So far, PDM-based proteomics has emerged to be one of the cutting-edge directions and massive data have been accumulated. However, such PDM-based proteomic data have not been provided by any of the available databases, and proteomics profiles of all proteins in proteomic study are also completely absent from existing databases. Herein, an integrated database named 'OrgXenomics' was thus developed to provide the proteomic data for PDMs, which was unique in (a) explicitly describing the establishment detail for a wide array of models, (b) systematically providing the proteomic profiles (expression/function/interaction) for all proteins in studied proteomic analysis and (c) comprehensively giving the raw data for diverse organoid/xenograft-based proteomic studies of various diseases. Our OrgXenomics was expected to server as one good complement to existing proteomic databases, and had great implication for the practice of precision medicine, which could be accessed at: https://idrblab.org/orgxenomics/.

Decellularized extracellular matrix derived from dental pulp stem cells promotes gingival fibroblast adhesion and migration

BackgroundDecellularized extracellular matrix (dECM) has been proposed as a useful source of biomimetic materials for regenerative medicine due to its biological properties that regulate cell behaviors. The present study aimed to investigate the influence of decellularized ECM derived from dental pulp stem cells (DPSCs) on gingival fibroblast (GF) cell behaviors. Cells were isolated from dental pulp and gingival tissues. ECM was derived from culturing dental pulp stem cells in growth medium supplemented with ascorbic acid. A bioinformatic database of the extracellular matrix was constructed using Metascape. GFs were reseeded onto dECM, and their adhesion, spreading, and organization were subsequently observed. The migration ability of the cells was determined using a scratch assay. Protein expression was evaluated using immunofluorescence staining.ResultsType 1 collagen and fibronectin were detected on the ECM and dECM derived from DPSCs. Negative phalloidin and nuclei were noted in the dECM. The proteomic database revealed enrichment of several proteins involved in ECM organization, ECM–receptor interaction, and focal adhesion. Compared with those on the controls, the GFs on the dECM exhibited more organized stress fibers. Furthermore, cultured GFs on dECM exhibited significantly enhanced migration and proliferation abilities. Interestingly, GFs seeded on dECM showed upregulation of FN1, ITGB3, and CTNNB1 mRNA levels.ConclusionsECM derived from DSPCs generates a crucial microenvironment for regulating GF adhesion, migration and proliferation. Therefore, decellularized ECM from DPSCs could serve as a matrix for oral tissue repair.

Combining Transcriptomics and Proteomics to Screen Candidate Genes Related to Bovine Birth Weight.

We established transcriptome and proteome databases for low-birth-weight (LB) and high-birth-weight (HB) calf placentae, identifying key genes and proteins associated with birth weight through bioinformatics analyses that included functional enrichment and protein-protein interactions (PPIs). Both mRNA and protein levels were validated. A total of 1494 differentially expressed genes (DEGs) and 294 differentially expressed proteins (DEPs) were identified when comparing the LB group to the HB group. Furthermore, we identified 53 genes and proteins exhibiting significant co-expression across both transcriptomic and proteomic datasets; among these, 40 were co-upregulated, 8 co-downregulated, while 5 displayed upregulation at the protein level despite downregulation at the mRNA level. Functional enrichment analyses (GO and KEGG) and protein-protein interaction (PPI) analysis indicate that, at the transcriptional level, the primary factor contributing to differences in calf birth weight is that the placenta of the high-birth-weight (HB) group provides more nutrients to the fetus, characterized by enhanced nutrient transport (SLC2A1 and SLC2A11), energy metabolism (ACSL1, MICALL2, PAG2, COL14A1, and ELOVL5), and lipid synthesis (ELOVL5 and ELOVL7). In contrast, the placenta of the low-birth-weight (LB) group prioritizes cell proliferation (PAK1 and ITGA3) and angiogenesis. At the protein level, while the placentae from the HB group exhibit efficient energy production and lipid synthesis, they also demonstrate reduced immunity to various diseases such as systemic lupus erythematosus and bacterial dysentery. Conversely, the LB group placentae excel in regulating critical biological processes, including cell migration, proliferation, differentiation, apoptosis, and signal transduction; they also display higher disease immunity markers (COL6A1, TNC CD36, CD81, Igh-1a, and IGHG) compared to those of the HB group placentae. Co-expression analysis further suggests that increases in calf birth weight can be attributed to both high-efficiency energy production and lipid synthesis within the HB group placentae (ELOVL5, ELOVL7, and ACSL1), alongside cholesterol biosynthesis and metabolic pathways involving CYP11A1 and CYP17A1. We propose that ELOVL5, ELOVL7, ACSL1, CYP11A1, and CYP17A1 serve as potential protein biomarkers for regulating calf birth weight through the modulation of the fatty acid metabolism, lipid synthesis, and cholesterol levels.

