RESUMEN
The developmental origins of healthy and disease (DOHaD) concept has demonstrated a higher rate of chronic diseases in the adult population of individuals whose mothers experienced severe maternal protein restriction (MPR). Using proteomic and in silico analyses, we investigated the lung proteomic profile of young and aged rats exposed to MPR during pregnancy and lactation. Our results demonstrated that MPR lead to structural and immune system pathways changes, and this outcome is coupled with a rise in the PI3k-AKT-mTOR signaling pathway, with increased MMP-2 activity, and CD8 expression in the early life, with long-term effects with aging. This led to the identification of commonly or inversely differentially expressed targets in early life and aging, revealing dysregulated pathways related to the immune system, stress, muscle contraction, tight junctions, and hemostasis. We identified three miRNAs (miR-378a-3p, miR-378a-5p, let-7a-5p) that regulate four proteins (ACTN4, PPIA, HSPA5, CALM1) as probable epigenetic lung marks generated by MPR. In conclusion, MPR impacts the lungs early in life, increasing the possibility of long-lasting negative outcomes for respiratory disorders in the offspring.
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Pulmón , MicroARNs , Proteómica , Animales , Femenino , Pulmón/metabolismo , Masculino , Proteómica/métodos , Embarazo , MicroARNs/genética , MicroARNs/metabolismo , Ratas , Efectos Tardíos de la Exposición Prenatal/metabolismo , Efectos Tardíos de la Exposición Prenatal/genética , Dieta con Restricción de Proteínas , Transducción de Señal , Serina-Treonina Quinasas TOR/metabolismo , Serina-Treonina Quinasas TOR/genética , Longevidad/genética , Ratas Wistar , Proteínas Proto-Oncogénicas c-akt/metabolismo , Proteoma/metabolismo , Fosfatidilinositol 3-Quinasas/metabolismo , Fosfatidilinositol 3-Quinasas/genética , Envejecimiento/metabolismo , Envejecimiento/genética , Metaloproteinasa 2 de la Matriz/metabolismo , Metaloproteinasa 2 de la Matriz/genéticaRESUMEN
Current stage of proteomic research in the field of biology, medicine, development of new drugs, population screening, or personalized approaches to therapy dictates the need to analyze large sets of samples within the reasonable experimental time. Until recently, mass spectrometry measurements in proteomics were characterized as unique in identifying and quantifying cellular protein composition, but low throughput, requiring many hours to analyze a single sample. This was in conflict with the dynamics of changes in biological systems at the whole cellular proteome level upon the influence of external and internal factors. Thus, low speed of the whole proteome analysis has become the main factor limiting developments in functional proteomics, where it is necessary to annotate intracellular processes not only in a wide range of conditions, but also over a long period of time. Enormous level of heterogeneity of tissue cells or tumors, even of the same type, dictates the need to analyze biological systems at the level of individual cells. These studies involve obtaining molecular characteristics for tens, if not hundreds of thousands of individual cells, including their whole proteome profiles. Development of mass spectrometry technologies providing high resolution and mass measurement accuracy, predictive chromatography, new methods for peptide separation by ion mobility and processing of proteomic data based on artificial intelligence algorithms have opened a way for significant, if not radical, increase in the throughput of whole proteome analysis and led to implementation of the novel concept of ultrafast proteomics. Work done just in the last few years has demonstrated the proteome-wide analysis throughput of several hundred samples per day at a depth of several thousand proteins, levels unimaginable three or four years ago. The review examines background of these developments, as well as modern methods and approaches that implement ultrafast analysis of the entire proteome.
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Espectrometría de Masas , Proteómica , Proteómica/métodos , Humanos , Proteoma/análisis , Proteoma/metabolismoRESUMEN
In recent years, advancements in deep learning techniques have significantly expanded the structural coverage of the human proteome. GalaxySagittarius-AF translates these achievements in structure prediction into target prediction for druglike compounds by incorporating predicted structures. This web server searches the database of human protein structures using both similarity- and structure-based approaches, suggesting potential targets for a given druglike compound. In comparison to its predecessor, GalaxySagittarius, GalaxySagittarius-AF utilizes an enlarged structure database, incorporating curated AlphaFold model structures alongside their binding sites and ligands, predicted using an updated version of GalaxySite. GalaxySagittarius-AF covers a large human protein space compared to many other available computational target screening methods. The structure-based prediction method enhances the use of expanded structural information, differentiating it from other target prediction servers that rely on ligand-based methods. Additionally, the web server has undergone enhancements, operating two to three times faster than its predecessor. The updated report page provides comprehensive information on the sequence and structure of the predicted protein targets. GalaxySagittarius-AF is accessible at https://galaxy.seoklab.org/sagittarius_af without the need for registration.
