ProteomicsPub Date : 2025-07-09DOI: 10.1002/pmic.70006
Ivo Fabrik, Rudolf Kupcik, Daniela Fabrikova, Marketa Chvojkova, Kristina Holubova, Kristina Hakenova, Martin Horak, Jiri Soukup, Monika Manethova, Robert Rusina, Radoslav Matej, Ales Ryska, Ondrej Soukup
{"title":"Memantine Administration Enhances Glutamatergic and GABAergic Pathways in the Human Hippocampus of Alzheimer's Disease Patients","authors":"Ivo Fabrik, Rudolf Kupcik, Daniela Fabrikova, Marketa Chvojkova, Kristina Holubova, Kristina Hakenova, Martin Horak, Jiri Soukup, Monika Manethova, Robert Rusina, Radoslav Matej, Ales Ryska, Ondrej Soukup","doi":"10.1002/pmic.70006","DOIUrl":"10.1002/pmic.70006","url":null,"abstract":"<p>One of the traditional treatments in Alzheimer's disease (AD) is administration of memantine, the NMDA receptor antagonist. However, the molecular mechanism of the complex memantine action and the impact on the hippocampal proteome in humans is unknown. In this study, hippocampal proteins extracted from formalin-fixed paraffin-embedded post mortem tissues obtained from healthy donors (<i>n</i> = 15), AD patients not treated with memantine (<i>n</i> = 11), and AD patients treated with memantine (<i>n</i> = 8) were investigated using tandem mass tag (TMT)-based quantitative proteomics. Memantine medication induced subtle but distinct changes in the hippocampal proteome in AD patients. Although it did not prevent the metabolic and physiologic decline associated with AD pathology, memantine administration upregulated several mitochondrially encoded proteins and mitigated the proteomic pattern of activated phagocytes. Furthermore, memantine specifically enhanced the expression of postsynaptic glutamatergic and GABAergic receptors and components of the respective pathways without affecting presynaptic proteome. This suggests that memantine treatment in AD patients not only alleviates excitotoxic stress by inhibiting NMDA receptor activity, but also triggers broader adaptations in the synaptic signaling and plasticity.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 15","pages":"42-49"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12329391/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144937427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2025-07-09DOI: 10.1002/pmic.70007
Ayako Takemori, Philipp T. Kaulich, Andreas Tholey, Nobuaki Takemori
{"title":"Dissolvable Polyacrylamide Gel Electrophoresis-Enabled High-Resolution Sample Fractionation for Middle-Down Proteomics","authors":"Ayako Takemori, Philipp T. Kaulich, Andreas Tholey, Nobuaki Takemori","doi":"10.1002/pmic.70007","DOIUrl":"10.1002/pmic.70007","url":null,"abstract":"<div>\u0000 \u0000 <p>Top-down proteomics (TDP) is a powerful analytical approach for the highly sensitive measurement of intact proteoforms by mass spectrometry. However, its application to high molecular weight proteoforms remains challenging. Middle-down proteomics (MDP) offers a practical solution but requires pre-fractionation of the complex peptide mixture generated by limited digestion to successfully achieve trace-level peptide detection. Here, we present 2D-GeLC-FAIMS-MS, an innovative gel-based sample pre-fractionation workflow for in-depth MDP. This workflow integrates limited Glu-C digestion with a two-dimensional sample fractionation strategy that combines a BAC (<i>N,N′</i>-bis(acryloyl)cystamine)-cross-linked dissolvable polyacrylamide gel electrophoresis (BAC-PAGE) with PEPPI-MS, a highly efficient passive protein extraction method. Samples are first size-fractionated by BAC-PAGE and subsequently subjected to in-gel Glu-C digestion. The resulting middle-down peptides (< 50 kDa) undergo a second fractionation via SDS-PAGE, followed by peptide recovery using PEPPI-MS and LC-FAIMS-MS analysis. The dissolution properties of BAC gels enable efficient sample transfer between the two PAGE steps with minimal loss, ensuring high-resolution pre-fractionation. This novel workflow provides a robust and efficient strategy for the comprehensive characterization of middle-down peptides, facilitating improved sensitivity and depth in proteome analysis.</p>\u0000 </div>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 15","pages":"50-57"},"PeriodicalIF":3.9,"publicationDate":"2025-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144937461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2025-07-06DOI: 10.1002/pmic.70008
Sampa Das
