SEARCH · PubMed Health

Results for “Proteomics techniques”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2025

T cell population size control by coronin 1 uncovered: from a spot identified by two-dimensional gel electrophoresis to quantitative proteomics.

INTRODUCTION: Recent work identified members of the evolutionarily conserved coronin protein family as key regulators of cell population size. This work originated ~25 years ago through the identification, by two-dimensional gel electrophoresis, of coronin 1 as a host protein involved in the virulence of Mycobacterium tuberculosis. We here describe the journey from a spot on a 2D gel to the recent realization that coronin proteins represent key controllers of eukaryotic cell population sizes, using ever more sophisticated proteomic techniques. AREAS COVERED: We discuss the value of 'old school' proteomics using relatively simple and cost-effective technologies that allowed to gain insights into subcellular proteomes and describe how label-free quantitative (phospho)proteomics using mass spectrometry allowed to disentangle the role for coronin 1 in eukaryotic cell population size control. Finally, we mention potential implications of coronin-mediated cell population size control for health and disease. EXPERT OPINION: Proteome analysis has been revolutionized by the advent of modern-day mass spectrometers and is indispensable for a better understanding of biology. Here, we discuss how careful dissection of physio-pathological processes by a combination of proteomics, genomics, biochemistry and cell biology may allow to zoom in on the unexplored, thereby possibly tackling hitherto unasked questions and defining novel mechanisms.

Proteomics↗

PubMed2025

Glutamate molecular structure and protein affect the inhibition of breast cancer cell metastasis: Cell-derived exosomes inhibitory effects through the MAPK signaling pathway.

The aim of this study was to investigate the inhibitory effect of glutamate molecular structure and protein on breast cancer cell metastasis and the potential inhibitory mechanism of cell-derived exosomes via MAPK signaling pathway. Breast cancer cell lines with high metastatic potential were selected by in vitro cell culture technique. The effects of specific inhibitors of glutamic acid on the proliferation and metastasis of breast cancer cells were studied. Changes in protein expression profiles were analyzed by proteomics techniques to identify key proteins associated with breast cancer metastasis. Breast cancer cells were treated with inhibitors of the MAPK signaling pathway to evaluate their effect on cell metastasis and compare with exosome treatment. The results showed that the specific inhibitors of glutamate molecular structure could significantly inhibit the proliferation and metastasis of breast cancer cells. Proteomic analysis revealed several down-regulated proteins that are closely related to breast cancer metastasis.

Humans↗

PubMed2025

Multi-Omics and Integrative Analytics in Natural Products Discovery.

Natural products (NPs) have long been an essential source of new bioactive compounds for drug discovery; however, traditional methods for screening and isolating these compounds can be slow and often yield diminishing returns. Fortunately, advanced multi-omics and computational approaches present powerful solutions to these challenges. This review highlights innovative methodologies that integrate metabolomics, genomics, transcriptomics, and proteomics with bioinformatics and analytical chemistry to accelerate NP discovery. For instance, untargeted metabolomics platforms like high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) and Global Natural Products Social (GNPS) molecular networking allow for comprehensive profiling of new compounds, while targeted isotope-labeling strategies enhance this process. Additionally, genome and metagenome mining tools such as antibiotics and secondary metabolite analysis shell (antiSMASH), Deep Biosynthetic Gene Cluster (DeepBGC), and Pipeline for Reconstructing Integrated Syntheses of Metabolites (PRISM) quickly identify biosynthetic gene clusters (BGCs) in both cultured and uncultured organisms, often using heterologous expression to validate products. Transcriptomic analyses, including RNA sequencing (RNA-seq), co-expression networks, and fluxomics, help clarify how pathways are regulated, while quantitative proteomics techniques like tandem mass tags/isobaric tags for relative and absolute quantitation (TMT/iTRAQ) and label-free methods, along with chemoproteomics approaches such as cellular thermal shift assay and thermal proteome profiling (TPP), uncover molecular targets and their mechanisms of action. This review also places significant emphasis on the role of artificial intelligence (AI) and machine learning (ML) in integrating multi-omics data, spanning activities from constructing gene-metabolite correlation networks to leveraging knowledge graphs and graph neural networks for data fusion and functional prediction. Finally, this review concludes by discussing the synergistic benefits of multi-omics for natural-product discovery, addressing current technical challenges, and exploring future directions toward high-throughput, intelligent data integration for next-generation NP research.

