Comparative proteomic analysis of the ovarian fluid and eggs of Siberian sturgeon.

BACKGROUND: Sturgeon species are living fossils that exhibit unique reproductive characteristics, and elucidation of the molecular processes governing the formation and quality of sturgeon eggs is crucial. However, comprehensive data on the protein composition of sturgeon ovarian fluid (OF) and eggs and their functional significance are lacking. To address this knowledge gap, the aim of the present study was to conduct a comprehensive comparative proteomic analysis of Siberian sturgeon OF and eggs using liquid chromatography-mass spectrometry (LC-MS/MS). RESULTS: A total of 617 proteins were identified in OF, and 565 proteins were identified in eggs. A total of 772 proteins showed differential abundance. Among the differentially abundant proteins, 365 were more abundant in OFs, while 407 were more abundant in eggs. We identified 339 proteins unique to OFs and 287 proteins specific to eggs, and further investigated the top 10 most abundant proteins in each. The functional annotation of the OF proteins highlighted their predominant association with immune system processes, including the complement and coagulation cascade, neutrophil and leukocyte-mediated immunity, cholesterol metabolism, and regulation of the actin cytoskeleton. Analysis of egg proteins revealed enrichment in metabolic pathways, such as oxidative phosphorylation and fatty acid metabolism, and protein ubiquitination and translation. OF-specific proteins included extracellular matrix and secretory vesicles, and eggs were enriched in proteins localized to mitochondria and ribosome components. CONCLUSIONS: This study presents the first comprehensive characterization of the protein composition of sturgeon OF and eggs and elucidates their distinct functional roles. These findings advance our understanding of sturgeon reproduction, OF-egg signaling and the origin of OF proteins. The mass spectrometry proteomics data have been deposited in the ProteomeXchange Consortium with the dataset identifier PXD044168 to ensure accessibility for further research.

REMEMProt: a resource of membrane-enriched proteome profiles, their disease associations, and biomarker status.

The differential expression of plasma membrane proteins is integrally analyzed for their diagnosis, prognosis, and therapeutic applications in diverse clinical manifestations. Necessarily, distinct membrane protein enrichment methods and mass spectrometry platforms are employed for their global and relative quantitation. First of its kind to explore, we compiled membrane-associated proteomes in human and mouse systems into a database named, Resource of Experimental Membrane-Enriched Mass spectrometry-derived Proteome (REMEMProt). It currently hosts 14,626 proteins (9,507 proteins in Homo sapiens; 5,119 proteins in Mus musculus) with information on their membrane-protein enrichment methods, experimental/physiological context of detection in cells or tissues, transmembrane domain analysis, and their current attribution as biomarkers. Based on these annotations and the transmembrane domain analysis in proteins or their binary/complex protein-protein interactors, REMEMProt facilitates the assessment of the plasma membrane localization potential of proteins through batch query. A cross-study enrichment analysis platform is enabled in REMEMProt for comparative analysis of proteomes using novel/modified membrane enrichment methods and evaluation of methods for targeted enrichment of membrane proteins. REMEMProt data are made freely accessible to explore and download at https://rememprot.ciods.in/.

Energy flux couples sulfur isotope fractionation to proteomic and metabolite profiles in Desulfovibrio vulgaris.

Microbial sulfate reduction is central to the global carbon cycle and the redox evolution of Earth's surface. Tracking the activity of sulfate reducing microorganisms over space and time relies on a nuanced understanding of stable sulfur isotope fractionation in the context of the biochemical machinery of the metabolism. Here, we link the magnitude of stable sulfur isotopic fractionation to proteomic and metabolite profiles under different cellular energetic regimes. When energy availability is limited, cell-specific sulfate respiration rates and net sulfur isotope fractionation inversely covary. Beyond net S isotope fractionation values, we also quantified shifts in protein expression, abundances and isotopic composition of intracellular S metabolites, and lipid structures and lipid/water H isotope fractionation values. These coupled approaches reveal which protein abundances shift directly as a function of energy flux, those that vary minimally, and those that may vary independent of energy flux and likely do not contribute to shifts in S-isotope fractionation. By coupling the bulk S-isotope observations with quantitative proteomics, we provide novel constraints for metabolic isotope models. Together, these results lay the foundation for more predictive metabolic fractionation models, alongside interpretations of environmental sulfur and sulfate reducer lipid-H isotope data.