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Proteoma , Humanos , Proteoma/química , Proteoma/metabolismo , Ligandos , Bases de Datos de Proteínas , Sitios de Unión , Programas Informáticos , Biología Computacional/métodos , Conformación Proteica , Aprendizaje Profundo , Descubrimiento de Drogas/métodos , Modelos Moleculares , Proteínas/química , Proteínas/metabolismoRESUMEN
Congenital Anomalies of the Kidney and Urinary Tract (CAKUT) is the leading cause of childhood chronic kidney failure and a significant cause of chronic kidney disease in adults. Genetic and environmental factors are known to influence CAKUT development, but the currently known disease mechanism remains incomplete. Our goal is to identify affected pathways and networks in CAKUT, and thereby aid in getting a better understanding of its pathophysiology. With this goal, the miRNome, peptidome, and proteome of over 30 amniotic fluid samples of patients with non-severe CAKUT was compared to patients with severe CAKUT. These omics data sets were made findable, accessible, interoperable, and reusable (FAIR) to facilitate their integration with external data resources. Furthermore, we analysed and integrated the omics data sets using three different bioinformatics strategies: integrative analysis with mixOmics, joint dimensionality reduction and pathway analysis. The three bioinformatics analyses provided complementary features, but all pointed towards an important role for collagen in CAKUT development and the PI3K-AKT signalling pathway. Additionally, several key genes (CSF1, IGF2, ITGB1, and RAC1) and microRNAs were identified. We published the three analysis strategies as containerized workflows. These workflows can be applied to other FAIR data sets and help gaining knowledge on other rare diseases.
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Colágeno , Fosfatidilinositol 3-Quinasas , Proteínas Proto-Oncogénicas c-akt , Transducción de Señal , Humanos , Proteínas Proto-Oncogénicas c-akt/metabolismo , Proteínas Proto-Oncogénicas c-akt/genética , Fosfatidilinositol 3-Quinasas/metabolismo , Fosfatidilinositol 3-Quinasas/genética , Colágeno/metabolismo , Colágeno/genética , Biología Computacional/métodos , MicroARNs/genética , MicroARNs/metabolismo , Reflujo Vesicoureteral/genética , Reflujo Vesicoureteral/metabolismo , Femenino , Proteoma/metabolismo , Líquido Amniótico/metabolismo , Sistema Urinario/metabolismo , Multiómica , Anomalías UrogenitalesRESUMEN
Clinical expression of coronavirus disease 2019 (COVID-19) infectionis widely variable including fatal cases and patients with mild symptoms and a rapid resolution. We studied saliva from 63 hospitalized COVID-19 patients and from 30 healthy controls by integrating large-scale proteomics, peptidomics and targeted metabolomics to assess the biochemical alterations following the infection and to obtain a set of putative biomarkers useful for noninvasive diagnosis. We used an untargeted approach by using liquid chromatography-tandem mass spectrometry (LC-MS/MS) for proteomics and peptidomics analysis and targeted LC-multiple reaction monitoring/MS for the analysis of amino acids. The levels of 77 proteins were significantly different in COVID-19 patients. Among these, seven proteins were found only in saliva from patients with COVID-19, four were up-regulated and three were down-regulated at least five-folds in saliva from COVID-19 patients in comparison to controls. The analysis of proteins revealed a complex balance between pro-inflammatory and anti-inflammatory proteins and a reduced amount of several proteins with immune activity that possibly favours the spreading of the virus. Such reduction could be related to the enhanced activity of endopeptidases induced by the infection that in turn caused an altered balance of free peptides. In fact, on a total of 28 peptides, 22 (80%) were differently expressed in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and control subjects. The multivariate analysis of such peptides permits to obtain a diagnostic algorithm that discriminate the two populations with a high diagnostic efficiency. Among amino acids, only threonine resulted significantly different between COVID-19 patients and controls, while alanine levels were significantly different between COVID-19 patients with different severity. In conclusion, the present study defined a set of molecules to be detected with a quick and easy method based on mass spectrometry tandem useful to reveal biochemical alterations involved in the pathogenesis of such a complex disease. Data are available via ProteomeXchange with identifier PXD045612.
