Metabolomics for industrial fermentation

Metabolomics during the spontaneous fermentation in cocoa (Theobroma cacao L.): An exploraty review

Spontaneous fermentation is a process that depends on substrates' physical characteristics, crop variety, and postharvest practices; it induces variations in the metabolites that are responsible for the taste, aroma, and quality. Metabolomics makes it possible to detect key metabolites using chemometrics and makes it possible to establish patterns or identify biomarker behaviors under certain conditions at a given time. Therefore, sensitive and highly efficient analytical techniques allow for studying the metabolomic fingerprint changes during fermentation; which identify and quantify metabolites related to taste and aroma formation of an adequate processing time. This review shows that studying metabolomics in spontaneous fermentation permits the characterization of spontaneous fermentation in different stages. Also, it demonstrates the possibility of modulating the quality of cocoa by improving the spontaneous fermentation time (because of volatile aromatic compounds formation), thus standardizing the process to obtain attributes and quality that will later impact the chocolate quality.

Fluxomics - New Metabolomics Approaches to Monitor Metabolic Pathways

Fluxomics is an innovative -omics research field that measures the rates of all intracellular fluxes in the central metabolism of biological systems. Fluxomics gathers data from multiple different -omics fields, portraying the whole picture of molecular interactions. Recently, fluxomics has become one of the most relevant approaches to investigate metabolic phenotypes. Metabolic flux using 13C-labeled molecules is increasingly used to monitor metabolic pathways, to probe the corresponding gene-RNA and protein-metabolite interaction networks in actual time. Thus, fluxomics reveals the functioning of multi-molecular metabolic pathways and is increasingly applied in biotechnology and pharmacology. Here, we describe the main fluxomics approaches and experimental platforms. Moreover, we summarize recent fluxomic results in different biological systems.

Generic multicriteria approach to determine the best precipitation agent for removal of biomacromolecules prior to non-targeted metabolic analysis

The removal of biomacromolecules from biofluids decreases the sample complexity and lower electrospray suppression effects. Furthermore, it can increase the analysis sensitivity, precision, and selectivity. Often removal approaches evaluate the model based on a single criterion, like protein removed or response of one of few specific metabolites. In this study, we used a multicriteria approach to test the effect of using the solvents methanol and acetonitrile (organic solvent precipitation), trichloroacetic acid (acidic precipitation) and ammonium sulphate (salting out) to remove biomacromolecules from a downstream recovery process from a bacillus fermentation. The downstream recovery process intermediates were analysed using reversed-phase ultra-high-pressure liquid chromatography with electrospray ionisation and high-resolution time-of-flight mass spectrometry detection. To evaluate the pre-treatment agents the following multicriteria was applied i) practical considerations, ii) total amino acid in the precipitated pellet, iii) putative identification of the molecules removed or created by the different treatments, iv) coherence between high quality extracted ion chromatograms (repeatability of DW-CODA) and v) replicate consistency from principal component analysis score values obtained by using the CHEMometric analysis of sections of Selected Ion Chromatograms (CHEMSIC) method. This study presents a generic workflow to find the best pre-treatment for removing bio-macromolecules from biofluids with a multicriteria approach. In our case, the best protein removal strategy for downstream recovery intermediates was acetonitrile precipitation. This method showed high precision, created few artefact peaks compared to simple sample dilution, and mainly removed small peptides.

Systems metabolomics: from metabolomic snapshots to design principles

Metabolomics is a rapidly expanding technology that finds increasing application in a variety of fields, form metabolic disorders to cancer, from nutrition and wellness to design and optimization of cell factories. The integration of metabolic snapshots with metabolic fluxes, physiological readouts, metabolic models, and knowledge-informed Artificial Intelligence tools, is required to obtain a system-level understanding of metabolism. The emerging power of multi-omic approaches and the development of integrated experimental and computational tools, able to dissect metabolic features at cellular and subcellular resolution, provide unprecedented opportunities for understanding design principles of metabolic (dis)regulation and for the development of precision therapies in multifactorial diseases, such as cancer and neurodegenerative diseases.