ZEPPI: Proteome-scale sequence-based evaluation of protein-protein interaction models.

We introduce ZEPPI (Z-score Evaluation of Protein-Protein Interfaces), a framework to evaluate structural models of a complex based on sequence coevolution and conservation involving residues in protein-protein interfaces. The ZEPPI score is calculated by comparing metrics for an interface to those obtained from randomly chosen residues. Since contacting residues are defined by the structural model, this obviates the need to account for indirect interactions. Further, although ZEPPI relies on species-paired multiple sequence alignments, its focus on interfacial residues allows it to leverage quite shallow alignments. ZEPPI can be implemented on a proteome-wide scale and is applied here to millions of structural models of dimeric complexes in the Escherichia coli and human interactomes found in the PrePPI database. PrePPI's scoring function is based primarily on the evaluation of protein-protein interfaces, and ZEPPI adds a new feature to this analysis through the incorporation of evolutionary information. ZEPPI performance is evaluated through applications to experimentally determined complexes and to decoys from the CASP-CAPRI experiment. As we discuss, the standard CAPRI scores used to evaluate docking models are based on model quality and not on the ability to give yes/no answers as to whether two proteins interact. ZEPPI is able to detect weak signals from PPI models that the CAPRI scores define as incorrect and, similarly, to identify potential PPIs defined as low confidence by the current PrePPI scoring function. A number of examples that illustrate how the combination of PrePPI and ZEPPI can yield functional hypotheses are provided.

Proteomics Study of Benzene Metabolite Hydroquinone Induced Hematotoxicity in K562 Cells.

Objective: Hydroquinone (HQ), one of the phenolic metabolites of benzene, is widely recognized as an important participant in benzene-induced hematotoxicity. However, there are few relevant proteomics in HQ-induced hematotoxicity and the mechanism hasn't been fully understood yet. Methods: In this study, we treated K562 cells with 40 µmol/L HQ for 72 h, examined and validated protein expression changes by Label-free proteomic analysis and Parallel reaction monitoring (PRM), and performed bioinformatics analysis to identify interaction networks. Results: One hundred and eighty-seven upregulated differentially expressed proteins (DEPs) and 279 downregulated DEPs were identified in HQ-exposed K562 cells, which were involved in neutrophil-mediated immunity, blood microparticle, and other GO terms, as well as the lysosome, metabolic, cell cycle, and cellular senescence-related pathways. Focusing on the 23 DEGs and 5 DEPs in erythroid differentiation-related pathways, we constructed the network of protein interactions and determined 6 DEPs (STAT1, STAT3, CASP3, KIT, STAT5B, and VEGFA) as main hub proteins with the most interactions, among which STATs made a central impact and may be potential biomarkers of HQ-induced hematotoxicity. Conclusion: Our work reinforced the use of proteomics and bioinformatic approaches to advance knowledge on molecular mechanisms of HQ-induced hematotoxicity at the protein level and provide a valuable basis for further clarification.

Plasma proteome profiling reveals dynamic of cholesterol marker after dual blocker therapy.

Dual blocker therapy (DBT) has the enhanced antitumor benefits than the monotherapy. Yet, few effective biomarkers are developed to monitor the therapy response. Herein, we investigate the DBT longitudinal plasma proteome profiling including 113 longitudinal samples from 22 patients who received anti-PD1 and anti-CTLA4 DBT therapy. The results show the immune response and cholesterol metabolism are upregulated after the first DBT cycle. Notably, the cholesterol metabolism is activated in the disease non-progressive group (DNP) during the therapy. Correspondingly, the clinical indicator prealbumin (PA), free triiodothyronine (FT3) and triiodothyronine (T3) show significantly positive association with the cholesterol metabolism. Furthermore, by integrating proteome and radiology approach, we observe the high-density lipoprotein partial remodeling are activated in DNP group and identify a candidate biomarker APOC3 that can reflect DBT response. Above, we establish a machine learning model to predict the DBT response and the model performance is validated by an independent cohort with balanced accuracy is 0.96. Thus, the plasma proteome profiling strategy evaluates the alteration of cholesterol metabolism and identifies a panel of biomarkers in DBT.

Multi-omics integration highlights the role of ubiquitination in endometriosis fibrosis.