Protein phosphatase PP2Cα S-glutathionylation regulates cell migration

Redox signaling is a fundamental mechanism that controls all major biological processes partly via protein cysteine oxidations, including S-glutathionylation. Despite over 2,000 cysteines identified to form S-glutathionylation in databases, the identification of redox cysteines functionally linked to a biological process of interest remains challenging. Here, we demonstrate a strategy combining glutathionylation proteomic database, bioinformatics, and biological screening, which resulted in the identification of S-glutathionylated proteins, including PP2Cα, as redox players of cell migration. We showed that PP2Cα, a prototypical magnesium-dependent serine/threonine phosphatase, is susceptible to S-glutathionylation selectively at non-conserved C314. PP2Cα glutathionylation causes increased migration and invasion of breast cancer cell lines in oxidative stress or upon hydrogen peroxide production. Mechanistically, PP2Cα glutathionylation modulates its protein-protein interactions, activating c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) pathways to elevate migration and invasion. In addition, PP2Cα glutathionylation occurs in response to epidermal-growth factor, supporting a serine/threonine phosphatase PP2Cα as a new redox player in growth factor signal transduction.

Multi-epitope Vaccine Design against Grouper Iridovirus (GIV) Using Immuno-bioinformatics Approach

Grouper Iridovirus (GIV) infection induced cell death in grouper spleen cells and caused serious systemic diseases with more than 90% mortality. Therefore, effective strategies are critically needed to prevent economic losses and maintain the sustainability of grouper aquaculture. Using immuno-bioinformatics, this study aimed to create a multi-epitope vaccine (MEV) that would be effective against GIV. The GIV major capsid protein sequences were retrieved from the NCBI proteome database. Out of 284 epitopes, 17 CTL, 12 HTL, and 10 B-cell epitopes were predicted to be antigenic, non-allergenic, and non-toxic. 10 highly antigenic and overlapping epitopes were shortlisted. To generate full-length epitope vaccine candidates, the selected antigenic epitopes were fused with linkers and adjuvants. Four sets of different linker combinations (no linker, GGS, EAAK, GGGS, GPGPG, KK, and AAY) were tested and compared for their antigenicity, allergenicity, and toxicity using several servers. Molecular dynamics simulations with GROMACS were used on the modelled 3D structures to examine their stability. The results of vaccine candidate sequences screening and MD simulation predicted that the structure with GGS linker is relatively stable with a high antigenic index, non-allergenic, and non-toxic. The designed MEV in the present study could be a potential candidate for further vaccine production process against GIV.

Data mining antibody sequences for database searching in bottom-up proteomics

Mass spectrometry-based proteomics facilitates the identification and quantification of thousands of proteins but encounters challenges in measuring human antibodies due to their vast diversity. Bottom-up proteomics methods primarily rely on database searches, comparing experimental peptide values to theoretical database sequences. While the human body can produce millions of distinct antibodies, current databases, such as UniProtKB/Swiss-Prot, contain only 1095 sequences (as of January 2024), potentially hindering antibody identification via mass spectrometry. Therefore, expanding the database is crucial for discovering new antibodies. Recent genomic studies have amassed millions of human antibody sequences in the Observed Antibody Space (OAS) database, yet this data remains underutilized. Leveraging this vast collection, we conduct efficient database searches in publicly available proteomics data, focusing on SARS-CoV-2. In our study, thirty million heavy antibody sequences from 146 SARS-CoV-2 patients in the OAS database were digested in silico to obtain 18 million unique peptides. These peptides form the basis for new bottom-up proteomics databases. We used those databases for searching new antibody peptides in publicly available SARS-CoV-2 human plasma samples in the Proteomics Identification Database (PRIDE). This approach avoids false positives in antibody peptide identification as confirmed by searching against negative controls (brain samples) and employing different database sizes. We show that new antibody peptides were found in previous plasma samples and expect that the newly discovered antibody peptides can be further employed to develop therapeutic antibodies. The method will be broadly applicable to find characteristic antibodies for other diseases.