{"title":"EXPRESSION OF CONCERN: Binding of Insecticidal Lectin Colocasia esculenta Tuber Agglutinin (CEA) to Midgut Receptors of Bemisia tabaci and Lipaphis erysimi Provides Clues to its Insecticidal Potential","authors":"Sampa Das","doi":"10.1002/pmic.70008","DOIUrl":"10.1002/pmic.70008","url":null,"abstract":"<p><b>EXPRESSION OF CONCERN</b>: A, Roy, S, Gupta, D, Hess, K, P, Das, and S, Das, “Binding of Insecticidal Lectin <i>Colocasia esculenta</i> Tuber Agglutinin (CEA) to Midgut Receptors of <i>Bemisia tabaci</i> and <i>Lipaphis erysimi</i> Provides Clues to its Insecticidal Potential,” <i>Proteomics</i> 14, no. 13–14 (2014): 1646–1659, https://doi.org/10.1002/pmic.201300408.</p><p>This Expression of Concern is for the above article, published online on 17 April 2014 in Wiley Online Library (wileyonlinelibrary.com), and has been issued by agreement between the journal Editor-in-Chief, Lucie Kalvodova, and Wiley-VCH GmbH. A third party reported concerns that the image in Figure 1D as well as the marker lanes used in Figures 2D,E in this paper had been reused from another article by some of the same authors (Mondal et al. 2012 [http://doi.org/10.4236/ajps.2012.36094]). The authors responded to an inquiry by the publisher and stated that Figure 1D had been reused from the previous publication unintentionally and that the marker lanes in Figures 2D,E had been re-used across all their publications on mannose binding lectins during 2010 and through 2015. The authors supplied a new image for the CEA western blot in Figure 1D and the associated original data, but the parties could not confirm that the supplied data corresponded to the correct samples. The authors additionally confirmed that the original data for the CEA purification experiments were no longer available. The authors provided additional data which were related to the experiment in Figure 1D. However, the publisher could not verify its authenticity because the full set of data related to the experiment was not available. The Expression of Concern has been agreed to because, while the re-use of marker lanes is not viewed as a major concern, the parties have not been able to validate the data presented in Figure 1D. Therefore, the journal has decided to issue an expression of concern to inform and alert the readers. The authors disagree with the expression of concern.</p><p>The authors declare no conflicts of interest.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 19","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://analyticalsciencejournals.onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144574570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2025-06-30DOI: 10.1002/pmic.70004
Liang Xue, Shivani Tiwary, Mykola Bordyuh, Robert Stanton
{"title":"CoSpred: Machine Learning Workflow to Predict Tandem Mass Spectrum in Proteomics","authors":"Liang Xue, Shivani Tiwary, Mykola Bordyuh, Robert Stanton","doi":"10.1002/pmic.70004","DOIUrl":"10.1002/pmic.70004","url":null,"abstract":"<div>\u0000 \u0000 <p>In mass spectrometry-based proteomics, the use of deep learning algorithms can help improve the identification rates of peptides and proteins through the generation of high-fidelity theoretical spectrum which can be used as the basis of a more complete spectral library than those presently available, especially for unobserved protein/genetic variants. Here we focus on providing an end-to-end user-friendly machine learning workflow, which we call <b>Co</b>mplete <b>S</b>pectrum <b>Pred</b>ictor (CoSpred). Using CoSpred users can create their own machine learning compatible training dataset and then train a machine learning model to predict both backbone and non-backbone ions. For the model a transformer encoder architecture is used to predict the complete MS/MS spectrum from a given peptide sequence. In addition to the transformer model provided in the package, the code is built modularly to allow for alternate ML models to be easily “plugged in,” allowing for spectrum prediction optimization given different experimental conditions. The CoSpred workflow (preprocessing→training→inference) provides a path for state-of-art ML capabilities to be more accessible to proteomics scientists.</p>\u0000 </div>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 15","pages":"27-41"},"PeriodicalIF":3.9,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144525743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2025-06-27DOI: 10.1002/pmic.202500087
Irina-Mihaela Matache
