Riboflavin-LSD1 axis participates in the in vivo tumor-associated macrophage morphology in human colorectal liver metastases.

Tumor-associated macrophages (TAMs) are key components of the tumor microenvironment (TME). In colorectal liver metastasis (CLM), TAM morphology correlates with prognosis, with smaller TAMs (S-TAMs) conferring a more favorable prognosis than larger TAMs (L-TAMs). However, the metabolic profile of in vivo human TAM populations remains unknown. Multiparametric flow cytometry was used to freshly isolate S- and L-TAMs from surgically resected CLM patients (n = 14S-, 14L-TAMs). Mass spectrometry-based metabolomics analyses were implemented for the metabolic characterization of TAM populations. Gene expression analysis and protein activity were used to support the biochemical effects of the enzyme-substrate link between riboflavin and (lysine-specific demethylase 1A, LSD1) with TAM morphologies. L-TAMs were characterized by a positive correlation and a strong association between riboflavin and TAM morphologies. Riboflavin in both L-TAMs and in-vitro M2 polarized macrophages modulates LSD1 protein expression and activity. The inflammatory stimuli promoted by TNFα induced the increased expression of riboflavin transporter SLC52A3 and LSD1 in M2 macrophages. The modulation of the riboflavin-LSD1 axis represents a potential target for reprogramming TAM subtypes, paving the way for promising anti-tumor therapeutic strategies.

Mapping small metabolite changes after traumatic brain injury using AP-MALDI MSI.

Traumatic brain injury (TBI) is an alteration of brain function caused by a sudden transmission of an external force to the head. The biomechanical impact induces acute and chronic metabolic changes that highly contribute to injury evolution and outcome. TBI heterogeneity calls for approaches allowing the mapping of regional molecular and metabolic changes underpinning disease progression, with mass spectrometry imaging (MSI) as an efficient tool to study the spatial distribution of small metabolites. In this study, we applied an innovative targeted atmospheric pressure-MALDI mass spectrometry imaging (AP-MALDI MSI) approach, starting from an extensive list of metabolites, representative of different metabolic pathways, individually validated on the tissue under analysis with original standards using 2,5-dihydroxybenzoic acid (DHB), to characterize the impact of TBI on regional changes to small metabolites in the brain. Brains from sham and TBI mice obtained 21 days post-injury were analyzed to examine the spatial metabolic profile of small metabolites belonging to different metabolic pathways. By a whole brain analysis, we identified four metabolites (alanine, lysine, histidine, and inosine) with higher abundance in TBI than sham mice. Within the TBI group, lysine, histidine, and inosine were higher in the hemisphere ipsilateral to the biomechanical impact vs. the contralateral one. Images showed a major involvement of the ipsilateral thalamus characterized by the increase of arginine, lysine, histidine, and inosine and a significant reduction of glutamic acid, and N-acetylaspartic acid compared to the contralateral thalamus. These findings indicate high-resolution imaging mass spectrometry as a powerful tool to identify region-specific changes after a TBI to understand the metabolic changes underlying brain injury evolution.

Green-house gas fluxes and soil microbial functional genes abundance in saturated and drained peatlands in South-West Iceland.

The drainage of peatlands followed by land use conversion significantly impacts on the fluxes of green-house gases (GHGs, i.e. CO2, CH4, and N2O) to and from the atmosphere, driven by changes in soil properties and microbial communities. In this study, we compared saturated peatlands with drained ones used for sheep grazing or cultivated, which are common in South-West Iceland. These areas exhibit different degrees of soil saturation and nitrogen (N) content, reflecting the anthropic pressure gradient. We aimed at covering knowledge gaps about lack of estimates on N2O fluxes and drainage, by assessing the emissions of GHGs, and the impact of land conversion on these emissions. Moreover, we investigated soil microbial community functional diversity, and its connection with processes contributing to GHGs emission. GHGs emissions differed between saturated and drained peatlands, with increased soil respiration rates (CO2 emissions) and N mineralization (N2O), consistent with the trend of anthropogenic pressure. Drainage drastically reduced methane (CH4) emissions but increased CO2 emissions, resulting in a higher global warming potential (GWP). Cultivation, involving occasional tillage and fertilization, further increased N2O emissions, mediated by higher N availability and conditions favorable to nitrification. Functional genes mirrored the overall trend, showing a shift from prevalent methanogenic archaea (mcrA) in saturated peatlands to nitrifiers (amoA) in drained-cultivated areas. Environmental variables and nutrient content were critical factors affecting community composition in both environments, which overall affected the GHGs emissions and the relative contribution of the three gases.

Transcriptomic and metabolomic changes might predict frailty in SAMP8 mice.

Frailty is a geriatric, multi-dimensional syndrome that reflects multisystem physiological change and is a transversal measure of reduced resilience to negative events. It is characterized by weakness, frequent falls, cognitive decline, increased hospitalization and dead and represents a risk factor for the development of Alzheimer's disease (AD). The fact that frailty is recognized as a reversible condition encourages the identification of earlier biomarkers to timely predict and prevent its occurrence. SAMP8 (Senescence-Accelerated Mouse Prone-8) mice represent the most appropriate preclinical model to this aim and were used in this study to carry transcriptional and metabolic analyses in the brain and plasma, respectively, upon a characterization at cognitive, motor, structural, and neuropathological level at 2.5, 6, and 9 months of age. At 2.5 months, SAMP8 mice started displaying memory deficits, muscle weakness, and motor impairment. Functional alterations were associated with a neurodevelopmental deficiency associated with reduced neuronal density and glial cell loss. Through transcriptomics, we identified specific genetic signatures well distinguishing SAMP8 mice at 6 months, whereas plasma metabolomics allowed to segregate SAMP8 mice from SAMR1 already at 2.5 months of age by detecting constitutively lower levels of acylcarnitines and lipids in SAMP8 at all ages investigated correlating with functional deficits and neuropathological signs. Our findings suggest that specific genetic alterations at central level, as well as metabolomic changes in plasma, might allow to early assess a frail condition leading to dementia development, which paves the foundation for future investigation in a clinical setting.

Integrating metabolic profiling of pancreatic juice with transcriptomic analysis of pancreatic cancer tissue identifies distinct clinical subgroups.

Introduction: Metabolic reprogramming is a hallmark feature of pancreatic ductal adenocarcinoma (PDAC). A pancreatic juice (PJ) metabolic signature has been reported to be prognostic of oncological outcome for PDAC. Integration of PJ profiling with transcriptomic and spatial characterization of the tumor microenvironment would help in identifying PDACs with peculiar vulnerabilities. Methods: We performed a transcriptomic analysis of 26 PDAC samples grouped into 3 metabolic clusters (M_CL) according to their PJ metabolic profile. We analyzed molecular subtypes and transcriptional differences. Validation was performed by multidimensional imaging on tumor slides. Results: Pancreatic juice metabolic profiling was associated with PDAC transcriptomic molecular subtypes (p=0.004). Tumors identified as M_CL1 exhibited a non-squamous molecular phenotype and demonstrated longer survival. Enrichment analysis revealed the upregulation of immune genes and pathways in M_CL1 samples compared to M_CL2, the group with worse prognosis, a difference confirmed by immunofluorescence on tissue slides. Enrichment analysis of 39 immune signatures by xCell confirmed decreased immune signatures in M_CL2 compared to M_CL1 and allowed a stratification of patients associated with longer survival. Discussion: PJ metabolic fingerprints reflect PDAC molecular subtypes and the immune microenvironment, confirming PJ as a promising source of biomarkers for personalized therapy.