Convalescent plasma (CP) has emerged as a treatment for COVID-19. However, the composition and mechanism of action are not fully known. Therefore, we undertook a two-phase controlled study in which, first the immunological and metabolomic status of recovered and severe patients were evaluated. Secondly, the 28-day effect of CP on the immune response in severe patients was assessed. Nineteen recovered COVID-19 patients, 18 hospitalized patients with severe disease, and 16 pre-pandemic controls were included. Patients with severe disease were treated with CP transfusion and standard therapy (i.e., plasma recipients, n = 9) or standard therapy alone (n = 9). Clinical and biological assessments were done on day 0 and during follow-up on days 4, 7, 14, and 28. Clinical parameters, viral load, total immunoglobulin (Ig) G and IgA anti-S1-SARS-CoV-2 antibodies, neutralizing antibodies (NAbs), autoantibodies, cytokines, T and B cells, and metabolomic and lipidomic profiles were examined. Total IgG and IgA anti-S1-SARS-CoV-2 antibodies were key factors for CP selection and correlated with NAbs. In severe COVID-19 patients, mostly interleukin (IL)-6 (P = <0.0001), IL-10 (P = <0.0001), IP-10 (P = <0.0001), fatty acyls and glycerophospholipids were higher than in recovered patients. Latent autoimmunity and anti–IFN–α antibodies were observed in both recovered and severe patients. COVID-19 CP induced an early but transient cytokine profile modification and increases IgG anti-S1-SARS-CoV-2 antibodies. At day 28 post-transfusion, a decrease in activated, effector and effector memory CD4+ (P < 0.05) and activated and effector CD8+ (P < 0.01) T cells and naïve B cells (P = 0.001), and an increase in non-classical memory B cells (P=<0.0001) and central memory CD4+ T cells (P = 0.0252) were observed. Moreover, IL-6/IFN-γ (P = 0.0089) and IL-6/IL-10 (P = 0.0180) ratios decreased in plasma recipients compared to those who received standard therapy alone. These results may have therapeutic implications and justify further post-COVID-19 studies.

A search for extremophile organisms producing bioactive compounds led us to isolate a microalga identified as Galdieria sp. USBA-GBX-832 from acidic thermal springs. We have cultured Galdieria sp. USBA-GBX-832 under autotrophic, mixotrophic and heterotrophic conditions and determined variations of its production of biomass, lipids and PUFAs. Greatest biomass and PUFA production occurred under mixotrophic and heterotrophic conditions, but the highest concentration of lipids occurred under autotrophic conditions. Effects of variations of carbon sources and temperature on biomass and lipid production were evaluated and factorial experiments were used to analyze the effects of substrate concentration, temperature, pH, and organic and inorganic nitrogen on biomass production, lipids and PUFAs. Production of biomass and lipids was significantly dependent on temperature and substrate concentration. Greatest accumulation of PUFAs occurred at the lowest temperature tested. PUFA profiles showed trace concentrations of arachidonic acid (C_20:4) and eicosapentaenoic acid (C_20:5). This is the first time synthesis of these acids has been reported in Galdieria. These findings demonstrate that under heterotrophic conditions this microalga’s lipid profile is significantly different from those observed in other species of this genus which indicates that the culture conditions evaluated are key determinants of these organisms’ responses to stress conditions and accumulation of these metabolites.

In recent years, high-throughput lipid profiling has contributed to understand the biological, physiological and pathological roles of lipids in living organisms. Across all kingdoms of life, important cell and systemic processes are mediated by lipids including compartmentalization, signaling and energy homeostasis. Despite important advances in liquid chromatography and mass spectrometry, sample extraction procedures remain a bottleneck in lipidomic studies, since the wide structural diversity of lipids imposes a constrain in the type and amount of lipids extracted. Differences in extraction yield across lipid classes can induce a bias on down-stream analysis and outcomes. This review aims to summarize current lipid extraction techniques used for untargeted and targeted studies based on mass spectrometry. Considerations, applications, and limitations of these techniques are discussed when used to extract lipids in complex biological matrices, such as tissues, biofluids, foods, and microorganisms.

Background: Cachexia is a metabolic syndrome that affects up to 50–80% of cancer patients. The pathophysiology is characterized by a variable combination of reduced food intake and abnormal metabolism, including systemic inflammation and negative protein and energy balance. Despite its high clinical significance, defined diagnostic criteria and established therapeutic strategies are lacking. The ‘omics’ technologies provide a global view of biological systems. We hypothesize that blood‐based metabolomics might identify findings in cachectic patients that could provide clues to gain knowledge on its pathophysiology, and eventually postulate new therapeutic strategies.Methods: This is a cross‐sectional observational study in two cohorts of cancer patients, with and without cachexia. Patients were consecutively recruited from routine clinical practice of a General Oncology Department at ‘12 de Octubre’ University Hospital. Selected clinical and biochemical features were collected. Blood metabolite fingerprinting was performed using three analytical platforms, gas chromatography coupled to mass spectrometry (GC–MS), capillary electrophoresis coupled to mass spectrometry (CE–MS), and liquid chromatography coupled to mass spectrometry (LC–MS). Besides, we performed pathway‐based metabolite analyses to obtain more information on biological functions.Results: A total of 15 subjects were included in this study, 8 cachectic and 7 non‐cachectic patients. Metabolomic analyses were able to correctly classify their samples in 80% (GC–MS), 97% (CE–MS), 96% [LC–MS (positive mode)], and 89% [LC–MS (negative mode)] of the cases. The most prominent metabolic alteration in plasma of cachectic patients was the decrease of amino acids and derivatives [especially arginine, tryptophan, indolelactic acid, and threonine, with 0.4‐fold change (FC) compared with non‐cachectic patients], along with the reduction of glycerophospholipids [mainly lysophosphatidylcholines(O‐16:0) and lysophosphatidylcholines(20:3) sn‐1, FC = 0.1] and sphingolipids [SM(d30:0), FC = 0.5]. The metabolite with the highest increase was cortisol (FC = 1.6). Such alterations suggest a role of the following metabolic pathways in the pathophysiology of cancer cachexia: arginine and proline metabolism; alanine, aspartate, and glutamate metabolism; phenylalanine metabolism; lysine degradation; aminoacyl‐tRNA biosynthesis; fatty acid elongation in mitochondria; tricarboxylic acids cycle; among others.Conclusions: These findings suggest that plasma amino acids and lipids profiling has great potential to find the mechanisms involved in the pathogenesis of cachexia. Metabolic profiling of plasma from cancer patients show differences between cachexia and non‐cachexia in amino acids and lipids that might be related to mechanisms involved in its pathophysiology. A better understanding of these mechanisms might identify novel therapeutic approaches to palliate this unmet medical condition.