BACKGROUND: Endometriosis, characterized by the presence of active endometrial-like tissues outside the uterus, causes symptoms like dysmenorrhea and infertility due to the fibrosis of endometrial cells, which involves excessive deposition of extracellular matrix (ECM) proteins. Ubiquitination, an important post-transcriptional modification, regulates various biological processes in human diseases. However, its role in the fibrosis process in endometriosis remains unclear. METHODS: We employed multi-omics approaches on two cohorts of endometriosis patients with 39 samples. GO terms and KEGG pathways enrichment analyses were used to investigate the functional changes involved in endometriosis. Pearson's correlation coefficient analysis was conducted to explore the relationship between global proteome and ubiquitylome in endometriosis. The protein expression levels of ubiquitin-, fibrosis-related proteins, and E3 ubiquitin-protein ligase TRIM33 were validated via Western blot. Transfecting human endometrial stroma cells (hESCs) with TRIM33 small interfering RNA (siRNA) in vitro to explore how TRIM33 affects fibrosis-related proteins. RESULTS: Integration of proteomics and transcriptomics showed genes with concurrent change of both mRNA and protein level which involved in ECM production in ectopic endometria. Ubiquitylomics distinguished 1647 and 1698 ubiquitinated lysine sites in the ectopic (EC) group compared to the normal (NC) and eutopic (EU) groups, respectively. Further multi-omics integration highlighted the essential role of ubiquitination in key fibrosis regulators in endometriosis. Correlation analysis between proteome and ubiquitylome showed correlation coefficients of 0.32 and 0.36 for ubiquitinated fibrosis proteins in EC/NC and EC/EU groups, respectively, indicating positive regulation of fibrosis-related protein expression by ubiquitination in ectopic lesions. We identified ubiquitination in 41 pivotal proteins within the fibrosis-related pathway of endometriosis. Finally, the elevated expression of TGFBR1/α-SMA/FAP/FN1/Collagen1 proteins in EC tissues were validated across independent samples. More importantly, we demonstrated that both the mRNA and protein levels of TRIM33 were reduced in endometriotic tissues. Knockdown of TRIM33 promoted TGFBR1/p-SMAD2/α-SMA/FN1 protein expressions in hESCs but did not significantly affect Collagen1/FAP levels, suggesting its inhibitory effect on fibrosis in vitro. CONCLUSIONS: This study, employing multi-omics approaches, provides novel insights into endometriosis ubiquitination profiles and reveals aberrant expression of the E3 ubiquitin ligase TRIM33 in endometriotic tissues, emphasizing their critical involvement in fibrosis pathogenesis and potential therapeutic targets.

Integrated ribosome and proteome analyses reveal insights into sevoflurane-induced long-term social behavior and cognitive dysfunctions through ADNP inhibition in neonatal mice.

A growing number of studies have demonstrated that repeated exposure to sevoflurane during development results in persistent social abnormalities and cognitive impairment. Davunetide, an active fragment of the activity-dependent neuroprotective protein (ADNP), has been implicated in social and cognitive protection. However, the potential of davunetide to attenuate social deficits following sevoflurane exposure and the underlying developmental mechanisms remain poorly understood. In this study, ribosome and proteome profiles were analyzed to investigate the molecular basis of sevoflurane-induced social deficits in neonatal mice. The neuropathological basis was also explored using Golgi staining, morphological analysis, western blotting, electrophysiological analysis, and behavioral analysis. Results indicated that ADNP was significantly down-regulated following developmental exposure to sevoflurane. In adulthood, anterior cingulate cortex (ACC) neurons exposed to sevoflurane exhibited a decrease in dendrite number, total dendrite length, and spine density. Furthermore, the expression levels of Homer, PSD95, synaptophysin, and vglut2 were significantly reduced in the sevoflurane group. Patch-clamp recordings indicated reductions in both the frequency and amplitude of miniature excitatory postsynaptic currents (mEPSCs). Notably, davunetide significantly ameliorated the synaptic defects, social behavior deficits, and cognitive impairments induced by sevoflurane. Mechanistic analysis revealed that loss of ADNP led to dysregulation of Ca 2+ activity via the Wnt/ß-catenin signaling, resulting in decreased expression of synaptic proteins. Suppression of Wnt signaling was restored in the davunetide-treated group. Thus, ADNP was identified as a promising therapeutic target for the prevention and treatment of neurodevelopmental toxicity caused by general anesthetics. This study provides important insights into the mechanisms underlying social and cognitive disturbances caused by sevoflurane exposure in neonatal mice and elucidates the regulatory pathways involved.

