Proteomes

15 pages, 862 KiB

Open AccessReview

Multi-Omic Approaches in Cancer-Related Micropeptide Identification

by Katarina Vrbnjak and Raj Nayan Sewduth

Proteomes 2024, 12(3), 26; https://doi.org/10.3390/proteomes12030026 - 13 Sep 2024

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Despite the advances in modern cancer therapy, malignant diseases are still a leading cause of morbidity and mortality worldwide. Conventional treatment methods frequently lead to side effects and drug resistance in patients, highlighting the need for novel therapeutic approaches. Recent findings have identified [...] Read more.

Despite the advances in modern cancer therapy, malignant diseases are still a leading cause of morbidity and mortality worldwide. Conventional treatment methods frequently lead to side effects and drug resistance in patients, highlighting the need for novel therapeutic approaches. Recent findings have identified the existence of non-canonical micropeptides, an additional layer of the proteome complexity, also called the microproteome. These small peptides are a promising class of therapeutic agents with the potential to address the limitations of current cancer treatments. The microproteome is encoded by regions of the genome historically annotated as non-coding, and its existence has been revealed thanks to recent advances in proteomic and bioinformatic technology, which dramatically improved the understanding of proteome complexity. Micropeptides have been shown to be biologically active in several cancer types, indicating their therapeutic role. Furthermore, they are characterized by low toxicity and high target specificity, demonstrating their potential for the development of better tolerated drugs. In this review, we survey the current landscape of known micropeptides with a role in cancer progression or treatment, discuss their potential as anticancer agents, and describe the methodological challenges facing the proteome field of research. Full article

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30 pages, 1134 KiB

Open AccessReview

Transforming Clinical Research: The Power of High-Throughput Omics Integration

by Rui Vitorino

Proteomes 2024, 12(3), 25; https://doi.org/10.3390/proteomes12030025 - 6 Sep 2024

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Abstract

High-throughput omics technologies have dramatically changed biological research, providing unprecedented insights into the complexity of living systems. This review presents a comprehensive examination of the current landscape of high-throughput omics pipelines, covering key technologies, data integration techniques and their diverse applications. It looks [...] Read more.

High-throughput omics technologies have dramatically changed biological research, providing unprecedented insights into the complexity of living systems. This review presents a comprehensive examination of the current landscape of high-throughput omics pipelines, covering key technologies, data integration techniques and their diverse applications. It looks at advances in next-generation sequencing, mass spectrometry and microarray platforms and highlights their contribution to data volume and precision. In addition, this review looks at the critical role of bioinformatics tools and statistical methods in managing the large datasets generated by these technologies. By integrating multi-omics data, researchers can gain a holistic understanding of biological systems, leading to the identification of new biomarkers and therapeutic targets, particularly in complex diseases such as cancer. The review also looks at the integration of omics data into electronic health records (EHRs) and the potential for cloud computing and big data analytics to improve data storage, analysis and sharing. Despite significant advances, there are still challenges such as data complexity, technical limitations and ethical issues. Future directions include the development of more sophisticated computational tools and the application of advanced machine learning techniques, which are critical for addressing the complexity and heterogeneity of omics datasets. This review aims to serve as a valuable resource for researchers and practitioners, highlighting the transformative potential of high-throughput omics technologies in advancing personalized medicine and improving clinical outcomes. Full article

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12 pages, 879 KiB

Open AccessArticle

Investigating the Prognostic Potential of Plasma ST2 in Patients with Peripheral Artery Disease: Identification and Evaluation

by Ben Li, Farah Shaikh, Abdelrahman Zamzam, Rawand Abdin and Mohammad Qadura

Proteomes 2024, 12(3), 24; https://doi.org/10.3390/proteomes12030024 - 29 Aug 2024

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Abstract

Soluble interleukin 1 receptor-like 1 (ST2) is a circulating protein demonstrated to be associated with cardiovascular diseases; however, it has not been studied as a biomarker for peripheral artery disease (PAD). Using a prospectively recruited cohort of 476 patients (312 with PAD and [...] Read more.