Multiple urinary peptides are associated with hypertension: a link to molecular pathophysiology.

Hypertension is a common condition worldwide; however, its underlying mechanisms remain largely unknown. This study aimed to identify urinary peptides associated with hypertension to further explore the relevant molecular pathophysiology. Peptidome data from 2876 individuals without end-organ damage were retrieved from the Human Urinary Proteome Database, belonging to general population (discovery) or type 2 diabetic (validation) cohorts. Participants were divided based on systolic blood pressure (SBP) and diastolic BP (DBP) into hypertensive (SBP ≥140 mmHg and/or DBP ≥90 mmHg) and normotensive (SBP <120 mmHg and DBP <80 mmHg, without antihypertensive treatment) groups. Differences in peptide abundance between the two groups were confirmed using an external cohort ( n = 420) of participants without end-organ damage, matched for age, BMI, eGFR, sex, and the presence of diabetes. Furthermore, the association of the peptides with BP as a continuous variable was investigated. The findings were compared with peptide biomarkers of chronic diseases and bioinformatic analyses were conducted to highlight the underlying molecular mechanisms. Between hypertensive and normotensive individuals, 96 (mostly COL1A1 and COL3A1) peptides were found to be significantly different in both the discovery (adjusted) and validation (nominal significance) cohorts, with consistent regulation. Of these, 83 were consistently regulated in the matched cohort. A weak, yet significant, association between their abundance and standardized BP was also observed. Hypertension is associated with an altered urinary peptide profile with evident differential regulation of collagen-derived peptides. Peptides related to vascular calcification and sodium regulation were also affected. Whether these modifications reflect the pathophysiology of hypertension and/or early subclinical organ damage requires further investigation.

A New Beginning to the Existing Medicines; Repurposing FDA-Approved Drugs for the Neglected Re-Emerging Disease Leptospirosis.

Leptospirosis is one of the re-emerging zoonotic diseases, especially in tropical regions. Many antibiotics are used to treat leptospirosis, but there are no scientific evidence-based guidelines or systematic clinical trials for using these drugs. A bioinformatics approach was made to shortlist some Food and Drug Administration (FDA) of the United States of America-approved and currently used drugs for leptospirosis. The existing drugs from the Drug Bank database, which are currently not used for leptospirosis, were selected to identify their target proteins and binding sites using bioinformatics methods. Orthologues of these target proteins were selected from the proteome database of Leptospira. The similar sites and their interactions with the drugs were validated and recommended for use in leptospirosis. Further, the sensitivity of recommended drugs was also validated in vitro. The sequences and structures of these proteins were compared under strictly controlled parameters and shortlisted Gatifloxacin, Imipenem, Latamoxef, Doripenem, Tigecycline, and Lactams as repurposable drugs for leptospirosis. An in vitro validation of the drugs showed significant antileptospiral activity in 12 serovars with low IC50 concentrations and also showed that the IC50 values varied across Leptospira serovars. Further, suitable proteins under the concept of "One Target, Many Drugs" identified DNA gyrase subunit A (Q72WD1), 30S ribosomal protein S9 (Q72U99), and 30S ribosomal protein S12 (Q72UA6), and these proteins were found across the pathogenic, saprophytic, and intermediate species of Leptospira. We describe a method to find repurposable drugs from the approved list that are not currently used to treat leptospirosis and validate them to be taken forward for systematic clinical trials specific to leptospirosis for recommendations in clinical use.

Amplifiable protein identification via residue-resolved barcoding and composition code counting.

