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Journal of Genetics and Genomics = Yi... Mar 2024Protein post-translational modifications (PTMs), such as ubiquitination, phosphorylation, and small ubiquitin-like modifier (SUMO)ylation, are crucial for regulating...
Protein post-translational modifications (PTMs), such as ubiquitination, phosphorylation, and small ubiquitin-like modifier (SUMO)ylation, are crucial for regulating protein stability, activity, subcellular localization, and binding with cofactors. Such modifications remarkably increase the variety and complexity of proteomes, which are essential for regulating numerous cellular and physiological processes. The regulation of auxin signaling is finely tuned in time and space to guide various plant growth and development. Accumulating evidence indicates that PTMs play critical roles in auxin signaling regulations. Thus, a thorough and systematic review of the functions of PTMs in auxin signal transduction will improve our profound comprehension of the regulation mechanism of auxin signaling and auxin-mediated various processes. This review discusses the progress of protein ubiquitination, phosphorylation, histone acetylation and methylation, SUMOylation, and S-nitrosylation in the regulation of auxin signaling.
Topics: Indoleacetic Acids; Protein Processing, Post-Translational; Signal Transduction; Sumoylation; Ubiquitination
PubMed: 37451336
DOI: 10.1016/j.jgg.2023.07.002 -
Frontiers in Endocrinology 2023Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity....
INTRODUCTION
Polycystic Ovarian Syndrome (PCOS) is the most common endocrinopathy in women of reproductive age and remains widely underdiagnosed leading to significant morbidity. Artificial intelligence (AI) and machine learning (ML) hold promise in improving diagnostics. Thus, we performed a systematic review of literature to identify the utility of AI/ML in the diagnosis or classification of PCOS.
METHODS
We applied a search strategy using the following databases MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Web of Science, and the IEEE Xplore Digital Library using relevant keywords. Eligible studies were identified, and results were extracted for their synthesis from inception until January 1, 2022.
RESULTS
135 studies were screened and ultimately, 31 studies were included in this study. Data sources used by the AI/ML interventions included clinical data, electronic health records, and genetic and proteomic data. Ten studies (32%) employed standardized criteria (NIH, Rotterdam, or Revised International PCOS classification), while 17 (55%) used clinical information with/without imaging. The most common AI techniques employed were support vector machine (42% studies), K-nearest neighbor (26%), and regression models (23%) were the commonest AI/ML. Receiver operating curves (ROC) were employed to compare AI/ML with clinical diagnosis. Area under the ROC ranged from 73% to 100% (n=7 studies), diagnostic accuracy from 89% to 100% (n=4 studies), sensitivity from 41% to 100% (n=10 studies), specificity from 75% to 100% (n=10 studies), positive predictive value (PPV) from 68% to 95% (n=4 studies), and negative predictive value (NPV) from 94% to 99% (n=2 studies).
CONCLUSION
Artificial intelligence and machine learning provide a high diagnostic and classification performance in detecting PCOS, thereby providing an avenue for early diagnosis of this disorder. However, AI-based studies should use standardized PCOS diagnostic criteria to enhance the clinical applicability of AI/ML in PCOS and improve adherence to methodological and reporting guidelines for maximum diagnostic utility.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/prospero/, identifier CRD42022295287.
Topics: Female; Humans; Artificial Intelligence; Polycystic Ovary Syndrome; Proteomics; Machine Learning; Cluster Analysis
PubMed: 37790605
DOI: 10.3389/fendo.2023.1106625 -
Molecular & Cellular Proteomics : MCP Aug 2023Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of...
Osteoarthritis (OA) is the most prevalent rheumatic pathology. However, OA is not simply a process of wear and tear affecting articular cartilage but rather a disease of the entire joint. One of the most common locations of OA is the knee. Knee tissues have been studied using molecular strategies, generating a large amount of complex data. As one of the goals of the Rheumatic and Autoimmune Diseases initiative of the Human Proteome Project, we applied a text-mining strategy to publicly available literature to collect relevant information and generate a systematically organized overview of the proteins most closely related to the different knee components. To this end, the PubPular literature-mining software was employed to identify protein-topic relationships and extract the most frequently cited proteins associated with the different knee joint components and OA. The text-mining approach searched over eight million articles in PubMed up to November 2022. Proteins associated with the six most representative knee components (articular cartilage, subchondral bone, synovial membrane, synovial fluid, meniscus, and cruciate ligament) were retrieved and ranked by their relevance to the tissue and OA. Gene ontology analyses showed the biological functions of these proteins. This study provided a systematic and prioritized description of knee-component proteins most frequently cited as associated with OA. The study also explored the relationship of these proteins to OA and identified the processes most relevant to proper knee function and OA pathophysiology.
