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Candida albicans is a common pathogenic fungus that presents a challenge to healthcare facilities. It can switch between a yeast cell form that diffuses through the bloodstream to colonize internal organs and a filamentous form that penetrates host mucosa. Understanding the pathogen’s strategies for environmental adaptation and, ultimately, survival, is crucial. As a complementary study, herein, a multi-omics analysis was performed using high-resolution timsTOF MS to compare the proteomes and metabolomes of Wild Type (WT) Candida albicans (strain DK318) grown on agar plates versus liquid media. Proteomic analysis revealed a total of 1793 proteins and 15,013 peptides. Out of the 1403 identified proteins, 313 proteins were significantly differentially abundant with a p-value < 0.05. Of these, 156 and 157 proteins were significantly increased in liquid and solid media, respectively. Metabolomics analysis identified 192 metabolites in total. The majority (42/48) of the significantly altered metabolites (p-value 0.05 FDR, FC 1.5), mainly amino acids, were significantly higher in solid media, while only 2 metabolites were significantly higher in liquid media. The combined multi-omics analysis provides insight into adaptative morphological changes supporting Candida albicans’ life cycle and identifies crucial virulence factors during biofilm formation and bloodstream infection.

Defective in cullin neddylation 1 domain containing 1 (DCUN1D1) is an E3 ligase for the neddylation, a post-translational process similar to and occurring in parallel to ubiquitin proteasome pathway. Although established as an oncogene in a variety of squamous cell carcinomas, the precise role of DCUN1D1 in prostate cancer (PCa) has not been previously explored thoroughly. Here, we investigated the role of DCUN1D1 in PCa and demonstrated that DCUN1D1 is upregulated in cell lines as well as human tissue samples. Inhibition of DCUN1D1 significantly reduced PCa cell proliferation and migration and remarkably inhibited xenograft formation in mice. Applying both genomics and proteomics approaches, we provide novel information about the DCUN1D1 mechanism of action. We identified CUL3, CUL4B, RBX1, CAND1 and RPS19 proteins as DCUN1D1 binding partners. Our analysis also revealed the dysregulation of genes associated with cellular growth and proliferation, developmental, cell death and cancer pathways and the WNT/β-catenin pathway as potential mechanisms. Inhibition of DCUN1D1 leads to the inactivation of β-catenin through its phosphorylation and degradation which inhibits the downstream action of β-catenin, reducing its interaction with Lef1 in the Lef1/TCF complex that regulates Wnt target gene expression. Together our data point to an essential role of the DCUN1D1 protein in PCa which can be explored for potential targeted therapy.

Metastasis is a serious and often life-threatening condition, representing the leading cause of death among women with breast cancer (BC). Although the current clinical classification of BC is well-established, the addition of minimally invasive laboratory tests based on peripheral blood biomarkers that reflect pathological changes in the body is of utmost importance. In the current study, the serum proteome and lipidome profiles for 50 BC patients with (25) and without (25) metastasis were studied. Targeted proteomic analysis for concertation measurements of 125 proteins in the serum was performed via liquid chromatography–multiple reaction monitoring mass spectrometry (LC–MRM MS) using the BAK 125 kit (MRM Proteomics Inc., Victoria, BC, Canada). Untargeted label-free lipidomic analysis was performed using liquid chromatography coupled to tandem mass-spectrometry (LC–MS/MS), in both positive and negative ion modes. Finally, 87 serum proteins and 295 lipids were quantified and showed a moderate correlation with tumor grade, histological and biological subtypes, and the number of lymph node metastases. Two highly accurate classifiers that enabled distinguishing between metastatic and non-metastatic BC were developed based on proteomic (accuracy 90%) and lipidomic (accuracy 80%) features. The best classifier (91% sensitivity, 89% specificity, AUC = 0.92) for BC metastasis diagnostics was based on logistic regression and the serum levels of 11 proteins: alpha-2-macroglobulin, coagulation factor XII, adiponectin, leucine-rich alpha-2-glycoprotein, alpha-2-HS-glycoprotein, Ig mu chain C region, apolipoprotein C-IV, carbonic anhydrase 1, apolipoprotein A-II, apolipoprotein C-II and alpha-1-acid glycoprotein 1.