Biological Products↗

PubMed2026

Proteomic profiling of bone for the estimation of post-mortem interval and post-mortem submersion interval: a systematic review.

Accurate estimation of the Post-Mortem Interval (PMI) and Post-Mortem Submersion Interval (PMSI) remains a persistent challenge in forensic science, especially when traditional morphological and entomological methods fail due to advanced decomposition or in aquatic environments. Proteomic profiling of bone tissues has recently emerged as a promising approach, leveraging the predictable degradation patterns of bone proteins to estimate time since death more reliably. This systematic review, conducted in accordance with PRISMA guidelines, analyzed 24 peer-reviewed studies focusing on the application of proteomic techniques to bone tissue for PMI and PMSI estimation. The included studies were evaluated based on sample type, analytical techniques used, identified biomarkers, environmental conditions assessed, and the overall reliability and reproducibility of the findings. The review found that specific bone proteins, particularly collagen, osteocalcin, fetuin-A, etc. exhibited consistent degradation patterns that correlated strongly with elapsed post-mortem time. Cortical bone was identified as a more stable and informative matrix compared to trabecular bone. Mass spectrometry, especially LC-MS/MS, emerged as the predominant analytical technique due to its high sensitivity and accuracy in detecting low-abundance proteins over extended PMIs and PMSIs. However, protein degradation rates were significantly influenced by environmental variables such as temperature, humidity, soil pH, and microbial activity. This review also emphasizes the transformative role of bone proteomics in advancing forensic science while identifying key gaps that must be addressed to achieve global standardization and practical implementation in diverse forensic contexts. The integration of proteomics with other emerging technologies, such as machine learning algorithms and computational modeling, may further enhance the precision of PMI and PMSI estimation in future applications.

Postmortem Changes↗

PubMed2024

Secretome Analysis Using Affinity Proteomics and Immunoassays: A Focus on Tumor Biology.

The study of the cellular secretome using proteomic techniques continues to capture the attention of the research community across a broad range of topics in biomedical research. Due to their untargeted nature, independence from the model system used, historically superior depth of analysis, as well as comparative affordability, mass spectrometry-based approaches traditionally dominate such analyses. More recently, however, affinity-based proteomic assays have massively gained in analytical depth, which together with their high sensitivity, dynamic range coverage as well as high throughput capabilities render them exquisitely suited to secretome analysis. In this review, we revisit the analytical challenges implied by secretomics and provide an overview of affinity-based proteomic platforms currently available for such analyses, using the study of the tumor secretome as an example for basic and translational research.

Humans↗

PubMed2025

Proteome organ aging and cardiometabolic risk in a population at risk for heart failure.

BACKGROUND: Biological aging varies across individuals and tissues, influencing chronic diseases, including heart failure (HF). Emerging proteome techniques enable quantification of organ-specific aging acceleration (OAA), but whether OAA relates to HF severity and differs by sex remains unclear. We aim to assess the sex-related association between OAA of heart, artery and kidneys and HF severity, and to investigate relevant cardiometabolic risk factors of organ aging. METHODS: In 556 participants from the HELPFul cohort, we estimated predicted biological age for heart, artery, and kidneys using plasma proteomics and calculated OAA as the deviation from chronological age. Associations between OAA and HF stage, echocardiographic parameters, and cardiometabolic risk factors were evaluated using regression models. Composite indices, including triglyceride-glucose body mass index (TyG-BMI), c-reactive protein-triglyceride glucose index and triglyceride-to-HDL cholesterol ratio were assessed for associations with advanced OAA. RESULTS: Mean age was 63 ± 9 years; 65% were women. Patients were classified as HF stage A (35%), B (29%) and C/D (36%). Heart OAA was significantly associated with advanced HF (Stage C/D) in both sexes (OR = 1.12, 95% CI 1.03 to 1.23 in women; OR = 1.18, 95% CI 1.05 to 1.32 in men), while artery OAA was linked to HF only in women (OR = 1.10, 95% CI 1.01 to 1.18). Multi-organ aging (≥ 2 organs with advanced OAA) conferred over three-fold higher odds of being in Stage C/D. Heart OAA correlated with impaired cardiac structure and function, particularly reduced ejection fraction in men and increased left ventricular mass index in both sexes. Diabetes emerged as the most relevant factor of artery and kidney OAA. TyG-BMI was significantly associated with advanced kidney OAA, only in women (z-scored OR = 1.88, 95% CI 1.45 to 2.45). CONCLUSIONS: Proteome-derived organ aging correlates with HF severity, with possible sex-related patterns. Diabetes and higher TyG-BMI are associated with faster organ aging, which may reflect shared aging mechanisms between metabolic dysfunction and HF.