Soluble interleukin 1 receptor-like 1 (ST2) is a circulating protein demonstrated to be associated with cardiovascular diseases; however, it has not been studied as a biomarker for peripheral artery disease (PAD). Using a prospectively recruited cohort of 476 patients (312 with PAD and 164 without PAD), we conducted a prognostic study of PAD using clinical/biomarker data. Plasma concentrations of three circulating proteins [ST2, cytokine-responsive gene-2 (CRG-2), vascular endothelial growth factor (VEGF)] were measured at baseline and the cohort was followed for 2 years. The outcome of interest was a 2-year major adverse limb event (MALE; composite of major amputation, vascular intervention, or acute limb ischemia). Using 10-fold cross-validation, a random forest model was trained using clinical characteristics and plasma ST2 levels. The primary model evaluation metric was the F1 score. Out of the three circulating proteins analyzed, ST2 was the only one that was statistically significantly higher in individuals with PAD compared to patients without PAD (mean concentration in plasma of 9.57 [SD 5.86] vs. 11.39 [SD 6.43] pg/mL, p < 0.001). Over a 2-year period, 28 (9%) patients with PAD experienced MALE. Our predictive model, incorporating clinical features and plasma ST2 levels, achieved an F1 score of 0.713 for forecasting 2-year MALE outcomes. Patients identified as high-risk by this model showed a significantly increased likelihood of developing MALE (HR 1.06, 95% CI 1.02–1.13, p = 0.003). By combining clinical characteristics and plasma ST2 levels, our proposed predictive model offers accurate risk assessment for 2-year MALE in PAD patients. This algorithm supports risk stratification in PAD, guiding clinical decisions regarding further vascular evaluation, specialist referrals, and appropriate medical or surgical interventions, thereby potentially enhancing patient outcomes. Full article

(This article belongs to the Section Identification of Potential Biomarkers and Potential Therapeutic Targets)

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31 pages, 1404 KiB

Open AccessReview

The Current Molecular and Cellular Landscape of Chronic Obstructive Pulmonary Disease (COPD): A Review of Therapies and Efforts towards Personalized Treatment

by Luke A. Farrell, Matthew B. O’Rourke, Matthew P. Padula, Fernando Souza-Fonseca-Guimaraes, Gaetano Caramori, Peter A. B. Wark, Shymali C. Dharmage and Phillip M. Hansbro

Proteomes 2024, 12(3), 23; https://doi.org/10.3390/proteomes12030023 - 16 Aug 2024

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Abstract

Chronic obstructive pulmonary disease (COPD) ranks as the third leading cause of global illness and mortality. It is commonly triggered by exposure to respiratory irritants like cigarette smoke or biofuel pollutants. This multifaceted condition manifests through an array of symptoms and lung irregularities, [...] Read more.

Chronic obstructive pulmonary disease (COPD) ranks as the third leading cause of global illness and mortality. It is commonly triggered by exposure to respiratory irritants like cigarette smoke or biofuel pollutants. This multifaceted condition manifests through an array of symptoms and lung irregularities, characterized by chronic inflammation and reduced lung function. Present therapies primarily rely on maintenance medications to alleviate symptoms, but fall short in impeding disease advancement. COPD’s diverse nature, influenced by various phenotypes, complicates diagnosis, necessitating precise molecular characterization. Omics-driven methodologies, including biomarker identification and therapeutic target exploration, offer a promising avenue for addressing COPD’s complexity. This analysis underscores the critical necessity of improving molecular profiling to deepen our comprehension of COPD and identify potential therapeutic targets. Moreover, it advocates for tailoring treatment strategies to individual phenotypes. Through comprehensive exploration-based molecular characterization and the adoption of personalized methodologies, innovative treatments may emerge that are capable of altering the trajectory of COPD, instilling optimism for efficacious disease-modifying interventions. Full article