VRK1 Regulates Sensitivity to Oxidative Stress by Altering Histone Epigenetic Modifications and the Nuclear Phosphoproteome in Tumor Cells.

The chromatin organization and its dynamic remodeling determine its accessibility and sensitivity to DNA damage oxidative stress, the main source of endogenous DNA damage. We studied the role of the VRK1 chromatin kinase in the response to oxidative stress. which alters the nuclear pattern of histone epigenetic modifications and phosphoproteome pathways. The early effect of oxidative stress on chromatin was studied by determining the levels of 8-oxoG lesions and the alteration of the epigenetic modification of histones. Oxidative stress caused an accumulation of 8-oxoG DNA lesions that were increased by VRK1 depletion, causing a significant accumulation of DNA strand breaks detected by labeling free 3'-DNA ends. In addition, oxidative stress altered the pattern of chromatin epigenetic marks and the nuclear phosphoproteome pathways that were impaired by VRK1 depletion. Oxidative stress induced the acetylation of H4K16ac and H3K9 and the loss of H3K4me3. The depletion of VRK1 altered all these modifications induced by oxidative stress and resulted in losses of H4K16ac and H3K9ac and increases in the H3K9me3 and H3K4me3 levels. All these changes were induced by the oxidative stress in the epigenetic pattern of histones and impaired by VRK1 depletion, indicating that VRK1 plays a major role in the functional reorganization of chromatin in the response to oxidative stress. The analysis of the nuclear phosphoproteome in response to oxidative stress detected an enrichment of the phosphorylated proteins associated with the chromosome organization and chromatin remodeling pathways, which were significantly decreased by VRK1 depletion. VRK1 depletion alters the histone epigenetic pattern and nuclear phosphoproteome pathways in response to oxidative stress. The enzymes performing post-translational epigenetic modifications are potential targets in synthetic lethality strategies for cancer therapies.

Proteomic Analysis of Prehypertensive and Hypertensive Patients: Exploring the Role of the Actin Cytoskeleton.

Hypertension is a pervasive and widespread health condition that poses a significant risk factor for cardiovascular disease, which includes conditions such as heart attack, stroke, and heart failure. Despite its widespread occurrence, the exact cause of hypertension remains unknown, and the mechanisms underlying the progression from prehypertension to hypertension require further investigation. Recent proteomic studies have shown promising results in uncovering potential biomarkers related to disease development. In this study, serum proteomic data collected from Qatar Biobank were analyzed to identify altered protein expression between individuals with normal blood pressure, prehypertension, and hypertension and to elucidate the biological pathways contributing to this disease. The results revealed a cluster of proteins, including the SRC family, CAMK2B, CAMK2D, TEC, GSK3, VAV, and RAC, which were markedly upregulated in patients with hypertension compared to those with prehypertension (fold change ≥ 1.6 or ≤-1.6, area under the curve ≥ 0.8, and q-value < 0.05). Pathway analysis showed that the majority of these proteins play a role in actin cytoskeleton remodeling. Actin cytoskeleton reorganization affects various biological processes that contribute to the maintenance of blood pressure, including vascular tone, endothelial function, cellular signaling, inflammation, fibrosis, and mechanosensing. Therefore, the findings of this study suggest a potential novel role of actin cytoskeleton-related proteins in the progression from prehypertension to hypertension. The present study sheds light on the underlying pathological mechanisms involved in hypertension and could pave the way for new diagnostic and therapeutic approaches for the treatment of this disease.

Interleukin-13 Treatment of Living Lung Tissue Model Alters the Metabolome and Proteome-A Nano-DESI MS Metabolomics and Shotgun Proteomics Study.

Asthma is a chronic respiratory disease with one of the largest numbers of cases in the world; thus, constant investigation and technical development are needed to unravel the underlying biochemical mechanisms. In this study, we aimed to develop a nano-DESI MS method for the in vivo characterization of the cellular metabolome. Using air-liquid interface (ALI) cell layers, we studied the role of Interleukin-13 (IL-13) on differentiated lung epithelial cells acting as a lung tissue model. We demonstrate the feasibility of nano-DESI MS for the in vivo monitoring of basal-apical molecular transport, and the subsequent endogenous metabolic response, for the first time. Conserving the integrity of the ALI lung-cell layer enabled us to perform temporally resolved metabolomic characterization followed by "bottom-up" proteomics on the same population of cells. Metabolic remodeling was observed upon histamine and corticosteroid treatment of the IL-13-exposed lung cell monolayers, in correlation with alterations in the proteomic profile. This proof of principle study demonstrates the utility of in vivo nano-DESI MS for characterizing ALI tissue layers, and the new markers identified in our study provide a good starting point for future, larger-scale studies.