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Biomarcadores , COVID-19 , Metabolómica , Proteómica , SARS-CoV-2 , Saliva , Espectrometría de Masas en Tándem , Humanos , COVID-19/virología , COVID-19/metabolismo , Saliva/química , Saliva/virología , Espectrometría de Masas en Tándem/métodos , Masculino , Femenino , Proteómica/métodos , Persona de Mediana Edad , Metabolómica/métodos , Biomarcadores/análisis , Biomarcadores/metabolismo , Adulto , Anciano , Cromatografía Liquida/métodos , Estudios de Casos y Controles , Proteoma/análisis , Proteoma/metabolismoRESUMEN
Shortening of telomere length (TL) is correlated with many age-related disorders and is a hallmark of biological aging. This study used proteome-wide Mendelian randomization to identify the protein biomarkers associated with telomere length. Protein quantitative trait loci (pQTL) were derived from two studies, the deCODE Health study (4907 plasma proteins) and the UK Biobank Pharma Proteomics Project (2923 plasma proteins). Summary data from genome-wide association studies (GWAS) for TL were obtained from the UK Biobank (472,174 cases) and GWAS Catalog (418,401 cases). The association between proteins and TL was further assessed using colocalization and summary data-based Mendelian randomization (SMR) analyses. The protein-protein network, druggability assessment, and phenome-wide MR were used to further evaluate the potential biological effects, druggability, and safety of the target proteins. Proteome-wide MR analysis identified 22 plasma proteins that were causally associated with telomere length. Five of these proteins (APOE, SPRED2, MAX, RALY, and PSMB1) had the highest evidence of association with TL and should be prioritized. This study revealed telomere length-related protein biomarkers, providing new insights into the development of new treatment targets for chronic diseases and anti-aging intervention strategies.
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Biomarcadores , Estudio de Asociación del Genoma Completo , Análisis de la Aleatorización Mendeliana , Proteómica , Sitios de Carácter Cuantitativo , Humanos , Biomarcadores/sangre , Proteómica/métodos , Homeostasis del Telómero , Telómero/metabolismo , Telómero/genética , Proteoma/metabolismo , Proteínas Sanguíneas/genética , Proteínas Sanguíneas/metabolismo , Acortamiento del TelómeroRESUMEN
OBJECTIVES: The Ishikawa cell line is the most widely used model system for investigating implantation and endometrial cancer. Understanding the biology of this cell line is essential for developing effective interventional strategies. To gain a deeper understanding of its cellular protein profile, we extracted cellular proteins from Ishikawa cells and analyzed the peptides using mass spectrometry. Our goal was to create a proteomic resource specifically tailored for Ishikawa cells. This data set is of particular significance in the realm of targeted drug delivery. Liposomes are synthetic spherical vesicles composed of hydrophobic bilayer phospholipids and have received immense recognition as highly effective carriers for the delivery of pharmaceutical drugs and essential nutrients to the endometrium. Phosphatidylcholine and phosphatidylethanolamine are often combined to create functional liposomal systems. To discern any potential interfering effects originating from the liposome backbone, our investigation involved direct effects of phospholipid liposomes on endometrial epithelial cells. DATA DESCRIPTION: The data set includes peptide spectra derived from the intracellular proteomes of Ishikawa endometrial cancer cell isolates and their phospholipid-treated counterparts. Representing a proteome-wide profile, this dataset aims to contribute to a broader understanding of the physiology of endometrial epithelial cells. Proteomic analysis identified key proteins involved in the intricate regulation of cellular metabolism, cell cycle progression, and signaling. Between-group analysis revealed no differentially expressed proteins after adjusting for multiple testing using the applied thresholds (p-value < 0.05 and |logFC| > 1). Data are available via ProteomeXchange with identifier PXD050871.
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Neoplasias Endometriales , Liposomas , Proteómica , Femenino , Humanos , Neoplasias Endometriales/metabolismo , Neoplasias Endometriales/patología , Proteómica/métodos , Línea Celular Tumoral , Proteoma/metabolismo , Fosfatidiletanolaminas/metabolismo , Fosfatidilcolinas/metabolismoRESUMEN
Analyses of mitochondrial adaptations in human skeletal muscle have mostly used whole-muscle samples, where results may be confounded by the presence of a mixture of type I and II muscle fibres. Using our adapted mass spectrometry-based proteomics workflow, we provide insights into fibre-specific mitochondrial differences in the human skeletal muscle of men before and after training. Our findings challenge previous conclusions regarding the extent of fibre-type-specific remodelling of the mitochondrial proteome and suggest that most baseline differences in mitochondrial protein abundances between fibre types reported by us, and others, might be due to differences in total mitochondrial content or a consequence of adaptations to habitual physical activity (or inactivity). Most training-induced changes in different mitochondrial functional groups, in both fibre types, were no longer significant in our study when normalised to changes in markers of mitochondrial content.