Ultrasensitive protein identification is of paramount importance in basic research and clinical diagnostics but remains extremely challenging. A key bottleneck in preventing single-molecule protein sequencing is that, unlike the revolutionary nucleic acid sequencing methods that rely on the polymerase chain reaction (PCR) to amplify DNA and RNA molecules, protein molecules cannot be directly amplified. Decoding the proteins via amplification of certain fingerprints rather than the intact protein sequence thus represents an appealing alternative choice to address this formidable challenge. Herein, we report a proof-of-concept method that relies on residue-resolved DNA barcoding and composition code counting for amplifiable protein fingerprinting (AmproCode). In AmproCode, selective types of residues on peptides or proteins are chemically labeled with a DNA barcode, which can be amplified and quantified via quantitative PCR. The operation generates a relative ratio as the residue-resolved 'composition code' for each target protein that can be utilized as the fingerprint to determine its identity from the proteome database. We developed a database searching algorithm and applied it to assess the coverage of the whole proteome and secretome via computational simulations, proving the theoretical feasibility of AmproCode. We then designed the residue-specific DNA barcoding and amplification workflow, and identified different synthetic model peptides found in the secretome at as low as the fmol/L level for demonstration. These results build the foundation for an unprecedented amplifiable protein fingerprinting method. We believe that, in the future, AmproCode could ultimately realize single-molecule amplifiable identification of trace complex samples without further purification, and it may open a new avenue in the development of next-generation protein sequencing techniques.

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessment of their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs, protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, and urine diagnostic and prognostic protein biomarker panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing multiple reaction monitoring (MRM) assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SignificanceMass spectrometry-based proteomics platforms have accumulated substantial data on proteins differentially regulated in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessment of GCs.We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation.Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of MRM assays in a SCIEX QTRAP instrument.Aimed to caterproteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data.Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

Molecular insight into the potential functional role of pseudoenzyme GFOD1 via interaction with NKIRAS2.

The glucose-fructose oxidoreductase/inositol dehydrogenase/rhizopine catabolism protein (Gfo/Idh/MocA) family includes a variety of oxidoreductases with a wide range of substrates that utilize NAD or NADP as redox cofactor. Human contains two members of this family, namely glucose-fructose oxidoreductase domain-containing protein 1 and 2 (GFOD1 and GFOD2). While GFOD1 exhibits low tissue specificity, it is notably expressed in the brain, potentially linked to psychiatric disorders and severe diseases. Nevertheless, the specific function, cofactor preference, and enzymatic activity of GFOD1 remain largely unknown. In this work, we find that GFOD1 does not bind to either NAD or NADP. Crystal structure analysis unveils that GFOD1 exists as a typical homodimer resembling other family members, but lacks essential residues required for cofactor binding, suggesting that it may function as a pseudoenzyme. Exploration of GFOD1-interacting partners in proteomic database identifies NF-κB inhibitor-interacting Ras-like 2 (NKIRAS2) as one potential candidate. Co-immunoprecipitation (co-IP) analysis indicates that GFOD1 interacts with both GTP- and GDP-bound forms of NKIRAS2. The predicted structural model of the GFOD1-NKIRAS2 complex is validated in cells using point mutants and shows that GFOD1 selectively recognizes the interswitch region of NKIRAS2. These findings reveal the distinct structural properties of GFOD1 and shed light on its potential functional role in cellular processes.

PCAS: An Integrated Tool for Multi-Dimensional Cancer Research Utilizing Clinical Proteomic Tumor Analysis Consortium Data.

Proteomics offers a robust method for quantifying proteins and elucidating their roles in cellular functions, surpassing the insights provided by transcriptomics. The Clinical Proteomic Tumor Analysis Consortium database, enriched with comprehensive cancer proteomics data including phosphorylation and ubiquitination profiles, alongside transcriptomics data from the Genomic Data Commons, allow for integrative molecular studies of cancer. The ProteoCancer Analysis Suite (PCAS), our newly developed R package and Shinyapp, leverages these resources to facilitate in-depth analyses of proteomics, phosphoproteomics, and transcriptomics, enhancing our understanding of the tumor microenvironment through features like immune infiltration and drug sensitivity analysis. This tool aids in identifying critical signaling pathways and therapeutic targets, particularly through its detailed phosphoproteomic analysis. To demonstrate the functionality of the PCAS, we conducted an analysis of GAPDH across multiple cancer types, revealing a significant upregulation of protein levels, which is consistent with its important biological and clinical significance in tumors, as indicated in our prior research. Further experiments were used to validate the findings performed using the tool. In conclusion, the PCAS is a powerful and valuable tool for conducting comprehensive proteomic analyses, significantly enhancing our ability to uncover oncogenic mechanisms and identify potential therapeutic targets in cancer research.

