The Arabian camel is the largest known mammal that can survive in severe hot climatic conditions. We provide the molecular explanation for the thermotolerance of camel granulosa somatic cells after exposure to 45 °C for 2 (acute heat shock) or 20 h (chronic heat shock). The common features of the cellular responses to acute heat stress were the increase of heat shock proteins and DNA repair enzymes expression. Actin polymerization and Rho signaling were critically activated as a cellular defense against heat shock. Cells exposed to chronic heat shock showed altered cell architecture with a decrease in total detected proteins, metabolic enzymes, and cytoskeletal protein expression. Treatment with transforming growth factor beta (TGFβ) pathway inhibitor SB-431542 suppressed the morphological alterations of cells exposed to chronic heat shock. Moreover, during the recovery stage at 38 °C for 24 h, proteomic changes were partially restored with an exponential increase in HSP70 expression, and the cells restored their normal cellular morphology on the 9th day of recovery. Full proteomics data are available via ProteomeXchange with identifier PXD012159. The strategies of cellular defense and tolerance to both thermal conditions reflect the flexible adaptability of camel somatic cells to conserve life under extremely hot conditions.

Human SARS-CoV-2 and avian infectious bronchitis virus (IBV) are highly contagious and deadly coronaviruses, causing devastating respiratory diseases in humans and chickens. The lack of effective therapeutics exacerbates the impact of outbreaks associated with SARS-CoV-2 and IBV infections. Thus, novel drugs or therapeutic agents are highly in demand for controlling viral transmission and disease progression. Mesenchymal stem cells (MSC) secreted factors (secretome) are safe and efficient alternatives to stem cells in MSC-based therapies. This study aimed to investigate the antiviral potentials of human Wharton’s jelly MSC secretome (hWJ-MSC-S) against SARS-CoV-2 and IBV infections in vitro and in ovo. The half-maximal inhibitory concentrations (IC₅₀), cytotoxic concentration (CC₅₀), and selective index (SI) values of hWJ-MSC-S were determined using Vero-E6 cells. The virucidal, anti-adsorption, and anti-replication antiviral mechanisms of hWJ-MSC-S were evaluated. The hWJ-MSC-S significantly inhibited infection of SARS-CoV-2 and IBV, without affecting the viability of cells and embryos. Interestingly, hWJ-MSC-S reduced viral infection by >90%, in vitro. The IC₅₀ and SI of hWJ-MSC secretome against SARS-CoV-2 were 166.6 and 235.29 µg/mL, respectively, while for IBV, IC₅₀ and SI were 439.9 and 89.11 µg/mL, respectively. The virucidal and anti-replication antiviral effects of hWJ-MSC-S were very prominent compared to the anti-adsorption effect. In the in ovo model, hWJ-MSC-S reduced IBV titer by >99%. Liquid chromatography-tandem mass spectrometry (LC/MS-MS) analysis of hWJ-MSC-S revealed a significant enrichment of immunomodulatory and antiviral proteins. Collectively, our results not only uncovered the antiviral potency of hWJ-MSC-S against SARS-CoV-2 and IBV, but also described the mechanism by which hWJ-MSC-S inhibits viral infection. These findings indicate that hWJ-MSC-S could be utilized in future pre-clinical and clinical studies to develop effective therapeutic approaches against human COVID-19 and avian IB respiratory diseases.

Rhabdomyosarcoma (RMS), the most common pediatric soft tissue sarcoma, comprises embryonal (ERMS) and alveolar (ARMS) subtypes with distinct histopathological features, clinical outcomes, and therapeutic responses. To better characterize their molecular distinctions, we performed untargeted plasma proteomics and metabolomics profiling in children with ERMS (n = 18), ARMS (n = 17), and matched healthy controls (n = 18). Differential expression, functional enrichment (GO, KEGG, RaMP-DB), co-expression network analysis (WGCNA/WMCNA), and multi-omics integration (DIABLO, MOFA) revealed distinct molecular signatures for each subtype. ARMS displayed elevated oncogenic and stemness-associated proteins (e.g., cyclin E1, FAP, myotrophin) and metabolites involved in lipid transport, fatty acid metabolism, and polyamine biosynthesis. In contrast, ERMS was enriched in immune-related and myogenic proteins (e.g., myosin-9, SAA2, S100A11) and metabolites linked to glutamate/glycine metabolism and redox homeostasis. Pathway analyses highlighted subtype-specific activation of PI3K-Akt and Hippo signaling in ARMS and immune and coagulation pathways in ERMS. Additionally, the proteomics and metabolomics datasets showed association with clinical parameters, including disease stage, lymph node involvement, and age, demonstrating clear molecular discrimination consistent with clinical observation. Co-expression networks and integrative analyses further reinforced these distinctions, uncovering coordinated protein–metabolite modules. Our findings reveal novel, subtype-specific molecular programs in RMS and propose candidate biomarkers and pathways that may guide precision diagnostics and therapeutic targeting in pediatric sarcomas.