Humans↗

PubMed2026

AI-driven diagnostic and prognostic models for metabolic dysfunction-associated steatotic liver disease: insights from clinical, imaging, and multi-omics studies-a scoping review.

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is the most common chronic liver disease around the world, affecting 33.6% of the adult population (95% CI: 28.1%-39.5%; I 2 = 99.9%), or roughly one in three. The extent of the liver damage is variable, from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH, formerly NASH), cirrhosis and hepatocellular carcinoma (HCC). Early diagnosis is essential to prevent serious liver damage. Traditional diagnostic techniques such as liver biopsy, imaging, and biomarker testing are all invasive, costly, reduced sensitive to early-stage disease, and they also have variability among observers. Modern diagnostic and prognostic approaches based on the principles of Artificial Intelligence (AI) and specifically on machine learning (ML) and deep learning (DL) have enabled multimodal approaches integrating clinical, imaging and molecular data. This scoping review conducted per PRISMA-ScR guidelines, synthesizes findings from 73 studies (search window 2020-2026) across three dimensions: clinical data driven models, imaging-based classifiers (ultrasound, CT and MRI), and multi-omics (genomics, transcriptomics and proteomics) techniques. Moreover, emergence of models such as U-Net and LiverNet 2.x, classification models like DeepLiverNet and BiLSTM models, as well as transformer frameworks and the identification of biomarkers models are also described. This study also investigates challenges such as data heterogeneity, data interpretability, fairness and real-world clinical application. Finally, important areas of research opportunities and future directions are highlighted to present a developing clinically applicable, explainable and ethical AI solutions to manage MASLD.

MASLD↗

PubMed2025

Tonic signaling of the B-cell antigen-specific receptor is a common functional hallmark in chronic lymphocytic leukemia cell phosphoproteomes at early disease stages.

B-cell chronic lymphocytic leukemia (B-CLL) is characterized by highly heterogeneous genomic alterations and altered signaling pathways, with limited studies on its proteome. Our study presents a comprehensive analysis of the proteome and phosphoproteome in B-CLL and CLL-like monoclonal B-cell lymphocytosis (MBL) primary cells. Using high-resolution mass spectrometry, we identified 2970 proteins and 316 phosphoproteins across five tumor samples, including 55 newly identified phosphopeptides (ProteomeXchange-PXD005997). Our multifaceted approach also integrated protein microarrays and western blotting for further data validation in a new patient cohort of 14 patients. Despite sharing 73% of their proteomes, the phosphoproteomes varied significantly among samples, independent of cytogenetic alterations and immunoglobulin heavy variable cluster (IGHV) mutational status. We identified common functional hallmarks in B-CLL and MBL phosphoproteomes, notably tonic signaling (low-level, constitutive signaling) of the B-cell antigen-specific receptor (BCR) and nuclear factor NF-kappa-B (NF-kβ)/signal transducer and activator of transcription 3 (STAT3) pathways. Nine phosphoproteins involved in BCR signaling were further validated, showing a high correlation with early disease stages. Our study advances the field by providing a detailed perspective on the proteome and phosphoproteome of B-CLL cells, revealing signaling pathways crucial for disease development and progression. Integrating diverse proteomics techniques and identifying novel phosphopeptides offers new insights into CLL biology, potentially informing future therapeutic strategies and biomarker development for early diagnosis and personalized treatment.