Fibulin-2 is an extracellular matrix inhibitor of oligodendrocytes relevant to multiple sclerosis.

Impairment of oligodendrocytes and myelin contributes to neurological disorders including multiple sclerosis (MS), stroke, and Alzheimer's disease. Regeneration of myelin (remyelination) decreases the vulnerability of demyelinated axons, but this repair process commonly fails with disease progression. A contributor to inefficient remyelination is the altered extracellular matrix (ECM) in lesions, which remains to be better defined. We have identified fibulin-2 (FBLN2) as a highly upregulated ECM component in lesions of MS and stroke and in proteome databases of Alzheimer's disease and traumatic brain injury. Focusing on MS, the inhibitory role of FBLN2 was suggested in the experimental autoimmune encephalomyelitis (EAE) model, in which genetic FBLN2 deficiency improved behavioral recovery by promoting the maturation of oligodendrocytes and enhancing remyelination. Mechanistically, when oligodendrocyte progenitors were cultured in differentiation medium, FBLN2 impeded their maturation into oligodendrocytes by engaging the Notch pathway, leading to cell death. Adeno-associated virus deletion of FBLN2 in astrocytes improved oligodendrocyte numbers and functional recovery in EAE and generated new myelin profiles after lysolecithin-induced demyelination. Collectively, our findings implicate FBLN2 as a hitherto unrecognized injury-elevated ECM, and a therapeutic target, that impairs oligodendrocyte maturation and myelin repair.

Abstract PO4-06-08: ZP4 AS A NOVEL TARGET FOR CAR T CELL THERAPY IN TRIPLE NEGATIVE BREAST CANCER

Abstract Triple negative breast cancer (TNBC) has the worst prognosis of BC subtypes, largely due to lack of approved targeted therapies. Chimeric antigen receptor (CAR) T cells have demonstrated great success in certain hematological malignancies; however, in the treatment of solid cancers, CAR T cells are faced with a variety of obstacles that limit their efficacy, including on-target/off-tumor toxicity. To minimize these toxicities, the ideal CAR T cell target must be overexpressed by the tumor and absent from vital organs. Cancer/germline (CG) antigens satisfy this need, as their expression is restricted to male or female germ cells. Using a bioinformatic pipeline to identify novel CG antigens expressed in TNBC and other solid cancers, we have identified zona pellucida glycoprotein 4 (ZP4) as a candidate CG antigen target for CAR T cell therapy. This protein is a component of the human zona pellucida matrix, an extracellular structure that surrounds the oocyte and functions in folliculogenesis, species-specific fertilization, and early development. We have identified ZP4 expression in approximately 10% of TNBC cases from available RNAseq and proteomic databases and have confirmed ZP4 expression in several TNBC PDX models. The overall purpose of this study is to redirect T cells against ZP4 by engineering and validating a second generation ZP4-specific CAR. We have generated a library of monoclonal antibody (mAb) candidates against the extracellular portion of human ZP4. Antibody clones were screened, and their specificity validated via ELISA and flow cytometry, and the three strongest binders (z108, z128, and z164) were selected for further investigation. By IHC, we confirmed that the ZP4 mAb clones stained the area surrounding normal oocytes and did not show binding to any of the 23 normal tissues screened. The variable regions of the antibody heavy and light chains were sequenced using 5’RACE and used to assemble second generation CAR constructs composed of the variable heavy and light chain fragments separated by a linker, a CH2/CH3 hinge domain, a CD28 transmembrane domain, a CD28 co-stimulatory domain, and the CD3z signaling domain. Activated T cells transduced with retroviral supernatant express the ZP4 CAR constructs at high levels. While all ZP4 CAR T cells demonstrate antigen-specific cytotoxic killing of ZP4+ target tumor cells in short-term in vitro assays, z128 ZP4 CAR T cells demonstrate superior persistence and efficacy in long-term repeat tumor challenge in vitro assays and orthotopic in vivo mouse models. In summary, ZP4 is a promising target for TNBC and we have successfully engineered ZP4 specific CAR T cells. ZP4 CAR T cells effectively target and kill ZP4+ cells in in vitro cytotoxicity assays but perform differently in repeat tumor challenge assays and in vivo. Future studies will elucidate the precise differences between our three candidate CAR constructs and further test the effector function, trafficking, proliferation, and persistence of z128 ZP4 CAR T cells in vivo using ZP4+ PDX models. This work has exciting potential to bring a novel CAR T cell therapy to patients with TNBC, without concerns for on-target off-tumor toxicity. Citation Format: Lauren Somes, Jonathan Lei, Paul Shafer, Xinpei Yi, Diego Chamorro, Emily Madaras, Michael Lewis, Bing Zhang, Valentina Hoyos. ZP4 AS A NOVEL TARGET FOR CAR T CELL THERAPY IN TRIPLE NEGATIVE BREAST CANCER [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-06-08.