Water monitor lizards (WMLs) reside in unhygienic and challenging ecological surroundings and are routinely exposed to various pathogenic microorganisms. It is possible that their gut microbiota produces substances to counter microbial infections. Here we determine whether selected gut bacteria of water monitor lizards (WMLs) possess anti-amoebic properties using Acanthamoeba castellanii of the T4 genotype. Conditioned media (CM) were prepared from bacteria isolated from WML. The CM were tested using amoebicidal, adhesion, encystation, excystation, cell cytotoxicity and amoeba-mediated host cell cytotoxicity assays in vitro. Amoebicidal assays revealed that CM exhibited anti-amoebic effects. CM inhibited both excystation and encystation in A. castellanii. CM inhibited amoebae binding to and cytotoxicity of host cells. In contrast, CM alone showed limited toxic effects against human cells in vitro. Mass spectrometry revealed several antimicrobials, anticancer, neurotransmitters, anti-depressant and other metabolites with biological functions. Overall, these findings imply that bacteria from unusual places, such as WML gut, produce molecules with anti-acanthamoebic capabilities.

Skin cancer, including malignant melanoma (MM) and keratinocyte carcinoma (KC), historically named non-melanoma skin cancers (NMSC), represents the most common type of cancer among the white skin population. Despite decades of clinical research, the incidence rate of melanoma is increasing globally. Therefore, a better understanding of disease pathogenesis and resistance mechanisms is considered vital to accomplish early diagnosis and satisfactory control. The “Omics” field has recently gained attention, as it can help in identifying and exploring metabolites and metabolic pathways that assist cancer cells in proliferation, which can be further utilized to improve the diagnosis and treatment of skin cancer. Although skin tissues contain diverse metabolic enzymes, it remains challenging to fully characterize these metabolites. Metabolomics is a powerful omics technique that allows us to measure and compare a vast array of metabolites in a biological sample. This technology enables us to study the dermal metabolic effects and get a clear explanation of the pathogenesis of skin diseases. The purpose of this literature review is to illustrate how metabolomics technology can be used to evaluate the metabolic profile of human skin cancer, using a variety of analytical platforms including gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and nuclear magnetic resonance (NMR). Data collection has not been based on any analytical method.

Untargeted multi-omics analysis of plasma is an emerging tool for the identification of novel biomarkers for evaluating disease prognosis, and for developing a better understanding of molecular mechanisms underlying human disease. The successful application of metabolomic and proteomic approaches relies on reproducibly quantifying a wide range of metabolites and proteins. Herein, we report the results of untargeted metabolomic and proteomic analyses from blood plasma samples following analyte extraction by two frequently-used solvent systems: chloroform/methanol and methanol-only. Whole blood samples were collected from participants (n = 6) at University Hospital Sharjah (UHS) hospital, then plasma was separated and extracted by two methods: (i) methanol precipitation and (ii) 4:3 methanol:chloroform extraction. The coverage and reproducibility of the two methods were assessed by ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). The study revealed that metabolite extraction by methanol-only showed greater reproducibility for both metabolomic and proteomic quantifications than did methanol/chloroform, while yielding similar peptide coverage. However, coverage of extracted metabolites was higher with the methanol/chloroform precipitation.

Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative “omics” approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis.

The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has captivated the globe’s attention since its emergence in 2019. This highly infectious, spreadable, and dangerous pathogen has caused health, social, and economic crises. Therefore, a worldwide collaborative effort was made to find an efficient strategy to overcome and develop vaccines. The new vaccines provide an effective immune response that safeguards the community from the virus’ severity. WHO has approved nine vaccines for emergency use based on safety and efficacy data collected from various conducted clinical trials. Herein, we review the safety and effectiveness of the WHO-approved COVID-19 vaccines and associated immune responses, and their impact on improving the public’s health. Several immunological studies have demonstrated that vaccination dramatically enhances the immune response and reduces the likelihood of future infections in previously infected individuals. However, the type of vaccination and individual health status can significantly affect immune responses. Exposure of healthy individuals to adenovirus vectors or mRNA vaccines causes the early production of antibodies from B and T cells. On the other hand, unhealthy individuals were more likely to experience harmful events due to relapses in their existing conditions. Taken together, aligning with the proper vaccination to a patient’s case can result in better outcomes.

