Ultrafiltration-based Extraction and LC-MS/MS Quantification of Phenylalanine in Human Blood Sample for Metabolite Target Analysis

Background: Phenylalanine is a significant biomarker for various diseases like phenylketonuria, gastric cancers, and ischemic stroke according to recent studies. Methods: In the present study; a simple, sensitive, selective and novel analytical method was validated by using an ultrafiltration-based extraction and LC-MS/MS quantification of phenylalanine in human plasma using 13C phenylalanine heavy isotope. Amicon® Ultra Centrifugal Filter was used for ultrafiltration. Parameters affecting LC separation and MS/MS detection were investigated and optimized. Chromatographic separation was achieved on a Merck SeQuant ZIC-HILIC (100x4.6 mm, 5 μm) at a column temperature of 40°C using a mobile phase of mixture of acetonitrile containing 0.1% formic acid and water containing 0.1% formic acid (50:50 v/v) at a flow rate of 0.35 mL/min. The transitions m/z 167→121 for 13C phenylalanine, m/z 166→120 for phenylalanine itself were monitored using the MRM mode. Result: The assay was linear concentration range of 0.0025 μg/mL to 1.20 μg/mL (R2=0.999). The developed method was validated according to FDA guidelines. The method was found linear, sensitive, precise, accurate, and selective.

Environmental Microbiota Drives Microbial Succession and Metabolic Profiles during Chinese Liquor Fermentation

ABSTRACT Many microorganisms in the environment participate in the fermentation process of Chinese liquor. However, it is unknown to what extent the environmental microbiota influences fermentation. In this study, high-throughput sequencing combined with multiphasic metabolite target analysis was applied to study the microbial succession and metabolism changes during Chinese liquor fermentation from two environments (old and new workshops). SourceTracker was applied to evaluate the contribution of environmental microbiota to fermentation. Results showed that Daqu contributed 9.10 to 27.39% of bacterial communities and 61.06 to 80.00% of fungal communities to fermentation, whereas environments (outdoor ground, indoor ground, tools, and other unknown environments) contributed 62.61 to 90.90% of bacterial communities and 20.00 to 38.94% of fungal communities to fermentation. In the old workshop, six bacterial genera ( Lactobacillus [11.73% average relative abundance], Bacillus [20.78%], Pseudomonas [6.13%], Kroppenstedtia [10.99%], Weissella [16.64%], and Pantoea [3.40%]) and five fungal genera ( Pichia [55.10%], Candida [1.47%], Aspergillus [10.66%], Saccharomycopsis [22.11%], and Wickerhamomyces [3.35%]) were abundant at the beginning of fermentation. However, in the new workshop, the change of environmental microbiota decreased the abundances of Bacillus (5.74%), Weissella (6.64%), Pichia (33.91%), Aspergillus (7.08%), and Wickerhamomyces (0.12%), and increased the abundances of Pseudomonas (17.04%), Kroppenstedtia (13.31%), Pantoea (11.41%), Acinetobacter (3.02%), Candida (16.47%), and Kazachstania (1.31%). Meanwhile, in the new workshop, the changes of microbial community resulted in the increase of acetic acid, lactic acid, malic acid, and ethyl acetate, and the decrease of ethyl lactate during fermentation. This study showed that the environmental microbiota was an important source of fermentation microbiota and could drive both microbial succession and metabolic profiles during liquor fermentation. IMPORTANCE Traditional solid-state fermentation of foods and beverages is mainly carried out by complex microbial communities from raw materials, starters, and the processing environments. However, it is still unclear how the environmental microbiota influences the quality of fermented foods and beverages, especially for Chinese liquors. In this study, we utilized high-throughput sequencing, microbial source tracking, and multiphasic metabolite target analysis to analyze the origins of microbiota and the metabolic profiles during liquor fermentation. This study contributes to a deeper understanding of the role of environmental microbiota during fermentation.

Population Dynamics and Metabolite Target Analysis of Lactic Acid Bacteria during Laboratory Fermentations of Wheat and Spelt Sourdoughs

ABSTRACT Four laboratory sourdough fermentations, initiated with wheat or spelt flour and without the addition of a starter culture, were prepared over a period of 10 days with daily back-slopping. Samples taken at all refreshment steps were used for determination of the present microbiota. Furthermore, an extensive metabolite target analysis of more than 100 different compounds was performed through a combination of various chromatographic methods including liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry. The establishment of a stable microbial ecosystem occurred through a three-phase evolution within a week, as revealed by both microbiological and metabolite analyses. Strains of Lactobacillus plantarum, Lactobacillus fermentum, Lactobacillus rossiae, Lactobacillus brevis, and Lactobacillus paraplantarum were dominating some of the sourdough ecosystems. Although the heterofermentative L. fermentum was dominating one of the wheat sourdoughs, all other sourdoughs were dominated by a combination of obligate and facultative heterofermentative taxa. Strains of homofermentative species were not retrieved in the stable sourdough ecosystems. Concentrations of sugar and amino acid metabolites hardly changed during the last days of fermentation. Besides lactic acid, ethanol, and mannitol, the production of succinic acid, erythritol, and various amino acid metabolites, such as phenyllactic acid, hydroxyphenyllactic acid, and indolelactic acid, was shown during fermentation. Physiologically, they contributed to the equilibration of the redox balance. The biphasic approach of the present study allowed us to map some of the interactions taking place during sourdough fermentation and helped us to understand the fine-tuned metabolism of lactic acid bacteria, which allows them to dominate a food ecosystem.

PLANT AND FOOD METABOLOMICS IN THE POST-GENOMIC ERA: CONCEPTS, METHODOLOGIES AND APPLICATIONS

The metabolome (by analogy to genome, transcriptome, proteome) represents generally the total metabolite pool of a living organism, the entire complement of all the low molecular weight metabolites (small organic molecules, i.e. sugars, amino acids, flavours, acids, pigments, hormones) in biological samples such as a leaf, fruit, food, blood, etc. Metabolomics refers either to plants, microorganisms, food or animal and human organisms. Different specific aspects of fingerprinting, metabolic profile and metabolite target analysis are presented. A critical discussion of methodologies used in metabolomics is presented. Finally, there are mentioned the advantages offered by metabolomics versus genomics and their applications, i.e. a tremendous number of measurements to be done in short time and with high resolution and sensitivity, to realize “maps” of plants and their derived products.