Topics: Humans; Cartilage, Articular; Knee Joint; Osteoarthritis, Knee
PubMed: 37356495
DOI: 10.1016/j.mcpro.2023.100606 -
Nature Communications Sep 2023COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be... (Meta-Analysis)
Meta-Analysis
COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community.
Topics: Humans; COVID-19; Proteome; Proteomics; SARS-CoV-2; Cytoplasm
PubMed: 37739942
DOI: 10.1038/s41467-023-41159-z -
Frontiers in Oral Health 2023Some salivary proteins seem to be differently abundant among caries-free (CF) and caries-affected (CA) individuals, but previous results are contradictory precluding... (Review)
Review
OBJECTIVE
Some salivary proteins seem to be differently abundant among caries-free (CF) and caries-affected (CA) individuals, but previous results are contradictory precluding that definitive conclusion be drawn. A pooled analysis of the available evidence may provide more robust data on identifying oral cavity protein patterns among CF and CA individuals. This systematic review and meta-analysis (PROSPERO CRD42021269079) aimed to compare the oral cavity protein abundance among caries-free and caries-affected individuals.
METHODS
This study was conducted following PRISMA guidelines. PubMed, Embase, and Web of Science databases were systematically assessed (up to February 2023) to retrieve clinical studies written in English, German, or in Latin-based languages that compared the oral cavity protein abundance among CF and CA individuals. Data extraction and methodological quality assessment (NIH guidelines) were independently performed by two investigators. Qualitative synthesis was performed from all included studies and meta-analysis was performed using a random-effects model with inverse variance for studies that reported the concentration of proteins or enzymatic activity. Standardized mean difference (SMD) with respective 95% confidence interval (CI) were calculated for each outcome.
RESULTS
A total of 90 studies (two cohort and 88 cross-sectional designs) of more than 6,000 participants were selected for data extraction, being the quality of evidence graded as "fair" for most of them. The oral cavity of CF individuals presented lower total protein concentration [SMD = 0.37 (95% CI: 0.07-0.68; 18 studies)], lower total antioxidant capacity [SMD = 1.29 (95% CI: 0.74-1.85); 17 studies], and lower carbonic anhydrase activity [SMD = 0.83 (95% CI: 0.58-1.09); three studies], whereas CA individuals presented lower carbonic anhydrase concentration [SMD = -0.66 (95% CI: -1.00 to -0.32); three studies], urease [SMD = -0.95 (IC 95%: -1.72 to -0.17); four studies], and arginine deiminase system [SMD = -2.07 (95% CI: -3.53 to -0.62); three studies] activities. Antimicrobial peptides, secretory immunoglobulin-A concentrations and alpha-amylase activity were similar among individuals.
CONCLUSION
Differences on oral cavity protein abundance were observed among CF and CA individuals. These data indicate some protein patterns for the oral health and dental caries conditions. Even when statistically significant, some of the results were not very consistent. Cohort studies need to be conducted to validate these results.
PubMed: 37780687
DOI: 10.3389/froh.2023.1265817 -
Biomolecules Nov 2023Mitochondria are ancient endosymbiotic double membrane organelles that support a wide range of eukaryotic cell functions through energy, metabolism, and cellular... (Review)
Review
Mitochondria are ancient endosymbiotic double membrane organelles that support a wide range of eukaryotic cell functions through energy, metabolism, and cellular control. There are over 1000 known proteins that either reside within the mitochondria or are transiently associated with it. These mitochondrial proteins represent a functional subcellular protein network (mtProteome) that is encoded by mitochondrial and nuclear genomes and significantly varies between cell types and conditions. In neurons, the high metabolic demand and differential energy requirements at the synapses are met by specific modifications to the mtProteome, resulting in alterations in the expression and functional properties of the proteins involved in energy production and quality control, including fission and fusion. The composition of mtProteomes also impacts the localization of mitochondria in axons and dendrites with a growing number of neurodegenerative diseases associated with changes in mitochondrial proteins. This review summarizes the findings on the composition and properties of mtProteomes important for mitochondrial energy production, calcium and lipid signaling, and quality control in neural cells. We highlight strategies in mass spectrometry (MS) proteomic analysis of mtProteomes from cultured cells and tissue. The research into mtProteome composition and function provides opportunities in biomarker discovery and drug development for the treatment of metabolic and neurodegenerative disease.