Cancer of the central nervous system (CNS) is ranked as the 19th most prevalent form of the disease in 2020. This study aims to identify candidate biomarkers and metabolic pathways affected by paclitaxel and etoposide, which serve as potential treatments for glioblastoma, and are linked to the pathogenesis of glioblastoma. We utilized an untargeted metabolomics approach using the highly sensitive ultra-high-performance liquid chromatography-electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS) for identification. In this study, 92 and 94 metabolites in U87 and U373 cell lines were profiled, respectively. The produced metabolites were then analyzed utilizing t-tests, volcano plots, and enrichment analysis modules. Our analysis revealed distinct metabolites to be significantly dysregulated (nutriacholic acid, L-phenylalanine, L-arginine, guanosine, ADP, hypoxanthine, and guanine), and to a lesser extent, mevalonic acid in paclitaxel and/or etoposide treated cells. Furthermore, both urea and citric acid cycles, and metabolism of polyamines and amino acids (aspartate, arginine, and proline) were significantly enriched. These findings can be used to create a map that can be utilized to assess the antitumor effect of paclitaxel and/or etoposide within the studied cancer cells.

Hepatocellular carcinoma (HCC) is the second prominent cause of cancer-associated death worldwide. Usually, HCC is diagnosed in advanced stages, wherein sorafenib, a multiple target tyrosine kinase inhibitor, is used as the first line of treatment. Unfortunately, resistance to sorafenib is usually encountered within six months of treatment. Therefore, there is a critical need to identify the underlying reasons for drug resistance. In the present study, we investigated the proteomic and metabolomics alterations accompanying sorafenib resistance in hepatocellular carcinoma Hep3B cells by employing ultra-high-performance liquid chromatography quadrupole time of flight mass spectrometry (UHPLC-QTOF-MS). The Bruker Human Metabolome Database (HMDB) library was used to identify the differentially abundant metabolites through MetaboScape 4.0 software (Bruker). For protein annotation and identification, the Uniprot proteome for Homo sapiens (Human) database was utilized through MaxQuant. The results revealed that 27 metabolites and 18 proteins were significantly dysregulated due to sorafenib resistance in Hep3B cells compared to the parental phenotype. D-alanine, L-proline, o-tyrosine, succinic acid and phosphatidylcholine (PC, 16:0/16:0) were among the significantly altered metabolites. Ubiquitin carboxyl-terminal hydrolase isozyme L1, mitochondrial superoxide dismutase, UDP-glucose-6-dehydrogenase, sorbitol dehydrogenase and calpain small subunit 1 were among the significantly altered proteins. The findings revealed that resistant Hep3B cells demonstrated significant alterations in amino acid and nucleotide metabolic pathways, energy production pathways and other pathways related to cancer aggressiveness, such as migration, proliferation and drug-resistance. Joint pathway enrichment analysis unveiled unique pathways, including the antifolate resistance pathway and other important pathways that maintain cancer cells’ survival, growth, and proliferation. Collectively, the results identified potential biomarkers for sorafenib-resistant HCC and gave insights into their role in chemotherapeutic drug resistance, cancer initiation, progression and aggressiveness, which may contribute to better prognosis and chemotherapeutic outcomes.