Dataset of seminal plasma proteome of Nellore bulls with high and low percentage of abnormalities sperm.

OBJECTIVES: Bovine seminal plasma proteins perform several functions related to sperm function. Changes in the expression pattern or abundance of seminal proteins are related to changes in the fertilizing capacity of bulls. Considering the role of seminal plasma proteins in sperm function and animal reproduction, we investigated changes in the protein abundance profile in response to sperm morphological changes using a proteomic approach. DATADESCRIPTION: In our present investigation, we employed liquid chromatography coupled with mass spectrometry to elucidate the proteomic composition of seminal plasma obtained from Nellore bulls exhibiting varying percentages of sperm abnormalities. Following semen collection, seminal plasma was promptly isolated from sperm, and proteins were subsequently precipitated, enzymatically digested using porcine trypsin, and subjected to analysis utilizing the Acquity nano UHPLC System in conjunction with a mass spectrometer. This dataset encompasses a total of 297 proteins, marking the inaugural instance in which a comparative profile of seminal plasma proteins in young Nellore bulls, categorized by their sperm abnormality percentages, has been delineated using LC-MS/MS. The comprehensive nature of this dataset contributes pivotal proteomic insights, representing a noteworthy advancement in our understanding of the reproductive biology of the Nellore breed.

Unveiling potential therapeutic targets for diabetes-induced frozen shoulder through Mendelian randomization analysis of the human plasma proteome.

INTRODUCTION: This study aimed to assess the causal relationship between diabetes and frozen shoulder by investigating the target proteins associated with diabetes and frozen shoulder in the human plasma proteome through Mendelian randomization (MR) and to reveal the corresponding pathological mechanisms. RESEARCH DESIGN AND METHODS: We employed the MR approach for the purposes of establishing: (1) the causal link between diabetes and frozen shoulder; (2) the plasma causal proteins associated with frozen shoulder; (3) the plasma target proteins associated with diabetes; and (4) the causal relationship between diabetes target proteins and frozen shoulder causal proteins. The MR results were validated and consolidated through colocalization analysis and protein-protein interaction network. RESULTS: Our MR analysis demonstrated a significant causal relationship between diabetes and frozen shoulder. We found that the plasma levels of four proteins were correlated with frozen shoulder at the Bonferroni significance level (p<3.03E-5). According to colocalization analysis, parathyroid hormone-related protein (PTHLH) was moderately correlated with the genetic variance of frozen shoulder (posterior probability=0.68), while secreted frizzled-related protein 4 was highly correlated with the genetic variance of frozen shoulder (posterior probability=0.97). Additionally, nine plasma proteins were activated during diabetes-associated pathologies. Subsequent MR analysis of nine diabetic target proteins with four frozen shoulder causal proteins indicated that insulin receptor subunit alpha, interleukin-6 receptor subunit alpha, interleukin-1 receptor accessory protein, glutathione peroxidase 7, and PTHLH might contribute to the onset and progression of frozen shoulder induced by diabetes. CONCLUSIONS: Our study identified a causal relationship between diabetes and frozen shoulder, highlighting the pathological pathways through which diabetes influences frozen shoulder.

Optimizing differential expression analysis for proteomics data via high-performing rules and ensemble inference.

Identification of differentially expressed proteins in a proteomics workflow typically encompasses five key steps: raw data quantification, expression matrix construction, matrix normalization, missing value imputation (MVI), and differential expression analysis. The plethora of options in each step makes it challenging to identify optimal workflows that maximize the identification of differentially expressed proteins. To identify optimal workflows and their common properties, we conduct an extensive study involving 34,576 combinatoric experiments on 24 gold standard spike-in datasets. Applying frequent pattern mining techniques to top-ranked workflows, we uncover high-performing rules that demonstrate optimality has conserved properties. Via machine learning, we confirm optimal workflows are indeed predictable, with average cross-validation F1 scores and Matthew's correlation coefficients surpassing 0.84. We introduce an ensemble inference to integrate results from individual top-performing workflows for expanding differential proteome coverage and resolve inconsistencies. Ensemble inference provides gains in pAUC (up to 4.61%) and G-mean (up to 11.14%) and facilitates effective aggregation of information across varied quantification approaches such as topN, directLFQ, MaxLFQ intensities, and spectral counts. However, further development and evaluation are needed to establish acceptable frameworks for conducting ensemble inference on multiple proteomics workflows.