{"title":"Beyond Gravity: Leveraging Gene Plasticity to Mitigate Spaceflight-Induced Pathologies","authors":"Irina-Mihaela Matache","doi":"10.1002/pmic.202500087","DOIUrl":"10.1002/pmic.202500087","url":null,"abstract":"<p>As space exploration becomes increasingly accessible, understanding the molecular and pathophysiological consequences of spaceflight on the human body becomes crucial. Space-induced modifications could disrupt multiple signaling pathways, with significant implications for the functional integrity of cardiovascular, nervous, and musculoskeletal systems, among others. In a recent study, Bourdakou et al. have focused on alterations in gene expression profiles linked to cardiovascular disease (CVD), using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) undergoing spaceflight and subsequent postflight conditions. Genes with known associations with CVD and nuclear factor erythroid 2-related factor 2 (NRF2) oxidative stress regulatory network have been identified to present consistent directional expression changes in both spaceflight and postflight. A computational drug repurposing analysis identified ten candidate agents with the potential to reverse observed transcriptomic modifications in spaceflight-exposed cardiomyocytes. These findings highlight the importance of molecular studies and emphasize the need for integrative, multi-omic research efforts to protect human health during and beyond spaceflight.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 11-12","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202500087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144503147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2025-06-27DOI: 10.1002/pmic.202500093
Griet Glorieux, Julie Klein, Agnieszka Latosinska
{"title":"Multi-Disciplinary and Omics-Driven Approaches to Advance Personalized Medicine in Cardiovascular and Chronic Kidney Disease","authors":"Griet Glorieux, Julie Klein, Agnieszka Latosinska","doi":"10.1002/pmic.202500093","DOIUrl":"10.1002/pmic.202500093","url":null,"abstract":"<p>We are living in an omics era, in which molecular profiling technologies can detect thousands of molecules across multiple biological layers. Yet chronic diseases—such as chronic kidney disease (CKD) and cardiovascular disease (CVD)—are still diagnosed only after overt signs and symptoms appear, relying on biomarkers that indicate established organ damage (e.g., estimated glomerular filtration rate (eGFR), albuminuria, troponin T, natriuretic peptides) [<span>1</span>]. In other words, by the time a chronic disease is recognized, curative treatment is generally no longer possible, as irreversible organ damage has already occurred. These conditions are termed “chronic” because, once they develop, patients live with them for the rest of their lives. Additionally, their life expectancy is shorter with a significant loss of quality of life.</p><p>Preventive measures to reduce the global burden of chronic diseases are therefore of paramount importance. The impact is enormous: in 2021, CKD caused 1.5 million deaths [<span>2</span>], while CVD accounted for more than 20 million deaths [<span>3</span>], with ischemic heart disease the leading and CKD the eleventh leading cause of mortality worldwide. Disability-adjusted life-years (DALYs) totaled 212 million for ischemic heart disease and 44.5 million for CKD [<span>4</span>]. In addition, the economic impact of both CKD and CVD is huge and is estimated to further increase in the coming years [<span>5-7</span>]. However, diagnosed cases represent only the “tip of the iceberg” (Figure 1); most patients remain undiagnosed because these diseases develop silently and progressively over the years.</p><p>CKD and CVD originate at the molecular level (bottom of the iceberg), are tightly interconnected—each increasing the risk of the other—and share common risk factors such as diabetes and hypertension. Additionally, therapies overlap for example, in patients with established CKD, renin–angiotensin system inhibitors, sodium-glucose co-transporter 2 inhibitors, and the non-steroidal mineralocorticoid receptor agonist finerenone reduce not only the risk of kidney disease progression but also cardiovascular events [<span>3</span>]. Considering the continuum of disease development, it is logical to intervene as early as possible, when the disease-associated changes are only at the molecular level. Moreover, early intervention has been demonstrated to be the most effective approach. In fact, intervention before irreversible organ damage should ideally even prevent onset of chronic disease. At the same time, no single biomarker can capture the complexity of these systemic disorders, which involve multiple organs and show marked heterogeneity in progression and treatment response. The societal, healthcare, and economic burden of CKD and CVD underscores the need for personalized, omics-based approaches that accommodate this multifactorial complexity and enable personalized intervention.