Humans↗

PubMed2026

Analytical challenges for mapping non-canonical and non-protein ubiquitin/Ubl modifications by mass spectrometry.

INTRODUCTION: Covalent modification by ubiquitin via Lys isopeptide bonds is fundamental for regulating protein turnover and function. Additionally, ubiquitin esterification occurs on Ser/Thr/Tyr residues in proteins and on non-proteinaceous substrates including ribose, saccharides, lipids, and small molecule drugs. Ubiquitin posttranslational modifications may therefore be much more widespread across cell biological pathways. Recent literature (PubMed) reflects the increased interest in analytical methods for mapping of non-canonical substrates modified by ubiquitin and ubiquitin-like (UBL) proteins. AREAS COVERED: Mass spectrometry (MS)-based methodologies involve advanced proteomic techniques to identify ubiquitin modifications on amino acids other than Lys, such as Ser, Thr, Tyr and Cys as well as protein N-termini. After digestion, standard MS workflows identify canonical ubiquitination by detecting a ubiquitin C-terminal tag attached to the amine side chains of Lys residues of substrate-derived peptides suitable for MS/MS sequencing. For non-canonical modifications on proteins and substrates other than proteins, specialized strategies are required, such as using antibodies to enrich N-terminally modified peptides in combination with using high-resolution MS/MS based on softer fragmentation technologies to detect esterification and possibly other types of substrate modifications. EXPERT OPINION: Enabling such technologies will reveal a previously unrecognized angle of the ubiquitin code's complexity in cells.

Humans↗

PubMed2026

Extracellular Vesicles From Glioblastoma Cells Reflect 2D vs. 3D Culture Adaptation and Resistance to Temozolomide.

Glioblastoma (GBM) is an aggressive brain tumor marked by extensive heterogeneity, resistance to therapy, and dismal prognosis. Extracellular vesicles (EVs) have emerged as key players in GBM biology, mediating intercellular communication and therapy adaptation. However, the exact functions and molecular impact of EVs in GBM remain incompletely understood. In this study, we performed a comparative proteomic analysis of U87MG GBM cells grown in two-dimensional (2D) monolayers and three-dimensional (3D) spheroids following temozolomide (TMZ) treatment, alongside characterization of EVs derived from both culture systems. 3D-spheroids secreted more EVs of smaller size and exhibited a more TMZ-resistant, stem-like proteome under TMZ-induced genotoxic stress. In contrast, 2D cell cultures demonstrated greater proteome remodeling, with EVs enriched in protein families involved in DNA repair, oxidative stress adaptation, and methylation processes. Notably, several methyltransferases were decreased intracellularly but selectively retained in EVs, suggesting active sorting to influence the tumor microenvironment or modulate epigenetic states in recipient cells. EVs also carried adhesion molecules and signaling proteins linked to migration, invasion, and Wnt pathway activation, as well as metabolic enzymes connecting serine metabolism and redox control to TMZ resistance. Mapping EV and cellular proteomes onto The Cancer Genome Atlas (TCGA) dataset identified prognostic protein families associated with either poor or favorable patient outcomes. Our data demonstrate that EV cargo composition mirrors TMZ-induced phenotypic adaptation and reveals molecular mechanisms underlying therapeutic resistance. These EV-associated signatures may serve as clinically actionable biomarkers for patient stratification and offer potential targets to overcome chemoresistance in GBM.

Humans↗

PubMed2026

Subcellular Proteomic Analyses Reveal REEP5 Knockdown in the Mouse Heart Disrupts Mitochondrial Networks.