Super-resolution proximity labeling with enhanced direct identification of biotinylation sites.

Promiscuous labeling enzymes, such as APEX2 or TurboID, are commonly used in in situ biotinylation studies of subcellular proteomes or protein-protein interactions. Although the conventional approach of enriching biotinylated proteins is widely implemented, in-depth identification of specific biotinylation sites remains challenging, and current approaches are technically demanding with low yields. A novel method to systematically identify specific biotinylation sites for LC-MS analysis followed by proximity labeling showed excellent performance compared with that of related approaches in terms of identification depth with high enrichment power. The systematic identification of biotinylation sites enabled a simpler and more efficient experimental design to identify subcellular localized proteins within membranous organelles. Applying this method to the processing body (PB), a non-membranous organelle, successfully allowed unbiased identification of PB core proteins, including novel candidates. We anticipate that our newly developed method will replace the conventional method for identifying biotinylated proteins labeled by promiscuous labeling enzymes.

Proteomic change in the upper lobe of the left lung of Beagle dogs at the lung migration stage of Toxocara canis infection.

BACKGROUND: Toxocara canis is considered one of the most neglected parasitic zoonoses and threatens the health of millions of people worldwide with a predilection for pediatric and adolescent populations in impoverished communities. Exploring the invasion and developmental mechanisms associated with T. canis infection in its definitive canine hosts will help to better control zoonotic toxocariasis. METHODS: Proteomic changes in samples from the upper lobe of the left lung of Beagle puppies were systematically analyzed by quantitative proteomic technology of data-independent acquisition (DIA) at 96 h post-infection (hpi) with T. canis. Proteins with P-values < 0.05 and fold change > 1.5 or < 0.67 were considered proteins with differential abundance (PDAs). RESULTS: A total of 28 downregulated PDAs and 407 upregulated PDAs were identified at 96 hpi, including RhoC, TM4SFs and LPCAT1, which could be associated with the maintenance and repair of lung homeostasis. GO annotation and KEGG pathway enrichment analyses of all identified proteins and PDAs revealed that many lung proteins have correlation to signal transduction, lipid metabolism and immune system. CONCLUSIONS: The present study revealed lung proteomic alterations in Beagle dogs at the lung migration stage of T. canis infection and identified many PDAs of Beagle dog lung, which may play important roles in the pathogenesis of toxocariasis, warranting further experimental validation.

Proteomics data in vitiligo: a scoping review.

An unbiased screening of which proteins are deregulated in vitiligo using proteomics can offer an enormous value. It could not only reveal robust biomarkers for detecting disease activity but can also identify which patients are most likely to respond to treatments. We performed a scoping review searching for all articles using proteomics in vitiligo. Eight manuscripts could be identified. Unfortunately, very limited overlap was found in the differentially expressed proteins between studies (15 out of 272; 5,51%) with variable degrees of the type of proteins and a substantial variety in the prevalence of acute phase proteins (range: 6-65%). Proteomics research has therefore brought little corroborating evidence on which proteins are differentially regulated between vitiligo patients and healthy controls or between active and stable vitiligo patients. While a limited patient size is an obvious weakness for several studies, an incomplete description of patient characteristics is an unfortunate and avoidable shortcoming. Additionally, the variations in the used methodology and analyses may further contribute to the overall observed variability. Nonetheless, more recent studies investigating the response to treatment seem to be more robust, as more differentially expressed proteins that have previously been confirmed to be involved in vitiligo were found. The further inclusion of proteomics analyses in clinical trials is recommended to increase insights into the pathogenic mechanisms in vitiligo and identify reliable biomarkers or promising drug targets. A harmonization in the study design, reporting and proteomics methodology could vastly improve the value of vitiligo proteomics research.