Metabolomics is a potential approach to paving new avenues for clinical diagnosis, molecular medicine, and therapeutic drug monitoring and development. The conventional metabolomics analysis pipeline depends on the data-independent acquisition (DIA) technique. Although powerful, it still suffers from stochastic, non-reproducible ion selection across samples. Despite the presence of different metabolomics workbenches, metabolite identification remains a tedious and time-consuming task. Consequently, sequential windowed acquisition of all theoretical MS (SWATH) acquisition has attracted much attention to overcome this limitation. This article aims to develop a novel SWATH platform for data analysis with a generation of an accurate mass spectral library for metabolite identification using SWATH acquisition. The workflow was validated using inclusion/exclusion compound lists. The false-positive identification was 3.4% from the non-endogenous drugs with 96.6% specificity. The workflow has proven to overcome background noise despite the complexity of the SWATH sample. From the Human Metabolome Database (HMDB), 1282 compounds were tested in various biological samples to demonstrate the feasibility of the workflow. The current study identified 377 compounds in positive and 303 in negative modes with 392 unique non-redundant metabolites. Finally, a free software tool, SASA, was developed to analyze SWATH-acquired samples using the proposed pipeline.

Fungal infection caused by invasive Aspergillus is a life-threatening complication in immunocompromised pediatric cancer patients. However, the early diagnosis of invasive infection remains a clinical challenge due to the lack of specific, non-invasive biomarkers. The current study investigates plasma metabolomic profiling integrated with an AI-derived fungal secondary metabolite database to identify potential biomarkers for rapid, non-invasive detection of Aspergillus infection. Plasma samples from thirteen pediatric oncology patients were analyzed using untargeted metabolomics based on UHPLC-MS/MS. Based on galactomannan assay results, three patients were classified as Aspergillus-Infected (AIC) and ten as non-infected controls (NPCs). An in-house custom database for secondary metabolites of fungi was incorporated to enhance metabolite annotation. Eight metabolites were found to be candidate biomarkers based on statistical significance, fold change, and biological relevance. In the AIC cohort, aflatoxin B1, aspergillimide, fumifungin, and uridine were found to be significantly elevated while citric acid presented a decrease. Multivariate analysis utilizing PCA and PLSDA showed distinct group separation. Moreover, sample size estimation indicates that a minimum of 25 participants would be needed in future studies for appropriate statistical power.

Meis1 is a transcription factor involved in numerous functions including development and proliferation and has been previously shown to harness cell cycle progression. In this study, we used in silico analysis to predict that miR-499-5p targets Meis1 and that Malat1 sponges miR-499-5p. For the first time, we demonstrated that the overexpression of miR-499-5p led to the downregulation of Meis1 mRNA and protein in C166 cells by directly binding to its 3’UTR. Moreover, knocking down Malat1 increased miR-499-5p expression, subsequently suppressing Meis1. Through BrdU incorporation assay, we showed that the knockdown of Malat1, Meis1, or mimicking with miR-499-5p promoted cell proliferation. Enrichment analyses on proteins identified via mass spectrometry after manipulating Malat1, miR-499-5p, or Meis1 revealed a multitude of differentially expressed proteins related to cell cycle, cell division, and key pathways like Wnt and mTOR, essential for cell proliferation. Collectively, our findings confirm that Malat1 sponges miR-499-5p, regulating Meis1, and that Malat1/miR-499-5p/Meis1 could potentially form an axis that has a pivotal influence on cellular proliferation.