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Role of Proteomics in Human Diseases and Infections
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Role of Proteomics in Human Diseases and Infections

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Pathology, Diagnostics, and Therapeutics".

Deadline for manuscript submissions: 20 February 2025 | Viewed by 3276

Special Issue Editors

Dr. Mahamud Ur Rashid

E-Mail Website
Guest Editor
Department of Pathology and Laboratory Medicine, The University of British Columbia, Vancouver, BC, Canada
Interests: proteomics; infections; host-virus interactions
Prof. Dr. Kevin Coombs

E-Mail Website
Guest Editor
Department of Medical Microbiology, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3E 0J9, Canada
Interests: arboviruses; influenza virus; macromolecular structure-function; proteomics, reovirus; virus-host interactions; Zika virus
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The human genome contains around 20,000 genes, which can be translated into over 80,000 proteins through alternative splicing. The maintenance and modification of cellular functions are orchestrated by numerous, complex signaling pathways, regulated through these proteins’ direct or indirect interactions. Disease or infections by a pathogen can cause the dysregulation of protein expressions, post-translational modification, or the impairment of their functional involvement in different signaling pathways. These changes in the cellular proteome are eventually reflected in organ-level dysfunction and may lead to severe illness or death.

This Special Issue aims to delve into the critical role proteomics plays in understanding and combating various human diseases and infections. Proteomics is pivotal in elucidating the mechanisms of diseases at the molecular level, offering insights into protein functions, modifications, and interactions within biological contexts. As we uncover the proteome of cells and tissues in health and disease, we gain valuable information that can lead to the identification of biomarkers, therapeutic targets, and a deeper understanding of disease pathogenesis and host–pathogen interactions.

We also want to welcome research on the innovative applications of proteomics in diagnosing, monitoring, and treating human diseases. We encourage submissions that explore the dynamic proteome in various diseases, the interactions between pathogens and host proteomes, and the potential of proteomics in developing novel diagnostic and therapeutic strategies.

Dr. Mahamud Ur Rashid
Prof. Dr. Kevin Coombs
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • proteomics
  • human diseases
  • infections
  • biomarkers
  • therapeutic targets
  • disease pathogenesis
  • host–pathogen interactions
  • diagnostic tools

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Published Papers (3 papers)