Topics: Humans; Proteome; Neurodegenerative Diseases; Proteomics; Mitochondria; Neurons; Mitochondrial Proteins
PubMed: 38002320
DOI: 10.3390/biom13111638 -
Cancers Oct 2023The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to... (Review)
Review
The accurate diagnosis of small-cell lung cancer (SCLC) is crucial, as treatment strategies differ from those of other lung cancers. This systematic review aims to identify proteins differentially expressed in SCLC compared to normal lung tissue, evaluating their potential utility in diagnosing and prognosing the disease. Additionally, the study identifies proteins differentially expressed between SCLC and large cell neuroendocrine carcinoma (LCNEC), aiming to discover biomarkers distinguishing between these two subtypes of neuroendocrine lung cancers. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted across PubMed/MEDLINE, Scopus, Embase, and Web of Science databases. Studies reporting proteomics information and confirming SCLC and/or LCNEC through histopathological and/or cytopathological examination were included, while review articles, non-original articles, and studies based on animal samples or cell lines were excluded. The initial search yielded 1705 articles, and after deduplication and screening, 16 articles were deemed eligible. These studies revealed 117 unique proteins significantly differentially expressed in SCLC compared to normal lung tissue, along with 37 unique proteins differentially expressed between SCLC and LCNEC. In conclusion, this review highlights the potential of proteomics technology in identifying novel biomarkers for diagnosing SCLC, predicting its prognosis, and distinguishing it from LCNEC.
PubMed: 37894372
DOI: 10.3390/cancers15205005 -
Frontiers in Immunology 2024Anaphylaxis manifests as a severe immediate-type hypersensitivity reaction initiated through the immunological activation of target B-cells by allergens, leading to the... (Meta-Analysis)
Meta-Analysis
BACKGROUND
Anaphylaxis manifests as a severe immediate-type hypersensitivity reaction initiated through the immunological activation of target B-cells by allergens, leading to the release of mediators. However, the well-known underlying pathological mechanisms do not fully explain the whole variety of clinical and immunological presentations. We performed a systemic review of proteomic and metabolomic studies and analyzed the extracted data to improve our understanding and identify potential new biomarkers of anaphylaxis.
METHODS
Proteomic and metabolomic studies in both human subjects and experimental models were extracted and selected through a systematic search conducted on databases such as PubMed, Scopus, and Web of Science, up to May 2023.
RESULTS
Of 137 retrieved publications, we considered 12 for further analysis, including seven on proteome analysis and five on metabolome analysis. A meta-analysis of the four human studies identified 118 proteins with varying expression levels in at least two studies. Beside established pathways of mast cells and basophil activation, functional analysis of proteomic data revealed a significant enrichment of biological processes related to neutrophil activation and platelet degranulation and metabolic pathways of arachidonic acid and icosatetraenoic acid. The pathway analysis highlighted also the involvement of neutrophil degranulation, and platelet activation. Metabolome analysis across different models showed 13 common metabolites, including arachidonic acid, tryptophan and lysoPC(18:0) lysophosphatidylcholines.
CONCLUSION
Our review highlights the underestimated role of neutrophils and platelets in the pathological mechanisms of anaphylactic reactions. These findings, derived from a limited number of publications, necessitate confirmation through human studies with larger sample sizes and could contribute to the development of new biomarkers for anaphylaxis.
SYSTEMATIC REVIEW REGISTRATION
https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42024506246.
Topics: Humans; Anaphylaxis; Arachidonic Acid; Proteomics; Allergens; Biomarkers
PubMed: 38384462
DOI: 10.3389/fimmu.2024.1328212 -
La Clinica Terapeutica 2023Cancer, a potentially fatal condition, is one of the leading causes of death worldwide. Among males aged 20 to 35, the most common cancer in healthy individuals is... (Review)
Review
BACKGROUND
Cancer, a potentially fatal condition, is one of the leading causes of death worldwide. Among males aged 20 to 35, the most common cancer in healthy individuals is testicular cancer, accounting for 1% to 2% of all cancers in men.