Receptor Expression-Enhancing Protein 5 (REEP5) is a cardiac-enriched, membrane-shaping protein localized to the sarco(endo)plasmic reticulum (SR/ER), where it supports membrane network architecture and cardiomyocyte function. While REEP5 has been implicated in calcium handling and contractility, its role in regulating inter-organelle communication and mitochondrial homeostasis remains less well-understood. In this study, we used recombinant adeno-associated virus serotype 9-mediated shRNA knockdown of Reep5 in mouse hearts, combined with subcellular fractionation and data-independent acquisition mass spectrometry, to define proteomic remodeling across microsomal (SR/ER), mitochondrial, and cytosolic compartments. Loss of REEP5 altered the composition of SR/ER membrane-shaping proteins, including upregulation of RTN4, ATL3, and CKAP4, suggesting a partial compensatory response. Microsomal, mitochondrial and cytosolic proteomes exhibited broad reorganization, with enrichment of proteins involved in redox adaptation and proteostasis, alongside depletion of mitochondrial import machinery and antioxidant enzymes. Imaging of isolated cardiomyocytes confirmed fragmented mitochondrial networks and increased reactive oxygen species, consistent with proteomic signatures of disrupted mitochondrial dynamics and oxidative stress. Gene ontology enrichment across all fractions highlighted widespread dysregulation in organelle-specific processes, including translation, protein localization, and metabolic remodeling. Notably, several altered pathways converged on mitochondria-associated membranes, suggesting that REEP5 may support SR/ER-mitochondria tethering and functional crosstalk. These findings position REEP5 as a key regulator of organelle homeostasis in the heart and underscore how its loss disrupts mitochondrial integrity and inter-organelle communication across cellular compartments.

Animals↗

PubMed2026

Post-translational modification of proteins in the human testis development pathway.

BACKGROUND: The foetal testes produce the androgens necessary to masculinise the developing embryo and support the maturation of germ cells, that will eventually develop into sperm, thus ensuring future reproductive capacity. The testes develop from the bi-potential gonads in a highly orchestrated process resulting in the differentiation of a complex tissue with multiple cellular lineages. While recent transcriptomic and chromatin-based analyses of human foetal testes have provided an unprecedented level of insight into signalling pathways activated during this process, proteomic studies of the human foetal gonads remain limited. Proteins are active molecules and post-translational modification (PTM) of proteins influences protein activity, stability and localisation. Studies have shown that PTMs regulate critical proteins in testis development, and their disruptions are implicated in congenital disorders including differences of sex development (DSD), in which sex development is atypical. Despite this, the role and regulation of protein PTM during human testis development remains poorly understood due to limited access to human foetal gonadal tissue, a paucity of large-scale proteomics studies, and a lack of robust of human gonad in vitro models. OBJECTIVE AND RATIONALE: This review aims to provide a comprehensive analysis of validated PTMs affecting proteins critical for testicular development. We discuss PTMs with evidence for a role in normal testis development, and highlight those disrupted in DSD. We review emerging techniques, including proteomic technologies and organ modelling systems that may advance our understanding of PTMs in foetal testis development. We discuss challenges that have restricted the application of these technologies and how overcoming these will significantly improve our understanding of testis development and disease, diagnostics and patient outcomes. SEARCH METHODS: We searched PubMed and the University of Melbourne library for peer-reviewed English-language studies using keywords such as phosphorylation, SUMOylation, acetylation, ubiquitination alongside each protein of interest. PTM sites in proteins involved in testis development were identified using the PhosphoSitePlus database focusing those confirmed in in vitro or animal model studies. ClinVar and the Human Gene Mutation Database were used to identify patient variants that may disrupt PTM sites. OUTCOMES: Our review finds that proteins required for human foetal testis development are subject to extensive PTM. Several PTM sites and PTM-mediated pathways [e.g. MAPK (mitogen-activated protein kinase) pathway] are disrupted in patients with DSD or related conditions. While recent advances in proteomics technologies hold considerable promise, their application to human foetal gonads has been constrained by technical, ethical, and logistical challenges. Encouragingly, emerging high-sensitivity and low-input technologies, alongside stem cell-based approaches, offer viable pathways to overcoming these barriers. WIDER IMPLICATIONS: The relationship between gene regulation, protein expression, and cellular outcome is inherently non-linear, shaped by additional regulatory layers-most notably PTMs. The contribution of PTMs to human testis development in both typical and atypical contexts is a major knowledge gap. Addressing this gap has broad clinical and biological relevance: it may help improve genetic diagnosis or shed light on how proteins or pathways critical for testis development respond to environmental signals-an increasingly pressing question as declining global fertility rates bring testicular function under greater scrutiny. REGISTRATION NUMBER: N/A.