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Ejercicio Físico , Proteínas Mitocondriales , Humanos , Masculino , Proteínas Mitocondriales/metabolismo , Adulto , Ejercicio Físico/fisiología , Proteómica/métodos , Músculo Esquelético/metabolismo , Mitocondrias Musculares/metabolismo , Adulto Joven , Fibras Musculares Esqueléticas/metabolismo , Descanso/fisiología , Mitocondrias/metabolismo , Proteoma/metabolismo , Adaptación FisiológicaRESUMEN
Zinc (Zn) deficiency is a significant nutritional limitation to crop yield globally, particularly in calcareous soil environments. Tree peony of Peaonia ostii 'Fengdan' is regarded as an oil crop due to its seeds rich in alpha-linolenic acid, a beneficial compound for health promotion. However, low seed yield remains a primary challenge in attaining sufficient seed oil from tree peony. In this study, Zn fertilization was applied to soil or foliage of P. ostii 'Fengdan' in the growth period before fruit development. Our findings reveal that foliar Zn-spraying, as opposed to soil application, proves to be a more effective method for augmenting seed yield, Zn accumulation and photosynthetic capacity in 'Fengdan'. Comparative analyses of the leaf proteome of 'Fengdan' using iTRAQ profiling under foliar Zn-spraying identified 115 differentially expressed proteins (DEPs), including 36 upregulated proteins, which likely contribute to the observed increase in seed yields of 'Fengdan' caused by foliage Zn-spraying. Specifically, Zn2+ stimulation of phosphatidylinositol signaling initiates a cascade of metabolic regulations. Firstly, ATP synthesis promotes leaf photosynthetic capacity, facilitated by improved sucrose metabolism through upregulated pullulanase and 1,4-alpha-glucan-branching enzyme. Furthermore, lipid synthesis and transport are facilitated by upregulated lipoyl synthase and plastid lipid-associated proteins. Additionally, DEPs involved in secondary metabolism are upregulated in the production of various metabolites conducive to 'Fengdan' growth. Overall, our results demonstrate that foliage Zn-spraying enhances seed yield in P. ostii 'Fengdan' by elevating Zn content and secondary metabolite synthesis in leaves, thereby augmenting leaf photosynthetic capacity and lipid synthesis. This study provides an effective way to increase seed yield of tree peony by exogenous Zn application.
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Fotosíntesis , Proteínas de Plantas , Proteoma , Semillas , Zinc , Fotosíntesis/efectos de los fármacos , Zinc/metabolismo , Semillas/metabolismo , Semillas/efectos de los fármacos , Semillas/crecimiento & desarrollo , Proteínas de Plantas/metabolismo , Proteínas de Plantas/genética , Proteoma/metabolismo , Hojas de la Planta/metabolismo , Hojas de la Planta/efectos de los fármacos , Proteómica/métodosRESUMEN
The integration of proteomics data with constraint-based reconstruction and analysis (COBRA) models plays a pivotal role in understanding the relationship between genotype and phenotype and bridges the gap between genome-level phenomena and functional adaptations. Integrating a generic genome-scale model with information on proteins enables generation of a context-specific metabolic model which improves the accuracy of model prediction. This review explores methodologies for incorporating proteomics data into genome-scale models. Available methods are grouped into four distinct categories based on their approach to integrate proteomics data and their depth of modeling. Within each category section various methods are introduced in chronological order of publication demonstrating the progress of this field. Furthermore, challenges and potential solutions to further progress are outlined, including the limited availability of appropriate in vitro data, experimental enzyme turnover rates, and the trade-off between model accuracy, computational tractability, and data scarcity. In conclusion, methods employing simpler approaches demand fewer kinetic and omics data, consequently leading to a less complex mathematical problem and reduced computational expenses. On the other hand, approaches that delve deeper into cellular mechanisms and aim to create detailed mathematical models necessitate more extensive kinetic and omics data, resulting in a more complex and computationally demanding problem. However, in some cases, this increased cost can be justified by the potential for more precise predictions.
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Modelos Biológicos , Proteómica , Proteómica/métodos , Genoma , Humanos , Proteoma/metabolismo , Proteoma/genética , Proteoma/análisisRESUMEN
Predicting the binding of ligands to the human proteome via reverse-docking methods enables the understanding of ligand's interactions with potential protein targets in the human body, thereby facilitating drug repositioning and the evaluation of potential off-target effects or toxic side effects of drugs. In this study, we constructed 11 reverse docking pipelines by integrating site prediction tools (PointSite and SiteMap), docking programs (Glide and AutoDock Vina), and scoring functions (Glide, Autodock Vina, RTMScore, DeepRMSD, and OnionNet-SFCT), and then thoroughly benchmarked their predictive capabilities. The results show that the Glide_SFCT (PS) pipeline exhibited the best target prediction performance based on the atomic structure models in AlphaFold2 human proteome. It achieved a success rate of 27.8% when considering the top 100 ranked prediction. This pipeline effectively narrows the range of potential targets within the human proteome, laying a foundation for drug target prediction, off-target assessment, and toxicity prediction, ultimately boosting drug development. By facilitating these critical aspects of drug discovery and development, our work has the potential to ultimately accelerate the identification of new therapeutic agents and improve drug safety.