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20 pages, 2065 KiB  
Article
Secretome and Proteome of Extracellular Vesicles Provide Protein Markers of Lung and Colorectal Cancer
by Natalia Soloveva, Svetlana Novikova, Tatiana Farafonova, Olga Tikhonova and Victor Zgoda
Int. J. Mol. Sci. 2025, 26(3), 1016; https://doi.org/10.3390/ijms26031016 - 25 Jan 2025
Viewed by 425
Abstract
Colorectal cancer (CRC) and lung cancer (LC) are leading causes of cancer-related mortality, highlighting the need for minimally invasive diagnostic, prognostic, and predictive markers for these cancers. Proteins secreted by a tumor into the extracellular space directly, known as the tumor secretome, as [...] Read more.
Colorectal cancer (CRC) and lung cancer (LC) are leading causes of cancer-related mortality, highlighting the need for minimally invasive diagnostic, prognostic, and predictive markers for these cancers. Proteins secreted by a tumor into the extracellular space directly, known as the tumor secretome, as well as proteins in the extra-cellular vesicles (EVs), represent an attractive source of biomarkers for CRC and LC. We performed proteomic analyses on secretome and EV samples from LC (A549, NCI-H23, NCI-H460) and CRC (Caco2, HCT116, HT-29) cell lines and targeted mass spectrometry on EVs from plasma samples of 20 patients with CRC and 19 healthy controls. A total of 782 proteins were identified across the CRC and LC secretome and EV samples. Of these, 22 and 44 protein markers were significantly elevated in the CRC and LC samples, respectively. Functional annotation revealed enrichment in proteins linked to metastasis and tumor progression for both cancer types. In EVs isolated from the plasma of patients with CRC, ITGB3, HSPA8, TUBA4A, and TLN1 were reduced, whereas FN1, SERPINA1, and CST3 were elevated, compared to healthy controls. These findings support the development of minimally invasive liquid biopsy methods for the detection, prognosis, and treatment monitoring of LC and CRC. Full article
(This article belongs to the Special Issue Role of Proteomics in Human Diseases and Infections)
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17 pages, 2080 KiB  
Article
Comprehensive Evaluation of Advanced Imputation Methods for Proteomic Data Acquired via the Label-Free Approach
by Grzegorz Wryk, Andrzej Gawor and Ewa Bulska
Int. J. Mol. Sci. 2024, 25(24), 13491; https://doi.org/10.3390/ijms252413491 - 17 Dec 2024
Viewed by 581
Abstract
Mass-spectrometry-based proteomics frequently utilizes label-free quantification strategies due to their cost-effectiveness, methodological simplicity, and capability to identify large numbers of proteins within a single analytical run. Despite these advantages, the prevalence of missing values (MV), which can impact up to 50% of the [...] Read more.
Mass-spectrometry-based proteomics frequently utilizes label-free quantification strategies due to their cost-effectiveness, methodological simplicity, and capability to identify large numbers of proteins within a single analytical run. Despite these advantages, the prevalence of missing values (MV), which can impact up to 50% of the data matrix, poses a significant challenge by reducing the accuracy, reproducibility, and interpretability of the results. Consequently, effective handling of missing values is crucial for reliable quantitative analysis in proteomic studies. This study systematically evaluated the performance of selected imputation methods for addressing missing values in proteomic dataset. Two protein identification algorithms, FragPipe and MaxQuant, were employed to generate datasets, enabling an assessment of their influence on im-putation efficacy. Ten imputation methods, representing three methodological categories—single-value (LOD, ND, SampMin), local-similarity (kNN, LLS, RF), and global-similarity approaches (LSA, BPCA, PPCA, SVD)—were analyzed. The study also investigated the impact of data logarithmization on imputation performance. The evaluation process was conducted in two stages. First, performance metrics including normalized root mean square error (NRMSE) and the area under the receiver operating characteristic (ROC) curve (AUC) were applied to datasets with artificially introduced missing values. The datasets were designed to mimic varying MV rates (10%, 25%, 50%) and proportions of values missing not at random (MNAR) (0%, 20%, 40%, 80%, 100%). This step enabled the assessment of data characteristics on the relative effectiveness of the imputation methods. Second, the imputation strategies were applied to real proteomic datasets containing natural missing values, focusing on the true-positive (TP) classification of proteins to evaluate their practical utility. The findings highlight that local-similarity-based methods, particularly random forest (RF) and local least-squares (LLS), consistently exhibit robust performance across varying MV scenarios. Furthermore, data logarithmization significantly enhances the effectiveness of global-similarity methods, suggesting it as a beneficial preprocessing step prior to imputation. The study underscores the importance of tailoring imputation strategies to the specific characteristics of the data to maximize the reliability of label-free quantitative proteomics. Interestingly, while the choice of protein identification algorithm (FragPipe vs. MaxQuant) had minimal influence on the overall imputation error, differences in the number of proteins classified as true positives revealed more nuanced effects, emphasizing the interplay between imputation strategies and downstream analysis outcomes. These findings provide a comprehensive framework for improving the accuracy and reproducibility of proteomic analyses through an informed selection of imputation approaches. Full article
(This article belongs to the Special Issue Role of Proteomics in Human Diseases and Infections)
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20 pages, 1275 KiB  
Article
The Modulation of Septic Shock: A Proteomic Approach
by Patrícia Terra Alves, Aline Gomes de Souza, Victor Alexandre F. Bastos, Eduarda L. Miguel, Augusto César S. Ramos, L. C. Cameron, Luiz Ricardo Goulart and Thúlio M. Cunha
Int. J. Mol. Sci. 2024, 25(19), 10641; https://doi.org/10.3390/ijms251910641 - 3 Oct 2024
Viewed by 1224
Abstract
Sepsis poses a significant challenge due its lethality, involving multiple organ dysfunction and impaired immune responses. Among several factors affecting sepsis, monocytes play a crucial role; however, their phenotype, proteomic profile, and function in septic shock remain unclear. Our aim was to fully [...] Read more.
Sepsis poses a significant challenge due its lethality, involving multiple organ dysfunction and impaired immune responses. Among several factors affecting sepsis, monocytes play a crucial role; however, their phenotype, proteomic profile, and function in septic shock remain unclear. Our aim was to fully characterize the subpopulations and proteomic profiles of monocytes seen in septic shock cases and discuss their possible impact on the disease. Peripheral blood monocyte subpopulations were phenotype based on CD14/CD16 expression by flow cytometry, and proteins were extracted from the monocytes of individuals with septic shock and healthy controls to identify changes in the global protein expression in these cells. Analysis using 2D-nanoUPLC-UDMSE identified 67 differentially expressed proteins in shock patients compared to controls, in which 44 were upregulated and 23 downregulated. These proteins are involved in monocyte reprogramming, immune dysfunction, severe hypotension, hypo-responsiveness to vasoconstrictors, vasodilation, endothelial dysfunction, vascular injury, and blood clotting, elucidating the disease severity and therapeutic challenges of septic shock. This study identified critical biological targets in monocytes that could serve as potential biomarkers for the diagnosis, prognosis, and treatment of septic shock, providing new insights into the pathophysiology of the disease. Full article
(This article belongs to the Special Issue Role of Proteomics in Human Diseases and Infections)
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