Metabolite profiling highlights the effect of microbial intervention in the soaking step of tempe

Riyanto R.A., Fukusaki E., Putri S.P. Metabolite profiling highlights the effect of microbial intervention in the soaking step of tempe. International Journal of Food Science and Technology 59, 7414 (2024); https://doi.org/10.1111/ijfs.17481.Soaking of soybeans is an essential step in tempe fermentation. Owing to the uncontrolled microflora, spontaneous soaking during tempe production leads to inconsistencies in tempe quality. Common methods to control it include the addition of acids or microbial starters. Despite knowing the benefits, their impact on tempe's composition was less understood. In this study, prior to tempe fungal fermentation, soybeans were soaked with Lactiplantibacillus plantarum NBRC 101978 and Pichia burtonii NBRC 0844. Tempe samples were subjected to comprehensive analysis using a widely targeted gas chromatography–mass spectrometry (GC–MS) metabolomics approach and evaluation of physical characteristics. A total of 100 metabolites of sugars, amino acids, fatty acids, and organic acids were annotated in all samples. Principal component analysis (PCA) explaining 47.6% of the variance showed that microbial interventions led to alterations in the metabolome of all samples, including the accumulation of amino acids in lactic acid bacteria (LAB)-soaked soybean tempe and tyramine in yeast-soaked soybean tempe. Unlike chemically added soaked soybean tempe, microbial intervention significantly reduced the relative intensity levels of several sugars by more than twofold. Furthermore, microbial interventions in the tempe-soaking step significantly elevated the levels of bioactive metabolites more than twofold. The introduction of microbial interventions in the tempe-soaking step also influences the physical characteristics of the end product. These findings merit further consideration for tempe development and the food industry

GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA)

<p>Abstract</p> <p>Background</p> <p>The goal of metabolomics analyses is a comprehensive and systematic understanding of all metabolites in biological samples. Many useful platforms have been developed to achieve this goal. Gas chromatography coupled to mass spectrometry (GC/MS) is a well-established analytical method in metabolomics study, and 200 to 500 peaks are routinely observed with one biological sample. However, only ~100 metabolites can be identified, and the remaining peaks are left as "unknowns".</p> <p>Result</p> <p>We present an algorithm that acquires more extensive metabolite information. Pearson's product-moment correlation coefficient and the Soft Independent Modeling of Class Analogy (SIMCA) method were combined to automatically identify and annotate unknown peaks, which tend to be missed in routine studies that employ manual processing.</p> <p>Conclusions</p> <p>Our data mining system can offer a wealth of metabolite information quickly and easily, and it provides new insights, particularly into food quality evaluation and prediction.</p

Quality Improvement of Semi-Wet Terasi by Optimizing the Starter Culture Ratio of Controlled Fermentation

Terasi is a traditional fermented shrimp paste used in Indonesian dish as condiments. Due to its affordability, the paste is widely consumed among the general population, and thus has a great impact in Indonesia. Currently, small-scale or home industry is common for terasi production, and natural fermentation process is the traditional method. Fermentation process is considered complete when desired aromatic odors are obtained. However, this makes the fermentation process subjective, because the decision is solely dependent on the producer. Additionally, natural fermentation poses a higher risk for contamination of microbial pathogens. As a result, the quality of the final product varies greatly from region to region. Therefore, it is necessary to improve the quality of terasi by means of controlled fermentation. Hence, the objective of the research is to optimize the controlled fermentation condition of terasi by determining the most optimal ratio of mixed starter culture. Optimal fermentation conditions were determined by analyzing the effect of the various starter inoculum on the inner microbial community, and results indicated that mixed culture of Staphylococcus saprophyticus, Bacillus subtilis, and Lactobacillus murinus with ratio of 2:1:2 was the most effective for suppressing the growth of unwanted microorganisms. The difference in the microbial composition also resulted to a change in the metabolite profile of terasi

Comparison Between the Potential of Tempe Flour Made from Germinated and Nongerminated Soybeans in Preventing Diabetes Mellitus