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Simulación del Acoplamiento Molecular , Proteoma , Humanos , Proteoma/química , Proteoma/metabolismo , Benchmarking , Programas Informáticos , Ligandos , Unión Proteica , Conformación ProteicaRESUMEN
Herbicide exposure can pose a considerable threat to non-target aquatic animals. We aimed to study changes in the liver proteome of a model cyprinid fish species, zebrafish Danio rerio, to provide a molecular basis for the adverse effects of environmentally relevant concentrations of glyphosate (100 µg/L), its breakdown product aminomethylphosphonic acid (AMPA; 100 µg/L), and a mixture of both (50 + 50 µg/L) in the presence of humic acid (20 mg/L), which simulated a component of natural organic matter in the aquatic environment. Proteomic analysis was performed by means of high-performance liquid chromatography-tandem mass spectrometry employing a label-free quantification approach. The results present molecular evidence of the stress responses and disturbance of primary metabolic processes such as immune response, dysregulation in DNA repair, necroptosis and apoptosis signaling pathways, oxidative phosphorylation, cholesterol, lipoprotein, and carbohydrate metabolism. We registered the synergistic effect of the glyphosate and AMPA co-exposure, which was expressed in a substantial increase in the number of dysregulated proteins compared to the solo treatments. Humic acid alleviated the effects of glyphosate and its mixture with AMPA and aggravated the impact of AMPA exposure. RuvB-like 2, a protein taking part in DNA repair, and EIF2S1, involved in the regulation of stress-induced gene expression, were downregulated in the liver of zebrafish from all treatments.
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Glicina , Glifosato , Herbicidas , Sustancias Húmicas , Hígado , Proteoma , Pez Cebra , Animales , Pez Cebra/metabolismo , Glicina/análogos & derivados , Glicina/toxicidad , Hígado/efectos de los fármacos , Hígado/metabolismo , Proteoma/metabolismo , Proteoma/efectos de los fármacos , Herbicidas/toxicidad , Organofosfonatos/toxicidad , Contaminantes Químicos del Agua/toxicidadRESUMEN
Whether differences in lifestyle between co-twins are reflected in differences in their internal or external exposome profiles remains largely underexplored. We therefore investigated whether within-pair differences in lifestyle were associated with within-pair differences in exposome profiles across four domains: the external exposome, proteome, metabolome and epigenetic age acceleration (EAA). For each domain, we assessed the similarity of co-twin profiles using Gaussian similarities in up to 257 young adult same-sex twin pairs (54% monozygotic). We additionally tested whether similarity in one domain translated into greater similarity in another. Results suggest that a lower degree of similarity in co-twins' exposome profiles was associated with greater differences in their behavior and substance use. The strongest association was identified between excessive drinking behavior and the external exposome. Overall, our study demonstrates how social behavior and especially substance use are connected to the internal and external exposomes, while controlling for familial confounders.
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Exposoma , Estilo de Vida , Humanos , Femenino , Masculino , Adulto , Adulto Joven , Gemelos Monocigóticos , Metaboloma , Proteoma/metabolismo , Epigénesis GenéticaRESUMEN
Integrating protein quantitative trait loci (pQTL) data and summary statistics from genome-wide association studies (GWAS) of brain image-derived phenotypes (IDPs) can benefit in identifying IDP-related proteins. Here, we developed a systematic omics-integration analytic framework by sequentially using proteome-wide association study (PWAS), Mendelian randomization (MR), and colocalization (COLOC) analyses to identify the potentially causal brain and plasma proteins for IDPs, followed by pleiotropy analysis, mediation analysis, and drug exploration analysis to investigate potential mediation pathways of pleiotropic proteins to neuropsychiatric disorders (NDs) as well as candidate drug targets. A total of 201 plasma proteins and 398 brain proteins were significantly associated with IDPs from PWAS analysis. Subsequent MR and COLOC analyses further identified 313 potentially causal IDP-related proteins, which were significantly enriched in neural-related phenotypes, among which 91 were further identified as pleiotropic proteins associated with both IDPs and NDs, including EGFR, TMEM106B, GPT, and HLA-B. Drug prioritization analysis showed that 6.33% of unique pleiotropic proteins had drug targets or interactions with medications for NDs. Nine potential mediation pathways were identified to illustrate the mediating roles of the IDPs in the causal effect of the pleiotropic proteins on NDs, including the indirect effect of TMEM106B on Alzheimer's disease (AD) risk via radial diffusivity (RD) of the posterior limb of the internal capsule (PLIC), with the mediation proportion being 11.18%, and the indirect effect of EGFR on AD through RD of PLIC, RD of splenium of corpus callosum (SCC), and fractional anisotropy (FA) of SCC, with the mediation proportion being 18.99%, 22.79%, and 19.91%, respectively. These findings provide novel insights into pathogenesis, drug targets, and neuroimaging biomarkers of NDs.