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17 pages, 2636 KiB

Open AccessArticle

The Low-Abundance Plasma Proteome Reveals Differentially Abundant Proteins Associated with Breast Implant Capsular Contracture: A Pilot Study

by Md. Arifur Rahman, Ardeshir Amirkhani, Maria Mempin, Seong Beom Ahn, Anand K. Deva, Mark S. Baker, Karen Vickery and Honghua Hu

Proteomes 2024, 12(3), 22; https://doi.org/10.3390/proteomes12030022 - 6 Aug 2024

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Abstract

Capsular contracture (CC) is one of the most common postoperative complications associated with breast implant-associated infections. The mechanisms that lead to CC remain poorly understood. Plasma is an ideal biospecimen for early proteomics biomarker discovery. However, as high-abundance proteins mask signals from low-abundance [...] Read more.

Capsular contracture (CC) is one of the most common postoperative complications associated with breast implant-associated infections. The mechanisms that lead to CC remain poorly understood. Plasma is an ideal biospecimen for early proteomics biomarker discovery. However, as high-abundance proteins mask signals from low-abundance proteins, identifying novel or specific proteins as biomarkers for a particular disease has been hampered. Here, we employed depletion of high-abundance plasma proteins followed by Tandem Mass Tag (TMT)-based quantitative proteomics to compare 10 healthy control patients against 10 breast implant CC patients. A total of 450 proteins were identified from these samples. Among them, 16 proteins were significantly differentially expressed in which 5 proteins were upregulated and 11 downregulated in breast implant CC patients compared to healthy controls. Gene Ontology enrichment analysis revealed that proteins related to cell, cellular processes and catalytic activity were highest in the cellular component, biological process, and molecular function categories, respectively. Further, pathway analysis revealed that inflammatory responses, focal adhesion, platelet activation, and complement and coagulation cascades were enriched pathways. The differentially abundant proteins from TMT-based quantitative proteomics have the potential to provide important information for future mechanistic studies and in the development of breast implant CC biomarkers. Full article

(This article belongs to the Section Identification of Potential Biomarkers and Potential Therapeutic Targets)

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8 pages, 718 KiB

Open AccessArticle

Quantitative Analysis of Complement Membrane Attack Complex Proteins Associated with Extracellular Vesicles

by Illarion V. Turko

Proteomes 2024, 12(3), 21; https://doi.org/10.3390/proteomes12030021 - 12 Jul 2024

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Abstract

Extracellular vesicles (EVs) represent a universal mechanism of intercellular communication in normal and pathological conditions. There are reports showing the presence of complement proteins in EV preparations, specifically those that can form a membrane attack complex (MAC). In the present work, we have [...] Read more.

Extracellular vesicles (EVs) represent a universal mechanism of intercellular communication in normal and pathological conditions. There are reports showing the presence of complement proteins in EV preparations, specifically those that can form a membrane attack complex (MAC). In the present work, we have used a quantitative mass spectrometry method that allows for the measurement of multiple targeted proteins in one experimental run. The quantification of MAC-forming proteins, namely C5b, C6, C7, C8, and C9, in highly purified EVs from normal human plasma revealed the presence of MAC proteins at approximately equal stoichiometry that does not fit the expected stoichiometry of preformed MAC. We concluded that while MAC proteins can be associated with EVs from normal plasma and presumably can be delivered to the recipient cells, there is no evidence that the EVs carry preformed MAC. Full article

(This article belongs to the Section Extracellular Vesicles)

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17 pages, 6479 KiB

Open AccessArticle

Seasonal Proteome Variations in Orbicella faveolata Reveal Molecular Thermal Stress Adaptations

by Martha Ricaurte, Nikolaos V. Schizas, Ernesto F. Weil, Pawel Ciborowski and Nawal M. Boukli

Proteomes 2024, 12(3), 20; https://doi.org/10.3390/proteomes12030020 - 10 Jul 2024

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Abstract

Although seasonal water temperatures typically fluctuate by less than 4 °C across most tropical reefs, sustained heat stress with an increase of even 1 °C can alter and destabilize metabolic and physiological coral functions, leading to losses of coral reefs worldwide. The Caribbean [...] Read more.