Humans↗

PubMed2026

Protocol for the isolation and characterization of extracellular vesicles and particles from human and murine cell lines.

Cells produce a heterogeneous population of extracellular vesicles and particles (EVPs). Small extracellular vesicles (sEVs or exosomes) are lipid membrane-enclosed vesicles with sizes ranging from 30 to 150 nm. Here, we present a protocol to isolate and characterize EVPs from the conditioned medium of cell lines. We describe steps for cell culture, conditioned media collection, differential ultracentrifugation, and EVP characterization. We then detail procedures for proteomic and biodistribution analyses. For complete details on the use and execution of this protocol, please refer to Yeung et al.1.

Animals↗

PubMed2025

Shared and divergent acute cardiovascular risk protein responses to lipid infusion in women with and without PCOS.

AIMS: Elevated circulating lipids are linked to cardiovascular disease (CVD), especially in insulin-resistant states like polycystic ovary syndrome (PCOS), but their effects on cardiovascular risk proteins (CVRPs) remain unclear. This study used a two-step approach to examine acute cardiovascular proteomic responses to lipid-induced metabolic stress. We first identified proteins altered by lipids and insulin in healthy control (HC) women, then assessed whether these responses were similar or divergent in women with PCOS. METHODS: In a randomised cross-over study, 10 healthy controls and 12 women with PCOS underwent 5-h saline (control) or intralipid infusions. After 3 h, a 2-h hyperinsulinemic-euglycemic clamp was initiated. Plasma CVRP expression was assessed at baseline, post-lipid (180 min) and post-clamp (300 min) using SOMAscan proteomics. STRING and pathway enrichment analyses were performed to explore functional associations. RESULTS: In the HC group, lipid infusion altered the expression of 11 out of 54 CVRPs including increases in RANK, IL2RA, TACI, SLAF5 and DCN (p <0.05) and decreases in THPO, BOC, SOD2, FGF23, and AgRP (p <0.05). Most changes reversed with insulin, but BOC, SOD2, MMP12, FGF23, and DCN remained dysregulated. In PCOS, responses mirrored the HC group except for lower AgRP following lipid infusion (p <0.01), and persistent elevation of SLAF5 and DCN following insulin (p <0.05). Enrichment analysis linked altered proteins to immune activation, cell proliferation, and cytokine-receptor signalling. CONCLUSION: Acute lipid infusion revealed shared and phenotype-specific proteomic responses linked to early vascular stress. In PCOS, persistent dysregulation suggests reduced metabolic adaptability, with exploratory signals that may complement established biomarkers of early cardiovascular risk.

Humans↗

PubMed2026

Proteomics in environmental pollution research: Advances, challenges, and future directions.

Environmental proteomics has emerged as a powerful approach for elucidating the molecular mechanisms underlying pollutant-induced biological effects. Although this field has developed rapidly, the systematic review of recent proteomics applications in environmental pollution research remains limited. This review explored the emerging roles of toxicoproteomics in biomarker discovery and mechanistic elucidation, as well as ecotoxicoproteomics in ecological risk assessment and bioremediation strategies. Here, we review the field, highlighting recent trends such as the integration of proteomics with genomics, transcriptomics, and metabolomics to provide a comprehensive view of biological responses to environmental stressors. We further discuss the growing application of artificial intelligence in improving proteomics data interpretation and accelerating biomarker discovery. In addition, recent technological advances in environmental proteomics are highlighted, including next-generation tissue microarray proteomics, nanoscale proteomics, single-cell proteomics, and spatial proteomics. Despite its potential, proteomics faces challenges, such as high operational costs, computational complexity in analysis, and technical limitations in low-abundance protein detection. We propose that the convergence of proteomics with artificial intelligence and multi-omics approaches offers promising solutions to these challenges, enhancing the practical application of proteomics in environmental monitoring and risk assessment.