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Biomarcadores , Encéfalo , Estudio de Asociación del Genoma Completo , Trastornos Mentales , Neuroimagen , Sitios de Carácter Cuantitativo , Humanos , Encéfalo/metabolismo , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Neuroimagen/métodos , Trastornos Mentales/metabolismo , Trastornos Mentales/diagnóstico por imagen , Trastornos Mentales/genética , Trastornos Mentales/tratamiento farmacológico , Análisis de la Aleatorización Mendeliana , Proteoma/metabolismo , Proteómica/métodos , Pleiotropía Genética , Fenotipo , MultiómicaRESUMEN
Resistance biomarkers are needed to identify patients with advanced melanoma obtaining a response to ICI treatment and developing resistance later. We searched a combination of molecular signatures of response to ICIs in patients with metastatic melanoma. In a retrospective study on patients with metastatic melanoma treated with an anti-PD-1 agent carried out at Istituto Nazionale Tumori-IRCCS-Fondazione "G. Pascale", Naples, Italy. We integrated a whole proteome profiling of metastatic tissue with targeted transcriptomics. To assess the prognosis of patients according to groups of low and high risk, we used PFS and OS as outcomes. To identify the proteins and mRNAs gene signatures associated with the patient's response groups, the discriminant analysis for sparse data performed via partial least squares procedure was performed. Tissue samples from 22 patients were analyzed. A combined protein and gene signature associated with poorer response to ICI immunotherapy in terms of PFS and OS was identified. The PFS and OS Kaplan-Meier curves were significantly better for patients with high expression of the protein signature compared to patients with low expression of the protein signature and who were high-risk (Protein: HR = 0.023, 95% CI: 0.003-0.213; p < 0.0001. Gene: HR = 0.053, 95% CI: 0.011-0.260; p < 0.0001). The Kaplan-Meier curves showed that patients with low-risk gene signatures had better PFS (HR = 0 0.221, 95% CI: 0.071-0.68; p = 0.007) and OS (HR = 0.186, 95% CI: 0.05-0.695; p = 0.005). The proteomic and transcriptomic combined analysis was significantly associated with the outcomes of the anti-PD-1 treatment with a better predictive value compared to a single signature. All the patients with low expression of protein and gene signatures had progression within 6 months of treatment (median PFS = 3 months, 95% CI: 2-3), with a significant difference vs. the low-risk group (median PFS = not reached; p < 0.0001), and significantly poorer survival (OS = 9 months, 95% CI: 5-9) compared to patients with high expression of protein and gene signatures (median OS = not reached; p < 0.0001). We propose a combined proteomic and transcriptomic signature, including genes involved in pro-tumorigenic pathways, thereby identifying patients with reduced probability of response to immunotherapy with ICIs for metastatic melanoma.
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Inhibidores de Puntos de Control Inmunológico , Melanoma , Proteómica , Transcriptoma , Humanos , Melanoma/tratamiento farmacológico , Melanoma/genética , Melanoma/patología , Melanoma/metabolismo , Melanoma/mortalidad , Femenino , Masculino , Estudios Retrospectivos , Proteómica/métodos , Persona de Mediana Edad , Inhibidores de Puntos de Control Inmunológico/uso terapéutico , Anciano , Pronóstico , Receptor de Muerte Celular Programada 1/antagonistas & inhibidores , Receptor de Muerte Celular Programada 1/metabolismo , Receptor de Muerte Celular Programada 1/genética , Biomarcadores de Tumor/genética , Adulto , Perfilación de la Expresión Génica , Regulación Neoplásica de la Expresión Génica , Proteoma/metabolismo , Neoplasias Cutáneas/tratamiento farmacológico , Neoplasias Cutáneas/genética , Neoplasias Cutáneas/patología , Neoplasias Cutáneas/mortalidad , Neoplasias Cutáneas/metabolismo , Metástasis de la NeoplasiaRESUMEN
PE/PPE proteins secreted by the ESX-5 type VII secretion system constitute a major protein repertoire in pathogenic mycobacteria and are essential for bacterial survival, pathogenicity, and host-pathogen interaction; however, little is known about their expression and secretion. The scarcity of arginine and lysine residues in PE/PPE protein sequences and the high homology of their N-terminal domains limit protein identification using classical trypsin-based proteomic methods. This study used endoproteinase AspN and trypsin to characterize the proteome of Mycobacterium marinum. Twenty-seven PE/PPE proteins were uniquely identified in AspN digests, especially PE_PGRS proteins. These treatments allowed the identification of approximately 50% of the PE/PPE pool encoded in the genome. Moreover, EspG5 pulldown assays retrieved 44 ESX-5-associated PPE proteins, covering 85% of the PPE pool in the identified proteome. The identification of PE/PE_PGRS proteins in the EspG5 interactome suggested the presence of PE-PPE pairs. The correlation analysis between protein abundance and phylogenetic relationships found potential PE/PPE pairs, indicating the presence of multiple PE/PE_PGRS partners in one PPE. We validated that EspG5 interacted with PPE31 and PPE32 and mapped critical residues for complex formation. The modified proteomic platform increases the coverage of PE/PPE proteins and elucidates the expression and localization of these proteins.
