MSIpixel: a fully automated pipeline for compound annotation and quantitation in mass spectrometry imaging experiments.

Mass spectrometry imaging (MSI) is commonly used to map the spatial distribution of small molecules within complex biological matrices. One of the major challenges in imaging MS-based spatial metabolomics is molecular identification and metabolite annotation, to address this limitation, annotation is often complemented with parallel bulk LC-MS2-based metabolomics to confirm and validate identifications. Here we applied MSI method, utilizing data-dependent acquisition, to visualize and identify unknown molecules in a single instrument run. To reach this aim we developed MSIpixel, a fully automated pipeline for compound annotation and quantitation in MSI experiments. It overcomes challenges in molecular identification, and improving reliability and comprehensiveness in MSI-based spatial metabolomics.

Prolonged exposure to simulated microgravity promotes stemness impairing morphological, metabolic and migratory profile of pancreatic cancer cells: a comprehensive proteomic, lipidomic and transcriptomic analysis.

BACKGROUND: The impact of the absence of gravity on cancer cells is of great interest, especially today that space is more accessible than ever. Despite advances, few and contradictory data are available mainly due to different setup, experimental design and time point analyzed. METHODS: Exploiting a Random Positioning Machine, we dissected the effects of long-term exposure to simulated microgravity (SMG) on pancreatic cancer cells performing proteomic, lipidomic and transcriptomic analysis at 1, 7 and 9 days. RESULTS: Our results indicated that SMG affects cellular morphology through a time-dependent activation of Actin-based motility via Rho and Cdc42 pathways leading to actin rearrangement, formation of 3D spheroids and enhancement of epithelial-to-mesenchymal transition. Bioinformatic analysis reveals that SMG may activates ERK5/NF-κB/IL-8 axis that triggers the expansion of cancer stem cells with an increased migratory capability. These cells, to remediate energy stress and apoptosis activation, undergo a metabolic reprogramming orchestrated by HIF-1α and PI3K/Akt pathways that upregulate glycolysis and impair ß-oxidation, suggesting a de novo synthesis of triglycerides for the membrane lipid bilayer formation. CONCLUSIONS: SMG revolutionizes tumor cell behavior and metabolism leading to the acquisition of an aggressive and metastatic stem cell-like phenotype. These results dissect the time-dependent cellular alterations induced by SMG and pave the base for altered gravity conditions as new anti-cancer technology.

Large-Scale Plasma Analysis Revealed New Mechanisms and Molecules Associated with the Host Response to SARS-CoV-2.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to nearly every continent, registering over 1,250,000 deaths worldwide. The effects of SARS-CoV-2 on host targets remains largely limited, hampering our understanding of Coronavirus Disease 2019 (COVID-19) pathogenesis and the development of therapeutic strategies. The present study used a comprehensive untargeted metabolomic and lipidomic approach to capture the host response to SARS-CoV-2 infection. We found that several circulating lipids acted as potential biomarkers, such as phosphatidylcholine 14:0_22:6 (area under the curve (AUC) = 0.96), phosphatidylcholine 16:1_22:6 (AUC = 0.97), and phosphatidylethanolamine 18:1_20:4 (AUC = 0.94). Furthermore, triglycerides and free fatty acids, especially arachidonic acid (AUC = 0.99) and oleic acid (AUC = 0.98), were well correlated to the severity of the disease. An untargeted analysis of non-critical COVID-19 patients identified a strong alteration of lipids and a perturbation of phenylalanine, tyrosine and tryptophan biosynthesis, phenylalanine metabolism, aminoacyl-tRNA degradation, arachidonic acid metabolism, and the tricarboxylic acid (TCA) cycle. The severity of the disease was characterized by the activation of gluconeogenesis and the metabolism of porphyrins, which play a crucial role in the progress of the infection. In addition, our study provided further evidence for considering phospholipase A2 (PLA2) activity as a potential key factor in the pathogenesis of COVID-19 and a possible therapeutic target. To date, the present study provides the largest untargeted metabolomics and lipidomics analysis of plasma from COVID-19 patients and control groups, identifying new mechanisms associated with the host response to COVID-19, potential plasma biomarkers, and therapeutic targets.