Proteomics↗

PubMed2026

Canine Tear Proteomics: A New Frontier in Veterinary Ophthalmology.

Canine tear proteomics is an emerging field with significant potential for advancing both veterinary ophthalmology and comparative biomedical research. Tears are a readily accessible, non-invasive biofluid that contain a mixture of proteins involved in ocular surface protection, immune defense, and intercellular signaling. In dogs, tear proteomics studies have revealed biomarkers associated with various ocular and non-ocular diseases including keratoconjunctivitis sicca (KCS), glaucoma, neoplasia, and diabetes mellitus. This review compiles all previous studies conducted on the comprehensive canine tear proteome and highlights some of the key tear proteomic studies in human biomedical research. Tear film composition, study design, technological advancements, and select tear proteins are discussed along with key protein alterations and their use as potential biomarkers of disease. Fundamental challenges, clinical implications, and future directions of this rapidly growing field are discussed in detail. As proteomic technology and analytical techniques continue to evolve, canine tear proteomics will become a valuable tool for the veterinary ophthalmologist, enabling the early identification and diagnosis of ocular disease as well as providing a means for monitoring treatment outcomes, disease progression, and overall prognosis for the canine patient.

Animals↗

PubMed2025

Proteomics-enabled learning machine algorithms enhance the prediction of cardiovascular diseases in patients with type 2 diabetes mellitus.

BACKGROUND AND AIMS: Estimating the risk of cardiovascular disease (CVD) complications in type 2 diabetes mellitus (T2DM) patients is critical in the medical decision-making process. This study aimed to use a machine learning technique combined with proteomics to develop personalized models for predicting CVD in patients with T2DM. METHODS AND RESULTS: In total, 874 patients with T2DM and 2,920 Olink proteins obtained from the UK Biobank were used in this study. Proteins were screened using Cox regression and LASSO regression. A basic model containing clinical features and a full model combining proteome and clinical features were constructed using the random survival forest algorithm. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the predictive performance of the models and compare them with other CVD predictive models. Compared with the basic model, the full model performed better in predicting CVD, with time-dependent AUCs of 0.81 (3 years), 0.74 (5 years) and 0.74 (10 years) (0.77, 0.69 and 0.67). We calculated the risk scores of the Framingham, ASCVD and Score2-Diabetes models. The results revealed that the prediction performance of the full model was also better than that of the abovementioned models. In terms of differentiation accuracy, the results of the net reclassification improvement index and integrated discrimination improvement index showed that the full model can identify high-risk individuals more accurately (accuracy rate: 79% vs. 69%). CONCLUSIONS: Proteomics can be used to predict cardiovascular complications in diabetic patients. It is also necessary to consider the applicability of the model due to the limitations of the sample size and the constraints of proteomics in clinical applications.

Humans↗

PubMed2024

Omics approaches to unravel insecticide resistance mechanism in Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae).

Bemisia tabaci (Gennadius) whitefly (BtWf) is an invasive pest that has already spread worldwide and caused major crop losses. Numerous strategies have been implemented to control their infestation, including the use of insecticides. However, prolonged insecticide exposures have evolved BtWf to resist these chemicals. Such resistance mechanism is known to be regulated at the molecular level and systems biology omics approaches could shed some light on understanding this regulation wholistically. In this review, we discuss the use of various omics techniques (genomics, transcriptomics, proteomics, and metabolomics) to unravel the mechanism of insecticide resistance in BtWf. We summarize key genes, enzymes, and metabolic regulation that are associated with the resistance mechanism and review their impact on BtWf resistance. Evidently, key enzymes involved in the detoxification system such as cytochrome P450 (CYP), glutathione S-transferases (GST), carboxylesterases (COE), UDP-glucuronosyltransferases (UGT), and ATP binding cassette transporters (ABC) family played key roles in the resistance. These genes/proteins can then serve as the foundation for other targeted techniques, such as gene silencing techniques using RNA interference and CRISPR. In the future, such techniques will be useful to knock down detoxifying genes and crucial neutralizing enzymes involved in the resistance mechanism, which could lead to solutions for coping against BtWf infestation.

Hemiptera↗