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Proteínas Bacterianas , Mycobacterium marinum , Proteoma , Mycobacterium marinum/metabolismo , Mycobacterium marinum/genética , Proteínas Bacterianas/metabolismo , Proteínas Bacterianas/genética , Proteoma/metabolismo , Proteómica/métodos , Filogenia , Sistemas de Secreción Tipo VII/metabolismo , Sistemas de Secreción Tipo VII/genética , Especificidad por SustratoRESUMEN
Proteins are the most common types of biomarkers used in breast cancer (BC) theranostics and management. By definition, a biomarker must be a relevant, objective, stable, and quantifiable biomolecule or other parameter, but proteins are known to exhibit the most variate and profound structural and functional variation. Thus, the proteome is highly dynamic and permanently reshaped and readapted, according to changing microenvironments, to maintain the local cell and tissue homeostasis. It is known that protein posttranslational modifications (PTMs) can affect all aspects of protein function. In this review, we focused our analysis on the different types of PTMs of histological biomarkers in BC. Thus, we analyzed the most common PTMs, including phosphorylation, acetylation, methylation, ubiquitination, SUMOylation, neddylation, palmitoylation, myristoylation, and glycosylation/sialylation/fucosylation of transcription factors, proliferation marker Ki-67, plasma membrane proteins, and histone modifications. Most of these PTMs occur in the presence of cellular stress. We emphasized that these PTMs interfere with these biomarkers maintenance, turnover and lifespan, nuclear or subcellular localization, structure and function, stabilization or inactivation, initiation or silencing of genomic and non-genomic pathways, including transcriptional activities or signaling pathways, mitosis, proteostasis, cell-cell and cell-extracellular matrix (ECM) interactions, membrane trafficking, and PPIs. Moreover, PTMs of these biomarkers orchestrate all hallmark pathways that are dysregulated in BC, playing both pro- and/or antitumoral and context-specific roles in DNA damage, repair and genomic stability, inactivation/activation of tumor-suppressor genes and oncogenes, phenotypic plasticity, epigenetic regulation of gene expression and non-mutational reprogramming, proliferative signaling, endocytosis, cell death, dysregulated TME, invasion and metastasis, including epithelial-mesenchymal/mesenchymal-epithelial transition (EMT/MET), and resistance to therapy or reversal of multidrug therapy resistance. PTMs occur in the nucleus but also at the plasma membrane and cytoplasmic level and induce biomarker translocation with opposite effects. Analysis of protein PTMs allows for the discovery and validation of new biomarkers in BC, mainly for early diagnosis, like extracellular vesicle glycosylation, which may be considered as a potential source of circulating cancer biomarkers.
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Biomarcadores de Tumor , Neoplasias de la Mama , Procesamiento Proteico-Postraduccional , Humanos , Neoplasias de la Mama/metabolismo , Neoplasias de la Mama/patología , Neoplasias de la Mama/genética , Biomarcadores de Tumor/metabolismo , Femenino , Proteoma/metabolismoRESUMEN
Druggable pockets are protein regions that have the ability to bind organic small molecules, and their characterization is essential in target-based drug discovery. However, deriving pocket descriptors is challenging and existing strategies are often limited in applicability. We introduce PocketVec, an approach to generate pocket descriptors via inverse virtual screening of lead-like molecules. PocketVec performs comparably to leading methodologies while addressing key limitations. Additionally, we systematically search for druggable pockets in the human proteome, using experimentally determined structures and AlphaFold2 models, identifying over 32,000 binding sites across 20,000 protein domains. We then generate PocketVec descriptors for each site and conduct an extensive similarity search, exploring over 1.2 billion pairwise comparisons. Our results reveal druggable pocket similarities not detected by structure- or sequence-based methods, uncovering clusters of similar pockets in proteins lacking crystallized inhibitors and opening the door to strategies for prioritizing chemical probe development to explore the druggable space.
