The Impact of Acute Nutritional Interventions on the Plasma Proteome.

CONTEXT: Humans respond profoundly to changes in diet, while nutrition and environment have a great impact on population health. It is therefore important to deeply characterize the human nutritional responses. OBJECTIVE: Endocrine parameters and the metabolome of human plasma are rapidly responding to acute nutritional interventions such as caloric restriction or a glucose challenge. It is less well understood whether the plasma proteome would be equally dynamic, and whether it could be a source of corresponding biomarkers. METHODS: We used high-throughput mass spectrometry to determine changes in the plasma proteome of i) 10 healthy, young, male individuals in response to 2 days of acute caloric restriction followed by refeeding; ii) 200 individuals of the Ely epidemiological study before and after a glucose tolerance test at 4 time points (0, 30, 60, 120 minutes); and iii) 200 random individuals from the Generation Scotland study. We compared the proteomic changes detected with metabolome data and endocrine parameters. RESULTS: Both caloric restriction and the glucose challenge substantially impacted the plasma proteome. Proteins responded across individuals or in an individual-specific manner. We identified nutrient-responsive plasma proteins that correlate with changes in the metabolome, as well as with endocrine parameters. In particular, our study highlights the role of apolipoprotein C1 (APOC1), a small, understudied apolipoprotein that was affected by caloric restriction and dominated the response to glucose consumption and differed in abundance between individuals with and without type 2 diabetes. CONCLUSION: Our study identifies APOC1 as a dominant nutritional responder in humans and highlights the interdependency of acute nutritional response proteins and the endocrine system.

Functional proteomic profiling links deficient DNA clearance with increased mortality in individuals with severe COVID-19 pneumonia.

The factors that influence survival during severe infection are unclear. Extracellular chromatin drives pathology, but the mechanisms enabling its accumulation remain elusive. Here, we show that in murine sepsis models, splenocyte death interferes with chromatin clearance through the release of the DNase I inhibitor actin. Actin-mediated inhibition was compensated by upregulation of DNase I or the actin scavenger gelsolin. Splenocyte death and neutrophil extracellular trap (NET) clearance deficiencies were prevalent in individuals with severe COVID-19 pneumonia or microbial sepsis. Activity tracing by plasma proteomic profiling uncovered an association between low NET clearance and increased COVID-19 pathology and mortality. Low NET clearance activity with comparable proteome associations was prevalent in healthy donors with low-grade inflammation, implicating defective chromatin clearance in the development of cardiovascular disease and linking COVID-19 susceptibility to pre-existing conditions. Hence, the combination of aberrant chromatin release with defects in protective clearance mechanisms lead to poor survival outcomes.

Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection.

The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.

We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves the identification and quantification performance in conventional DIA proteomic applications, and is particularly beneficial for high-throughput applications, as it is fast and enables deep and confident proteome coverage when used in combination with fast chromatographic methods.

Metabolomics Analysis of the Osteogenic Differentiation of Umbilical Cord Blood Mesenchymal Stem Cells Reveals Differential Sensitivity to Osteogenic Agents.

Mesenchymal stem cells (MSCs) of fetal origin, such as umbilical cord blood MSCs (UCB MSCs), have emerged as a promising cell source for musculoskeletal tissue regeneration because of their higher proliferation potential, lack of donor site morbidity, and their off-the-shelf potential. MSCs differentiated toward the osteogenic lineage exhibit a specific metabolic phenotype characterized by reliance to oxidative phosphorylation for energy production and reduced glycolytic rates. Currently, limited information exists on the metabolic transitions at different stages of the osteogenic process after osteoinduction with different agents. Herein, the osteoinduction efficiency of BMP-2 and dexamethasone on UCB MSCs was assessed using gas chromatography-mass spectrometry (GC-MS) metabolomics analysis, revealing metabolic discrepancies at 7, 14, and 21 days of induction. Whereas both agents when administered individually were able to induce collagen I, osteocalcin, and osteonectin expression, BMP-2 was less effective than dexamethasone in promoting alkaline phosphatase expression. The metabolomics analysis revealed that each agent induced distinct metabolic alterations, including changes in amino acid pools, glutaminolysis, one-carbon metabolism, glycolysis, and tricarboxylic acid cycle. Importantly, we showed that in vitro-differentiated UCB MSCs acquire a metabolic physiology similar to primary osteoblasts when induced with dexamethasone but not with BMP-2, highlighting the fact that metabolomics analysis is sensitive enough to reveal potential differences in the osteogenic efficiency and can be used as a quality control assay for evaluating the osteogenic process.

The impact of succinate trace on pWW0 and ortho-cleavage pathway transcription in Pseudomonas putida mt-2 during toluene biodegradation.