Diabetic kidney disease (DKD) is a severe irreversible complication of diabetes mellitus that further disturbs glucose metabolism. Identifying metabolic changes in the blood may provide early insight into DKD pathogenesis. This study aims to determine blood biomarkers differentiating DKD from non-diabetic kidney disease in the Emirati population utilizing the LC-MS/MS platform. Blood samples were collected from hemodialysis subjects with and without diabetes to detect indicators of pathological changes using an untargeted metabolomics approach. Metabolic profiles were analyzed based on clinically confirmed diabetic status and current HbA1c values. Five differentially significant metabolites were identified based on the clinically confirmed diabetic status, including hydroxyprogesterone and 3,4-Dihydroxymandelic acid. Similarly, we identified seven metabolites with apparent differences between Dialysis Diabetic (DD) and Dialysis non-Diabetic (DND) groups, including isovalerylglycine based on HbA1c values. Likewise, the top three metabolic pathways, including Tyrosine metabolism, were identified following the clinically confirmed diabetic status. As a result, nine different metabolites were enriched in the identified metabolic pathways, such as 3,4-Dihydroxymandelic acid. As a result, eleven different metabolites were enriched, including Glycerol. This study provides an insight into blood metabolic changes related to DKD that may lead to more effective management strategies.

Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (n = 26), normoglycemic MetS patients (n = 30), and healthy (normoglycemic lean) subjects (n = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using highly sensitive ultra-high-performance liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). One-way ANOVA analysis revealed that 59 metabolites differed significantly among the three groups (p < 0.05). Glutamine, 5-hydroxy-L-tryptophan, L-sorbose, and hippurate were highly associated with MetS. However, 9-methyluric acid, sphinganine, and threonic acid were highly associated with prediabetes/MetS. Metabolic pathway analysis showed that arginine biosynthesis and glutathione metabolism were associated with MetS/prediabetes, while phenylalanine, D-glutamine and D-glutamate, and lysine degradation were highly impacted in MetS. The current study sheds light on the potential diagnostic value of some metabolites in metabolic syndrome and the role of their alteration on some of the metabolic pathways. More studies are needed in larger cohorts in order to verify the implication of the above metabolites on MetS and their diagnostic value.

Background: The functional interplay between tumor cells and their adjacent stroma has been suggested to play crucial roles in the initiation and progression of tumors and the effectiveness of chemotherapy. The extracellular matrix (ECM), a complex network of extracellular proteins, provides both physical and chemicals cues necessary for cell proliferation, survival, and migration. Understanding how ECM composition and biomechanical properties affect cancer progression and response to chemotherapeutic drugs is vital to the development of targeted treatments. Methods: 3D cell-derived-ECMs and esophageal cancer cell lines were used as a model to investigate the effect of ECM proteins on esophageal cancer cell lines response to chemotherapeutics. Immunohistochemical and qRT-PCR evaluation of ECM proteins and integrin gene expression was done on clinical esophageal squamous cell carcinoma biopsies. Esophageal cancer cell lines (WHCO1, WHCO5, WHCO6, KYSE180, KYSE 450 and KYSE 520) were cultured on decellularised ECMs (fibroblasts-derived ECM; cancer cell-derived ECM; combinatorial-ECM) and treated with 0.1% Dimethyl sulfoxide (DMSO), 4.2 µM cisplatin, 3.5 µM 5-fluorouracil and 2.5 µM epirubicin for 24 h. Cell proliferation, cell cycle progression, colony formation, apoptosis, migration and activation of signaling pathways were used as our study endpoints. Results: The expression of collagens, fibronectin and laminins was significantly increased in esophageal squamous cell carcinomas (ESCC) tumor samples compared to the corresponding normal tissue. Decellularised ECMs abrogated the effect of drugs on cancer cell cycling, proliferation and reduced drug induced apoptosis by 20–60% that of those plated on plastic. The mitogen-activated protein kinase-extracellular signal-regulated kinase (MEK-ERK) and phosphoinositide 3-kinase-protein kinase B (PI3K/Akt) signaling pathways were upregulated in the presence of the ECMs. Furthermore, our data show that concomitant addition of chemotherapeutic drugs and the use of collagen- and fibronectin-deficient ECMs through siRNA inhibition synergistically increased cancer cell sensitivity to drugs by 30–50%, and reduced colony formation and cancer cell migration. Conclusion: Our study shows that ECM proteins play a key role in the response of cancer cells to chemotherapy and suggest that targeting ECM proteins can be an effective therapeutic strategy against chemoresistant tumors.