Asunto(s)
Descubrimiento de Drogas , Proteínas , Humanos , Sitios de Unión , Descubrimiento de Drogas/métodos , Proteínas/metabolismo , Proteínas/química , Unión Proteica , Proteoma/metabolismo , Modelos Moleculares , LigandosRESUMEN
BACKGROUND: Foxn1-/- deficient mice are a rare model of regenerative skin wound healing among mammals. In wounded skin, the transcription factor Foxn1 interacting with hypoxia-regulated factors affects re-epithelialization, epithelial-mesenchymal transition (EMT) and dermal white adipose tissue (dWAT) reestablishment and is thus a factor regulating scar-forming/reparative healing. Here, we hypothesized that transcriptional crosstalk between Foxn1 and Hif-1α controls the switch from scarless (regenerative) to scar-present (reparative) skin wound healing. To verify this hypothesis, we examined (i) the effect of hypoxia/normoxia and Foxn1 signalling on the proteomic signature of Foxn1-/- (regenerative) dermal fibroblasts (DFs) and then (ii) explored the effect of Hif-1α or Foxn1/Hif-1α introduced by a lentiviral (LV) delivery vector to injured skin of regenerative Foxn1-/- mice with particular attention to the remodelling phase of healing. RESULTS: We showed that hypoxic conditions and Foxn1 stimulation modified the proteome of Foxn1-/- DFs. Hypoxic conditions upregulated DF protein profiles, particularly those related to extracellular matrix (ECM) composition: plasminogen activator inhibitor-1 (Pai-1), Sdc4, Plod2, Plod1, Lox, Loxl2, Itga2, Vldlr, Ftl1, Vegfa, Hmox1, Fth1, and F3. We found that Pai-1 was stimulated by hypoxic conditions in regenerative Foxn1-/- DFs but was released by DFs to the culture media exclusively upon hypoxia and Foxn1 stimulation. We also found higher levels of Pai-1 protein in DFs isolated from Foxn1+/+ mice (reparative/scar-forming) than in DFs isolated from Foxn1-/- (regenerative/scarless) mice and triggered by injury increase in Foxn1 and Pai-1 protein in the skin of mice with active Foxn1 (Foxn1+/+ mice). Then, we demonstrated that the introduction of Foxn1 and Hif-1α via lentiviral injection into the wounded skin of regenerative Foxn1-/- mice activates reparative/scar-forming healing by increasing the wounded skin area and decreasing hyaluronic acid deposition and the collagen type III to I ratio. We also identified a stimulatory effect of LV-Foxn1 + LV-Hif-1α injection in the wounded skin of Foxn1-/- mice on Pai-1 protein levels. CONCLUSIONS: The present data highlight the effect of hypoxia and Foxn1 on the protein profile and functionality of regenerative Foxn1-/- DFs and demonstrate that the introduction of Foxn1 and Hif-1α into the wounded skin of regenerative Foxn1-/- mice activates reparative/scar-forming healing.
Asunto(s)
Cicatriz , Fibroblastos , Factores de Transcripción Forkhead , Cicatrización de Heridas , Animales , Cicatrización de Heridas/fisiología , Cicatrización de Heridas/genética , Fibroblastos/metabolismo , Ratones , Factores de Transcripción Forkhead/metabolismo , Factores de Transcripción Forkhead/genética , Cicatriz/metabolismo , Piel/metabolismo , Piel/lesiones , Ratones Noqueados , Proteoma/metabolismo , Subunidad alfa del Factor 1 Inducible por Hipoxia/metabolismo , Subunidad alfa del Factor 1 Inducible por Hipoxia/genética , Proteómica/métodos , Hipoxia/metabolismoRESUMEN
BACKGROUND: Camellia nitidissima is a rare, prized camellia species with golden-yellow flowers. It has a high ornamental, medicinal, and economic value. Previous studies have shown substantial flavonol accumulation in C. nitidissima petals during flower formation. However, the mechanisms underlying the golden flower formation in C. nitidissima remain largely unknown. RESULTS: We performed an integrative analysis of the transcriptome, proteome, and metabolome of the petals at five flower developmental stages to construct the regulatory network underlying golden flower formation in C. nitidissima. Metabolome analysis revealed the presence of 323 flavonoids, and two flavonols, quercetin glycosides and kaempferol glycosides, were highly accumulated in the golden petals. Transcriptome and proteome sequencing suggested that the flavonol biosynthesis-related genes and proteins upregulated and the anthocyanin and proanthocyanidin biosynthesis-related genes and proteins downregulated in the golden petal stage. Further investigation revealed the involvement of MYBs and bHLHs in flavonoid biosynthesis. Expression analysis showed that flavonol synthase 2 (CnFLS2) was highly expressed in the petals, and its expression positively correlated with flavonol content at all flower developmental stages. Transient overexpression of CnFLS2 in the petals increased flavonol content. Furthermore, correlation analysis showed that the jasmonate (JA) pathways positively correlated with flavonol biosynthesis, and exogenous methyl jasmonate (MeJA) treatment promoted CnFLS2 expression and flavonol accumulation. CONCLUSIONS: Our findings showed that the JA-CnFLS2 module regulates flavonol biosynthesis during golden petal formation in C. nitidissima.