This study was aimed to compare the chemical characteristics of tempe flour made from nongerminated soybean (NST) and germinated soybean (GST), especially on their capacity in preventing diabetes mellitus (DM). Soybeans were germinated for 20 hours in the dark until 2.5-5.0 mm of the radicle emerged. The ungerminated soybeans and the germinated soybeans were then processed into tempe and tempe flour. The two types of tempe flour were subjected to proximate analysis, amino acid profiling, antioxidant capacity, total phenol content, isoflavone content, and α-amylase and α-glucosidase enzyme inhibition analyses. GST was superior in preventing DM in the protein content and antioxidant parameters, as these were significantly higher (p&lt;0.05) than in NST. On the other hand, NST was superior in preventing diabetes in the isoflavon (daidzein, genistein, and total isoflavone) and α-amylase inhibition IC50 parameters which were significantly better (p&lt;0.05) than in GST. On the contrary, the diabetes-preventing parameters total phenols, α-glucosidase inhibition IC50, and insulinotropic amino acids (arginine, alanine, phenilalanine, isoleucine, leucine, and lysine) were not different (p&gt;0.05).&nbsp; Therefore, GST and NST both have potential in preventing diabetes through different mechanisms

Identification of potential quality markers in Indonesia’s Arabica specialty coffee using GC/MS-based metabolomics approach

Introduction: The cupping test is a widely used method for quality assessment of Arabica coffee. However, the cupping test is limited by the low number of certified panelists and the low throughput. Therefore, an analytical-based quality assessment may be a promising tool to complement the cupping test. A present, there is no report investigating quality marker candidates, focusing only on “specialty” grade Arabica coffee from Indonesia. Objective: This study identified the potential quality marker(s) in Arabica Specialty coffee at different stages (green beans, roasted beans, and brewed coffee. Methods: The metabolite profiles of ten different Arabica specialty-grade coffees were analyzed with different cup scores using gas chromatography–mass spectrometry (GC/MS). From the ten samples, green coffee beans, roasted coffee beans, and brewed coffee were selected. In addition, an orthogonal projection to latent structure (OPLS) regression analysis was conducted to obtain a potential quality marker based on the variable importance in projection (VIP). The potential quality marker(s) were validated by GC/MS metabolome profiling and OPLS analysis of different sets of samples consisting of 35 Arabica specialty-grade coffee samples. Results: In Arabica coffee samples, the OPLS model of the three stages showed galactinol to have a high VIP score. Galactinol showed a consistent positive correlation with cup scores at all stages of coffee production (green beans, roasted beans, and brewed coffee). The correlation suggests galactinol is a potential quality marker after further validation using different samples. Conclusion: GC/MS combined with OPLS regression analysis suggested galactinol as a quality marker and provide an early screening method for Arabica coffee quality that complements the cupping test performed by certified panelists.The version of record of this article, first published in Metabolomics, is available online at Publisher’s website: https://doi.org/10.1007/s11306-023-02051-

Expression Analysis of 1-aminocyclopropane-1-carboxylic Acid Oxidase Genes in Chitosan-Coated Banana

Banana is a climacteric fruit in which ethylene plays an important role in the regulation of the ripening process. Though it is the most produced fruit in Indonesia, the current post-harvest technologies for exporting this fruit are not economically friendly. Chitosan is one of economical biopolymer for edible coating which can extend fruit shelf-life. However, little study focused on the effect of chitosan coating has been done on gene expression level. In this study, the expression levels of several 1-aminocyclopropan-1-carboxylic acid oxidase (ACO) genes, which is an enzyme to convert 1-aminocyclopropan-1-carboxylic acid to ethylene in banana were analyzed on day 0, 1, 3, 5, 7, and 9 after ethylene treatment. As a result, one gene (ID: Ma01_t11540.1) had a similar expression pattern in both control and chitosan-coated bananas while the other genes (ID: Ma03_t02700.1, Ma05_t09360.1, Ma06_t02600.1, Ma10_t01130.1) showed different expression patterns. Among these genes, two genes (ID: Ma05_t09360.1, Ma10_t01130.1) were expressed higher than the other genes and the peak was observed on day 3. It was indicated that chitosan coating might activate the ethylene biosynthesis pathway in banana while it delayed fruit ripening

Novel mimetic tissue standards for precise quantitative mass spectrometry imaging of drug and neurotransmitter concentrations in rat brain tissues

The version of record of this article, first published in Analytical and Bioanalytical Chemistry, is available online at Publisher’s website: https://doi.org/10.1007/s00216-024-05477-5.Understanding the relationship between the concentration of a drug and its therapeutic efficacy or side effects is crucial in drug development, especially to understand therapeutic efficacy in central nervous system drug, quantifying drug-induced site-specific changes in the levels of endogenous metabolites, such as neurotransmitters. In recent times, evaluation of quantitative distribution of drugs and endogenous metabolites using matrix-assisted laser desorption/ionization (MALDI)-mass spectrometry imaging (MSI) has attracted much attention in drug discovery research. However, MALDI-MSI quantification (quantitative mass spectrometry imaging, QMSI) is an emerging technique, and needs to be further developed for practicable and convenient use in drug discovery research. In this study, we developed a reliable QMSI method for quantification of clozapine (antipsychotic drug) and dopamine and its metabolites in the rat brain using MALDI-MSI. An improved mimetic tissue model using powdered frozen tissue for QMSI was established as an alternative method, enabling the accurate quantification of clozapine levels in the rat brain. Furthermore, we used the improved method to evaluate drug-induced fluctuations in the concentrations of dopamine and its metabolites. This method can quantitatively evaluate drug localization in the brain and drug-induced changes in the concentration of endogenous metabolites, demonstrating the usefulness of QMSI