Although seasonal water temperatures typically fluctuate by less than 4 °C across most tropical reefs, sustained heat stress with an increase of even 1 °C can alter and destabilize metabolic and physiological coral functions, leading to losses of coral reefs worldwide. The Caribbean region provides a natural experimental design to study how corals respond physiologically throughout the year. While characterized by warm temperatures and precipitation, there is a significant seasonal component with relative cooler and drier conditions during the months of January to February and warmer and wetter conditions during September and October. We conducted a comparative abundance of differentially expressed proteins with two contrasting temperatures during the cold and warm seasons of 2014 and 2015 in Orbicella faveolata, one of the most important and affected reef-building corals of the Caribbean. All presented proteoforms (42) were found to be significant in our proteomics differential expression analysis and classified based on their gene ontology. The results were accomplished by a combination of two-dimensional gel electrophoresis (2DE) to separate and visualize proteins and mass spectrometry (MS) for protein identification. To validate the differentially expressed proteins of Orbicella faveolata at the transcription level, qRT-PCR was performed. Our data indicated that a 3.1 °C increase in temperature in O. faveolata between the cold and warm seasons in San Cristobal and Enrique reefs of southwestern Puerto Rico was enough to affect the expression of a significant number of proteins associated with oxidative and heat stress responses, metabolism, immunity, and apoptosis. This research extends our knowledge into the mechanistic response of O. faveolata to mitigate thermal seasonal temperature variations in coral reefs. Full article

(This article belongs to the Section Proteoform Analysis (Top-Down and Bottom-Up))

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1 pages, 131 KiB

Open AccessCorrection

Correction: Jain et al. Proteomic Approach for Comparative Analysis of the Spike Protein of SARS-CoV-2 Omicron (B.1.1.529) Variant and Other Pango Lineages. Proteomes 2022, 10, 34

by Mukul Jain, Nil Patil, Darshil Gor, Mohit Kumar Sharma, Neha Goel and Prashant Kaushik

Proteomes 2024, 12(3), 19; https://doi.org/10.3390/proteomes12030019 - 9 Jul 2024

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Abstract

In the publication [...] Full article

20 pages, 6013 KiB

Open AccessArticle

Investigating and Annotating the Human Peptidome Profile from Urine under Normal Physiological Conditions

by Amr Elguoshy, Keiko Yamamoto, Yoshitoshi Hirao, Tomohiro Uchimoto, Kengo Yanagita and Tadashi Yamamoto

Proteomes 2024, 12(3), 18; https://doi.org/10.3390/proteomes12030018 - 25 Jun 2024

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Abstract

Examining the composition of the typical urinary peptidome and identifying the enzymes responsible for its formation holds significant importance, as it mirrors the normal physiological state of the human body. Any deviation from this normal profile could serve as an indicator of pathological [...] Read more.

Examining the composition of the typical urinary peptidome and identifying the enzymes responsible for its formation holds significant importance, as it mirrors the normal physiological state of the human body. Any deviation from this normal profile could serve as an indicator of pathological processes occurring in vivo. Consequently, this study focuses on characterizing the normal urinary peptidome and investigating the various catalytic enzymes that are involved in generating these native peptides in urine. Our findings reveal that 1503 endogenous peptides, corresponding to 436 precursor proteins, were consistently identified robustly in at least 10 samples out of a total of 19 samples. Notably, the liver and kidneys exhibited the highest number of tissue-enriched or enhanced genes in the analyzed urinary peptidome. Furthermore, among the catalytic types, CTSD (cathepsin D) and MMP2 (matrix metalloproteinase-2) emerged as the most prominent peptidases in the aspartic and metallopeptidases categories, respectively. A comparison of our dataset with two of the most comprehensive urine peptidome datasets to date indicates a consistent relative abundance of core endogenous peptides for different proteins across all three datasets. These findings can serve as a foundational reference for the discovery of biomarkers in various human diseases. Full article

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Proteomes, Volume 12, Issue 3 (September 2024) – 9 articles

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