Toluene is a pollutant catabolised through the interconnected pWW0 (TOL) and ortho-cleavage pathways of Pseudomonas putida mt-2, while upon succinate and toluene mixtures introduction in batch cultures grown on M9 medium, succinate was previously reported as non-repressing. The effect of a 40 times lower succinate concentration, as compared to literature values, was explored through systematic real-time qPCR monitoring of transcriptional kinetics of the key TOL Pu, Pm and ortho-cleavage PbenR, PbenA promoters in mixed-substrate experiments. Even succinate trace inhibited transcription leading to bi-modal promoters expression. Potential carbon catabolite repression mechanisms and novel expression patterns of promoters were unfolded. Lag phase was shortened and biomass growth levels increased compared to sole toluene biodegradation suggesting enhanced pollutant removal efficiency. The study stressed the noticeable effect of a preferred compound's left-over on the main route of a bioprocess, revealing the beneficiary supply of low preferred substrates concentrations to design optimal bioremediation strategies.

Human embryonic and induced pluripotent stem cells maintain phenotype but alter their metabolism after exposure to ROCK inhibitor.

Human pluripotent stem cells (hPSCs) are adhesion-dependent cells that require cultivation in colonies to maintain growth and pluripotency. Robust differentiation protocols necessitate single cell cultures that are achieved by use of ROCK (Rho kinase) inhibitors. ROCK inhibition enables maintenance of stem cell phenotype; its effects on metabolism are unknown. hPSCs were exposed to 10 µM ROCK inhibitor for varying exposure times. Pluripotency (TRA-1-81, SSEA3, OCT4, NANOG, SOX2) remained unaffected, until after prolonged exposure (96 hrs). Gas chromatography-mass spectrometry metabolomics analysis identified differences between ROCK-treated and untreated cells as early as 12 hrs. Exposure for 48 hours resulted in reduction in glycolysis, glutaminolysis, the citric acid (TCA) cycle as well as the amino acids pools, suggesting the adaptation of the cells to the new culture conditions, which was also reflected by the expression of the metabolic regulators, mTORC1 and tp53 and correlated with cellular proliferation status. While gene expression and protein levels did not reveal any changes in the physiology of the cells, metabolomics revealed the fluctuating state of the metabolism. The above highlight the usefulness of metabolomics in providing accurate and sensitive information on cellular physiological status, which could lead to the development of robust and optimal stem cell bioprocesses.

Designing a bio-inspired biomimetic in vitro system for the optimization of ex vivo studies of pancreatic cancer.

Pancreatic cancer is one of the most aggressive and lethal human malignancies. Drug therapies and radiotherapy are used for treatment as adjuvants to surgery, but outcomes remain disappointing. Advances in tissue engineering suggest that 3D cultures can reflect the in vivo tumor microenvironment and can guarantee a physiological distribution of oxygen, nutrients, and drugs, making them promising low-cost tools for therapy development. Here, we review crucial structural and environmental elements that should be considered for an accurate design of an ex vivo platform for studies of pancreatic cancer. Furthermore, we propose environmental stress response biomarkers as platform readouts for the efficient control and further prediction of the pancreatic cancer response to the environmental and treatment input.

Role of oxidative stress in Sclerotial differentiation and aflatoxin B1 biosynthesis in Aspergillus flavus.

We show here that oxidative stress is involved in both sclerotial differentiation (SD) and aflatoxin B1 biosynthesis in Aspergillus flavus. Specifically, we observed that (i) oxidative stress regulates SD, as implied by its inhibition by antioxidant modulators of reactive oxygen species and thiol redox state, and that (ii) aflatoxin B1 biosynthesis and SD are comodulated by oxidative stress. However, aflatoxin B1 biosynthesis is inhibited by lower stress levels compared to SD, as shown by comparison to undifferentiated A. flavus. These same oxidative stress levels also characterize a mutant A. flavus strain, lacking the global regulatory gene veA. This mutant is unable to produce sclerotia and aflatoxin B1. (iii) Further, we show that hydrogen peroxide is the main modulator of A. flavus SD, as shown by its inhibition by both an irreversible inhibitor of catalase activity and a mimetic of superoxide dismutase activity. On the other hand, aflatoxin B1 biosynthesis is controlled by a wider array of oxidative stress factors, such as lipid hydroperoxide, superoxide, and hydroxyl and thiyl radicals.

Metabolic profiling reveals that time related physiological changes in mammalian cell perfusion cultures are bioreactor scale independent.

Metabolic profiling was used to characterize the time course of cell physiology both in laboratory- and manufacturing-scale mammalian cell perfusion cultures. Two independent experiments were performed involving three vials from the same BHK cell bank, used to inoculate three laboratory-scale bioreactors, from which four manufacturing-scale cultures were initiated. It was shown that metabolomic analysis can indeed enhance the prime variable dataset for the monitoring of perfusion cultures by providing a higher resolution view of the metabolic state. Metabolic profiles could capture physiological state shifts over the course of the perfusion cultures and indicated a metabolic "signature" of the phase transitions, which was not observable from prime variable data. Specifically, the vast majority of metabolites had lower concentrations in the middle compared to the other two phases. Notably, metabolomics provided orthogonal (to prime variables) evidence that all cultures followed this same metabolic state shift with cell age, independently of bioreactor scale.