MiRNAs Influence m6A RNA Methylation through FTO and IGF2BP2 in Pressure Overload-Induced Heart Failure.

N6-adenosine methylation (m6A) is a prevalent RNA modification associated with heart failure, alongside aberrant miRNA expression. Despite indications of miRNAs regulating m6A modification, their specific influence on m6A in heart failure remains unclear. The initial analysis utilized transcriptome and methylation sequencing data from GSE131296 in mice to identify key m6A methylation enzymes in heart failure and construct an associated network. Integration of miRNA sequencing data from GSE231700 revealed miRNAs influencing m6A methylation enzymes, contributing to the formation of a comprehensive network. Furthermore, differential miRNA levels in human serum were assessed via qPCR, and the expression of m6A methyltransferases in the heart was confirmed using proteomic databases. In pressure overload-induced heart failure mice, 217 mRNAs showed differential expression, with FTO and IGF2BP2 identified as m6A methylation enzymes. Subsequent methylation sequencing revealed 884 highly-methylated and 178 lowly-methylated peaks, establishing a network linking Fto and Igf2bp2 with these peaks. Additionally, miRNA sequencing identified 156 differentially expressed miRNAs, including let-7b-5p and miR-23b-3p, predicted as m6Aregulating miRNAs, both elevated in heart failure patients. miR-23b-3p and let-7b-5p are identified as potential regulators of RNA methylation in heart failure, acting via FTO and IGF2BP2, offering new insights into the role of miRNA-mediated RNA methylation and its potential therapeutic avenues for heart failure.

A review on available proteomic databases, annotation techniques and data projects important in male reproductive physiology research

A review on available proteomic databases, annotation techniques and data projects important in male reproductive physiology research

Proteomic Insights into Seminal Plasma and Spermatozoa Proteins of Small-Spotted Catsharks, Scyliorhinus canicula: Implications for Reproductive Conservation in Aquariums.

In the ex situ conservation of chondrichthyan species, successful reproduction in aquaria is essential. However, these species often exhibit reduced reproductive success under human care. A key aspect is that conventional sperm analyses do not provide insights into the functional competence of sperm. However, proteomics analysis enables a better understanding of male physiology, gaining relevance as a powerful tool for discovering protein biomarkers related to fertility. The present work aims to build the first proteome database for shark semen and to investigate the proteomic profiles of seminal plasma and spermatozoa from small-spotted catsharks (Scyliorhinus canicula) related to the underlying adaptations to both natural and aquarium environments, thereby identifying the reproductive impact in aquarium specimens. A total of 305 seminal plasma and 535 spermatozoa proteins were identified. Among these, 89 proteins (29.2% of the seminal plasma set) were common to both spermatozoa and seminal plasma. In the seminal plasma, only adenosylhomocysteinase protein showed differential abundance (DAP) between wild and aquarium animals. With respect to the spermatozoa proteins, a total of 107 DAPs were found between groups. Gene Ontology enrichment analysis highlighted the primary functional roles of these DAPs involved in oxidoreductase activity. Additionally, KEGG analysis indicated that these DAPs were primarily associated with metabolic pathways and carbon metabolism. In conclusion, we have successfully generated an initial proteome database for S. canicula seminal plasma and spermatozoa. Furthermore, we have identified protein variations, predominantly within spermatozoa, between aquarium and wild populations of S. canicula. These findings provide a foundation for future biomarker discovery in shark reproduction studies. However, additional research is required to determine whether these protein variations correlate with reproductive declines in captive sharks.