From Androgen Dependence to Independence in Prostate Cancer: Unraveling Therapeutic Potential and Proteomic Landscape of Hydroxychloroquine as an Autophagy Inhibitor.

Prostate cancer is a major planetary health challenge wherein new ways of thinking drug discovery and therapeutics innovation are much needed. Numerous studies have shown that autophagy inhibition holds a significant role as an adjunctive intervention in prostate cancer. Hydroxychloroquine (HCQ) has gained considerable attention due to its established role as an autophagy inhibitor across diverse cancer types, but its proteomics landscape and systems biology in prostate cancer are currently lacking in the literature. This study reports the proteomic responses to HCQ in prostate cancer cells, namely, androgen-dependent LNCaP and androgen-independent PC3 cells. Differentially expressed proteins and proteome in HCQ-treated cells were determined by label-free quantification with nano-high-performance liquid chromatography and tandem mass spectrometry (nHPLC-MS/MS), and harnessing bioinformatics tools. In PC3 cells, there was a marked shift toward metabolic reprogramming, highlighted by an upregulation of mitochondrial proteins in oxidative phosphorylation and tricarboxylic acid cycle, suggesting an adaptive mechanism to maintain energy production under therapeutic stress. In contrast, LNCaP cells prioritized proteostasis and cell cycle regulation, indicating a more conservative adaptation strategy. To the best of our knowledge, this study is the first to demonstrate the differential responses of prostate cancer cells to autophagy inhibition by HCQ, suggesting that a combination therapy approach, targeting distinct pathways in androgen-independent and androgen-dependent cells, could represent a promising treatment strategy. Moreover, the varied proteomic responses observed between these cell lines underscore the importance of personalized medicine in cancer therapy. Future translational and clinical research on HCQ and prostate cancer are called for.

Proteomic Profiling of Samples Derived from a Murine Model Following Cryptococcus neoformans Infection.

Proteomic profiling provides in-depth information about the regulation of diverse biological processes, activation of and communication across signaling networks, and alterations to protein production, modifications, and interactions. For infectious disease research, mass spectrometry-based proteomics enables detection of host defenses against infection and mechanisms used by the pathogen to evade such responses. In this chapter, we outline protein extraction from organs, tissues, and fluids collected following intranasal inoculation of a murine model with the human fungal pathogen Cryptococcus neoformans. We describe sample preparation, followed by purification, processing on the mass spectrometer, and a robust bioinformatics analysis. The information gleaned from proteomic profiling of fungal infections supports the detection of novel biomarkers for diagnostic and prognostic purposes.

Induction of acrosome reaction by 4-Br-A23187 alters the glycoproteomic profile of boar spermatozoa.

Protein glycosylation is a post-translational modification involved in wide range of biological processes. In mammalian spermatozoa this modification has been identified in numerous proteins, and membrane glycoproteins are involved in the fertilization process. The objective of the present study was to identify changes in protein glycosylation after acrosome reaction (AR) induction using the 4-Br-A23187 ionophore. Our results showed that treatment with 10 µM of 4-Br-A23187 for 20 min significantly increased the percentage of live acrosome-reacted spermatozoa compared to the control (69.8 ± 0.8 vs. 6.4 ± 0.5; mean % ± SEM, respectively). Also, we observed an increase in 32 kDa tyrosine-phosphorylated protein (p32) and a decrease in serine/threonine phosphorylation of the protein kinase A substrates (phospho-PKA-substrates) after ionophore treatment. Furthermore, changes in glycosylated proteins following AR induction were analyzed using different HRP-conjugated lectins (GNA, DSA, and SNA), revealing changes in mannose and sialic acid residues. Proteomic analysis of isolated proteins using GNA lectin revealed that 50 proteins exhibited significantly different abundance (q-value < 0.01). Subsequent analysis using Uniprot database identified 39 downregulated and 11 upregulated proteins in the presence of 4-Br-A23187. Notably, six of these proteins were classified as transmembrane proteins, namely LRRC37A/B like protein 1 C-terminal domain-containing protein, Membrane metalloendopeptidase like 1, VWFA domain-containing protein, Syndecan, Membrane spanning 4-domains A14 and Serine protease 54. This study shows a novel protocol to induce acrosome reaction in boar spermatozoa and identifies new transmembrane proteins containing mannose residues. Further work is needed to elucidate the role of these proteins in sperm-oocyte fusion.