Drosophila Sirt2/mammalian SIRT3 deacetylates ATP synthase beta and regulates complex V activity

Adenosine triphosphate (ATP) synthase beta, the catalytic subunit of mitochondrial complex V, synthesizes ATP. We show that ATP synthase beta is deacetylated by a human nicotinamide adenine dinucleotide (NAD(+))-dependent protein deacetylase, sirtuin 3, and its Drosophila melanogaster homologue, dSirt2. dsirt2 mutant flies displayed increased acetylation of specific Lys residues in ATP synthase beta and decreased complex V activity. Overexpression of dSirt2 increased complex V activity. Substitution of Lys 259 and Lys 480 with Arg in human ATP synthase beta, mimicking deacetylation, increased complex V activity, whereas substitution with Gln, mimicking acetylation, decreased activity. Mass spectrometry and proteomic experiments from wild-type and dsirt2 mitochondria identified the Drosophila mitochondrial acetylome and revealed dSirt2 as an important regulator of mitochondrial energy metabolism. Additionally, we unravel a ceramide-NAD(+)-sirtuin axis wherein increased ceramide, a sphingolipid known to induce stress responses, resulted in depletion of NAD(+) and consequent decrease in sirtuin activity. These results provide insight into sirtuin-mediated regulation of complex V and reveal a novel link between ceramide and Drosophila acetylome

Saliva and Plasma Reflect Metabolism Altered by Diabetes and Periodontitis

Periodontitis is an inflammatory disorder caused by disintegration of the balance between the periodontal microbiome and host response. While growing evidence suggests links between periodontitis and various metabolic disorders including type 2 diabetes (T2D), non-alcoholic liver disease, and cardiovascular disease (CVD), which often coexist in individuals with abdominal obesity, factors linking periodontal inflammation to common metabolic alterations remain to be fully elucidated. More detailed characterization of metabolomic profiles associated with multiple oral and cardiometabolic traits may provide better understanding of the complexity of oral-systemic crosstalk and its underlying mechanism. We performed comprehensive profiling of plasma and salivary metabolomes using untargeted gas chromatography/mass spectrometry to investigate multivariate covariation with clinical markers of oral and systemic health in 31 T2D patients with metabolic comorbidities and 30 control subjects. Orthogonal partial least squares (OPLS) results enabled more accurate characterization of associations among 11 oral and 25 systemic clinical outcomes, and 143 salivary and 78 plasma metabolites. In particular, metabolites that reflect cardiometabolic changes were identified in both plasma and saliva, with plasma and salivary ratios of (mannose + allose):1,5-anhydroglucitol achieving areas under the curve of 0.99 and 0.92, respectively, for T2D diagnosis. Additionally, OPLS analysis of periodontal inflamed surface area (PISA) as the numerical response variable revealed shared and unique responses of metabolomic and clinical markers to PISA between healthy and T2D groups. When combined with linear regression models, we found a significant correlation between PISA and multiple metabolites in both groups, including threonate, cadaverine and hydrocinnamate in saliva, as well as lactate and pentadecanoic acid in plasma, of which plasma lactate showed a predominant trend in the healthy group. Unique metabolites associated with PISA in the T2D group included plasma phosphate and salivary malate, while those in the healthy group included plasma gluconate and salivary adenosine. Remarkably, higher PISA was correlated with altered hepatic lipid metabolism in both groups, including higher levels of triglycerides, aspartate aminotransferase and alanine aminotransferase, leading to increased risk of cardiometabolic disease based on a score summarizing levels of CVD-related biomarkers. These findings revealed the potential utility of saliva for evaluating the risk of metabolic disorders without need for a blood test, and provide evidence that disrupted liver lipid metabolism may underlie the link between periodontitis and cardiometabolic disease.Sakanaka A., Kuboniwa M., Katakami N., et al. Saliva and Plasma Reflect Metabolism Altered by Diabetes and Periodontitis. Frontiers in Molecular Biosciences, 8, , 742002. https://doi.org/https://doi.org/10.3389/fmolb.2021.742002