Colorectal cancer cells with stably expressed SIRT3 demonstrate proliferating retardation by Wnt/β-catenin cascade inactivation.

Colorectal cancer (CRC) is a typical and lethal digestive system malignancy. In this study, we investigated the effect of sirtuin 3 (SIRT3) expression, a fidelity mitochondrial protein, on the proliferation of CRC cells and the mechanisms involved. Using the University of Alabama at Birmingham Cancer Data Analysis Portal database and the Clinical Proteomic Tumour Analysis Consortium database, we discovered that low expression of SIRT3 in CRC was a negative factor for survival prognosis (P < .05). Meanwhile, SIRT3 expression was correlated with distant metastasis and tumour, node, metastasis stage of CRC patients (P < .05). Subsequently, we observed that CRC cells with stable SIRT3 expression exhibited a significant decrease in proliferative capacities both in vitro and in vivo, compared to their counterparts (P < .05). Further investigation using western blot, immunoprecipitation and TOPflash/FOPflash assay showed the mechanism of growth retardation of these cells was highly associated with the degradation of β-catenin in cytosol, and the localization of β-catenin/α-catenin complex in the nucleus. In conclusion, our findings suggest that the inhibition of CRC cell proliferation by SIRT3 is closely associated with the inactivation of the Wnt/β-catenin signalling pathway.

Effect of ultrasonic processing on beef tenderness in longissimus lumborum during aging by proteomics analysis

This investigation was aimed to evaluate the proteins related to beef tenderness at different aging times (1, 3, 7 d) and to explain the changes in the longissimus lumborum at the molecular level with ultrasound treatment. The pH value decreased significantly (p<0.05) with increasing aging time, and was lower in the ultrasonic group compared to the non-ultrasonic group. It indicated that ultrasound had a positive effect on tenderness by maintaining lower cooking loss, higher water-holding capacity (WHC), and higher myofibril fragmentation index (MFI), as demonstrated by the immunoblotting analysis of desmin and caspase-3. Twenty-eight proteins were identified as potential markers of tenderness. A PCA analysis confirmed the differential expression of tenderness-related proteins. Bioinformatics analysis suggested that these proteins, which were distributed in the cytoplasm, membrane, and mitochondria, were more likely to be impacted by ultrasound. Overall, the identified proteomics database of beef serves as a valuable reference for using ultrasound to enhance meat quality and reduce aging duration.

The Selenoproteome as a Dynamic Response Mechanism to Oxidative Stress in Hydrogenotrophic Methanogenic Communities.

Methanogenesis is a critical process in the carbon cycle that is applied industrially in anaerobic digestion and biogas production. While naturally occurring in diverse environments, methanogenesis requires anaerobic and reduced conditions, although varying degrees of oxygen tolerance have been described. Microaeration is suggested as the next step to increase methane production and improve hydrolysis in digestion processes; therefore, a deeper understanding of the methanogenic response to oxygen stress is needed. To explore the drivers of oxygen tolerance in methanogenesis, two parallel enrichments were performed under the addition of H2/CO2 in an environment without reducing agents and in a redox-buffered environment by adding redox mediator 9,10-anthraquinone-2,7-disulfonate disodium. The cellular response to oxidative conditions is mapped using proteomic analysis. The resulting community showed remarkable tolerance to high-redox environments and was unperturbed in its methane production. Next to the expression of pathways to mitigate reactive oxygen species, the higher redox potential environment showed an increased presence of selenocysteine and selenium-associated pathways. By including sulfur-to-selenium mass shifts in a proteomic database search, we provide the first evidence of the dynamic and large-scale incorporation of selenocysteine as a response to oxidative stress in hydrogenotrophic methanogenesis and the presence of a dynamic selenoproteome.