METHODS
Throughout this review, we have employed a targeted research approach, carefully handpicking the most representative and relevant articles on the subject. Our methodology involved a systematic review of the scientific literature to ensure a comprehensive and accurate overview of the available sources.
RESULTS
The onset and spread of testicular cancer are significantly influenced by genetic changes, including mutations in oncogenes, tu-mor suppressor genes, and DNA repair genes. As a result of identifying these specific genetic mutations in cancers, targeted medications have been developed to disrupt the signaling pathways affected by these genetic changes. To improve the diagnosis and treatment of this disease, it is crucial to understand its natural and clinical histories.
CONCLUSIONS
In order to comprehend cancer better and to discover new biomarkers and therapeutic targets, oncologists are increasingly employing omics methods, such as genomics, transcriptomics, proteomics, and metabolomics. Targeted medications that focus on specific genetic pathways and mutations hold promise for advancing the diagnosis and management of this disease.
Topics: Humans; Male; Testicular Neoplasms; Precision Medicine; Genomics; Proteomics
PubMed: 37994745
DOI: 10.7417/CT.2023.2468 -
International Journal of Molecular... Sep 2023Periodontitis is one of the primary causes of tooth loss, and is also related to various systemic diseases. Early detection of this condition is crucial when it comes to... (Meta-Analysis)
Meta-Analysis Review
Periodontitis is one of the primary causes of tooth loss, and is also related to various systemic diseases. Early detection of this condition is crucial when it comes to preventing further oral damage and the associated health complications. This study offers a systematic review of the literature published up to April 2023, and aims to clearly explain the role of proteomics in identifying salivary biomarkers for periodontitis. Comprehensive searches were conducted on PubMed and Web of Science to shortlist pertinent studies. The inclusion criterion was those that reported on mass spectrometry-driven proteomic analyses of saliva samples from periodontitis cohorts, while those on gingivitis or other oral diseases were excluded. An assessment for risk of bias was carried out using the Newcastle-Ottawa Scale and Quality Assessment of Diagnostic Accuracy Studies or the NIH quality assessment tool, and a meta-analysis was performed for replicable candidate biomarkers, i.e., consistently reported candidate biomarkers (in specific saliva samples, and periodontitis subgroups, reported in ≥2 independent cohorts/reports) were identified. A Gene Ontology enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery bioinformatics resources, which consistently expressed candidate biomarkers, to explore the predominant pathway wherein salivary biomarkers consistently manifested. Of the 15 studies included, 13 were case-control studies targeting diagnostic biomarkers for periodontitis participants (periodontally healthy/diseased, = 342/432), while two focused on biomarkers responsive to periodontal treatment ( = 26 participants). The case-control studies were considered to have a low risk of bias, while the periodontitis treatment studies were deemed fair. Summary estimate and confidence/credible interval, etc. determination for the identified putative salivary biomarkers could not be ascertained due to the low number of studies in each case. The results from the included case-control studies identified nine consistently expressed candidate biomarkers (from nine studies with 230/297 periodontally healthy/diseased participants): (i) those that were upregulated: alpha-amylase, serum albumin, complement C3, neutrophil defensin, profilin-1, and S100-P; and (ii) those that were downregulated: carbonic anhydrase 6, immunoglobulin J chain, and lactoferrin. All putative biomarkers exhibited consistent regulation patterns. The implications of the current putative marker proteins identified were reviewed, with a focus on their potential roles in periodontitis diagnosis and pathogenesis, and as putative therapeutic targets. Although in its early stages, mass spectrometry-based salivary periodontal disease biomarker proteomics detection appeared promising. More mass spectrometry-based proteomics studies, with or without the aid of already available clinical biochemical approaches, are warranted to aid the discovery, identification, and validation of periodontal health/disease indicator molecule(s). Protocol registration number: CRD42023447722; supported by RD-02-202410 and GRF17119917.
Topics: Humans; Proteomics; Periodontitis; Mass Spectrometry; Biomarkers; Proteins; Periodontal Diseases; Saliva
PubMed: 37834046
DOI: 10.3390/ijms241914599