A preliminary study on the impact of exogenous A-Factor analogue 1,4-butyrolactone on stimulating bitespiramycin biosynthesis

Bitespiramycin is composed of nine main acylated spiramycin components with isovaleryspiramycin as the major component. However, even with excellent therapeutic effects, its application and industrialization are restricted due to its low titer. In this study, the exogenous addition of A-Factor analogue 1,4-butyrolactone (1,4-BL) stimulated an improvement in bitespiramycin biological titer by 29% with a tiny influence on concentration of major component. Moreover, the mechanism of 1,4-BL stimulating effect was preliminarily explored by the analyses of three key enzyme activities, intracellular metabolite profiling and metabolic flux distribution. All results coordinately revealed that the extensive accumulation of methylmalonyl-CoA and acetyl-CoA was the direct reason for the enhanced bitespiramycin biosynthesis. This study would provide theoretical and technical basis for the application of 1,4-BL addition strategy to industrial bitespiramycin production.

Insulin resistance and metabonomics analysis of fatty liver haemorrhagic syndrome in laying hens induced by a high-energy low-protein diet

Fatty liver haemorrhagic syndrome (FLHS) is a widespread metabolic disease in laying hens that causes a decrease in egg production and even death. Insulin resistance is a major contributor to the pathogenesis of nonalcoholic fatty liver disease. However, the relationship between FLHS and the insulin resistance mechanisms underlying FLHS is not well elucidated. Therefore, we established an FLHS model induced by feeding a high-energy low-protein diet. In the current study, we found that the fasting glucose and insulin concentrations were elevated in the FLHS group compared with the control group during the experimental period. The results of the oral glucose tolerance test (OGTT) and insulin sensitivity test (IST) showed a high level of insulin resistance in the FLHS model. InsR, 4EBP-1, Glut-1 and Glut-3 mRNA expression were decreased, and TOR, S6K1, and FOXO1 were elevated (P < 0.05). Metabolomic analysis with GC/MS identified 46 differentially expressed metabolites between these two groups, and of these, 14 kinds of metabolism molecules and 32 kinds of small metabolism molecules were decreased (P < 0.05). Further investigation showed that glucose, lipid and amino acid metabolism blocks in the progression of FLHS by GO functional and pathway analysis. Overall, these results suggest that insulin resistance participated in FLHS; comprehensively, metabolites participated in the dysregulated biological process.

Evaluation of metabolome sample preparation and extraction methodologies for oleaginous filamentous fungi Mortierella alpina

INTRODUCTION

Metabolomics has been successfully applied to guide the rational engineering of industrial strains and improve the performance of bioprocesses. Mortierella alpina has traditionally been one of the most popular industrial strains for the production of polyunsaturated fatty acids. However, a systematic comparison and optimisation of the metabolomic analysis methods of M. alpina has not yet been reported.

OBJECTIVE

We sought to identify potential weaknesses that are important for accurate metabolomic analysis. We also aimed to determine an efficient sample preparation protocol for metabolomics studies in the oleaginous filamentous fungus M. alpina.

METHODS

In this study, using GC-MS, we evaluated three sample preparation protocols and five solvent mixtures by assessment of the metabolite profile differences, the sum of peak intensities and the reproducibility of metabolite quantification.

RESULTS

The freeze-dried biomass had better reproducibility and recovery than fresh biomass for metabolite extraction and data normalisation that is part of a metabolomics analysis of filamentous fungi M. alpina. Methanol:water (1:1) was superior for the profiling of metabolites in oleaginous fungi M. alpina. The unbiased metabolite profiling difference between the growth phase and lipids synthesis phase revealed that the degradation of amino acids were critical nodes for the efficient synthesis of lipids in M. alpina.

CONCLUSION

The use of freeze-dried biomass for metabolite extraction and data normalisation was more efficient at measuring the active state of the intracellular metabolites in M. alpina. We recommend extracting the intracellular metabolites with methanol:water (1:1). An important role of amino acid oxidation in the nitrogen limitation-mediated lipid accumulation was found.