</p><p>Personalized medicine rep","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 11-12","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.202500093","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144503146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2025-06-23DOI: 10.1002/pmic.13977
Motahare Khorrami, Paul A. Haynes, Christopher Pastras, Mohsen Asadnia
{"title":"Quantitative Proteomics of Cochlear Tissues: Bilateral Comparisons in Guinea Pigs and Rats","authors":"Motahare Khorrami, Paul A. Haynes, Christopher Pastras, Mohsen Asadnia","doi":"10.1002/pmic.13977","DOIUrl":"10.1002/pmic.13977","url":null,"abstract":"<p>The cochlea, an incredibly sensitive sensory system, detects sound waves and converts them into electrical signals the brain recognizes as sound. Damage to cochlear hair cells can release proteins, triggering biological responses that may impair hearing. Mass spectrometry-based proteomics offers insights into protein expression changes in cochlear tissues, improving our understanding of inner ear diseases. In this study, we performed a comprehensive proteomics analysis of whole cochlear tissue extracted from healthy guinea pigs and rats. The study optimized protein extraction protocols and analyzed cochlear protein expression using three biological replicates for each animal model. The results included the identification of 1841 proteins in guinea pigs and 3423 proteins in rats, with a high overlap in cochlear protein expression between the left and right ears—93% in guinea pigs and 89% in rats. The findings validate the assumption that the cochlear tissues from both sides of the ears can be considered biologically equivalent. This experiment provides a comprehensive cochlear proteome for guinea pigs and rats, supporting future studies on inner ear disorders.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 13","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.13977","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2025-06-23DOI: 10.1002/pmic.13981
Lauren E. Grubb, Mohana Talasila, Linda Y. Gorim, Richard Glen Uhrig
{"title":"Defining the Molecular Impacts of Humalite Application on Field-Grown Wheat (Triticum aestivum L.) Using Quantitative Proteomics","authors":"Lauren E. Grubb, Mohana Talasila, Linda Y. Gorim, Richard Glen Uhrig","doi":"10.1002/pmic.13981","DOIUrl":"10.1002/pmic.13981","url":null,"abstract":"<p>Increasing global food production demands have resulted in increased fertilizer usage, causing detrimental environmental impacts. Biostimulants, such as humic substances, are currently being applied as a strategy to increase plant nutrient-use efficiency and minimize environmental impacts within cropping systems. One of these biostimulants is Humalite, which is a unique, naturally occurring coal-like substance found in deposits across southern Alberta. These deposits contain exceptionally high ratios of humic acids (>70%) and micronutrients due to their unique freshwater depositional environment. Humalite has begun to be applied to fields based on scientific data suggesting positive impacts on crop growth, yield, and nutrient usage; however, little is known about the underlying molecular mechanisms of Humalite. Here, as part of a larger field study, we report a quantitative proteomics approach to identify systems-level molecular changes induced by the addition of different Humalite application rates in field-grown wheat (<i>Triticum aestivum</i> L.) under three urea fertilizer application rates. In particular, we see wide-ranging abundance changes in proteins associated with several metabolic pathways and growth-related biological processes that suggest how Humalite modulates the plant molecular landscape. Overall, our results provide new, functional information that will help better inform agricultural producers on optimal biostimulant and fertilizer usage.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":"25 14","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/pmic.13981","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144367638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}