Sastia Prama Putri

Current metabolomics: Technological advances

Metabolomics, the global quantitative assessment of metabolites in a biological system, has played a pivotal role in various fields of science in the post-genomic era. Metabolites are the result of the interaction of the systems genome with its environment and are not merely the end product of gene expression, but also form part of the regulatory system in an integrated manner. Therefore, metabolomics is often considered a powerful tool to provide an instantaneous snapshot of the physiology of a cell. The power of metabolomics lies on the acquisition of analytical data in which metabolites in a cellular system are quantified, and the extraction of the most meaningful elements of the data by using various data analysis tool. In this review, we discuss the latest development of analytical techniques and data analyses methods in metabolomics study.

Selection of Discriminant Markers for Authentication of Asian Palm Civet Coffee (Kopi Luwak): A Metabolomics Approach

Kopi Luwak, an exotic Indonesian coffee, is made from coffee berries that have been eaten by the Asian palm civet ( Paradoxurus hermaphroditus ). Despite being known as the worlds most expensive coffee, there is no reliable, standardized method for determining its authenticity. GC-MS-based multimarker profiling was employed to explore significant metabolites as discriminant markers for authentication. Extracts of 21 coffee beans ( Coffea arabica and Coffea canephora ) from three cultivation areas were analyzed and subjected to multivariate analyses, principal component analysis, and orthogonal projection to latent structures discriminant analysis. Citric acid, malic acid, and the inositol/pyroglutamic acid ratio were selected for further verification by evaluating their differentiating abilities against various commercial coffee products. The markers demonstrated potential application in the differentiation of original, fake Kopi Luwak, regular coffee, and coffee blend samples with 50 wt % Kopi Luwak content. This is the first report to address the selection and successful validation of discriminant markers for the authentication of Kopi Luwak.

Farinomalein, a maleimide-bearing compound from the entomopathogenic fungus Paecilomyces farinosus.

A new maleimide-bearing compound, farinomalein (1), was isolated from the entomopathogenic fungus Paecilomyces farinosus HF599. The structure was determined on the basis of spectroscopic analyses and chemical conversion. Compound 1 showed potent activity (5 mug/disk) against the plant pathogenic Phytophthora sojae P6497.

Metabolomics-driven approach to solving a CoA imbalance for improved 1-butanol production in Escherichia coli

High titer 1-butanol production in Escherichia coli has previously been achieved by overexpression of a modified clostridial 1-butanol production pathway and subsequent deletion of native fermentation pathways. This strategy couples growth with production as 1-butanol pathway offers the only available terminal electron acceptors required for growth in anaerobic conditions. With further inclusion of other well-established metabolic engineering principles, a titer of 15g/L has been obtained. In achieving this titer, many currently existing strategies have been exhausted, and 1-butanol toxicity level has been surpassed. Therefore, continued engineering of the host strain for increased production requires implementation of alternative strategies that seek to identify non-obvious targets for improvement. In this study, a metabolomics-driven approach was used to reveal a CoA imbalance resulting from a pta deletion that caused undesirable accumulation of pyruvate, butanoate, and other CoA-derived compounds. Using metabolomics, the reduction of butanoyl-CoA to butanal catalyzed by alcohol dehydrogenase AdhE2 was determined as a rate-limiting step. Fine-tuning of this activity and subsequent release of free CoA restored the CoA balance that resulted in a titer of 18.3g/L upon improvement of total free CoA levels using cysteine supplementation. By enhancing AdhE2 activity, carbon flux was directed towards 1-butanol production and undesirable accumulation of pyruvate and butanoate was diminished. This study represents the initial report describing the improvement of 1-butanol production in E. coli by resolving CoA imbalance, which was based on metabolome analysis and rational metabolic engineering strategies.

Quantitative target analysis and kinetic profiling of acyl-CoAs reveal the rate-limiting step in cyanobacterial 1-butanol production

Cyanobacterial 1-butanol production is an important model system for direct conversion of CO2 to fuels and chemicals. Metabolically-engineered cyanobacteria introduced with a heterologous Coenzyme A (CoA)-dependent pathway modified from Clostridium species can convert atmospheric CO2 into 1-butanol. Efforts to optimize the 1-butanol pathway in Synechococcus elongatus PCC 7942 have focused on the improvement of the CoA-dependent pathway thus, probing the in vivo metabolic state of the CoA-dependent pathway is essential for identifying its limiting steps. In this study, we performed quantitative target analysis and kinetic profiling of acyl-CoAs in the CoA-dependent pathway by reversed phase ion-pair liquid chromatography-triple quadrupole mass spectrometry. Using 13C-labelled cyanobacterial cell extract as internal standard, measurement of the intracellular concentration of acyl-CoAs revealed that the reductive reaction of butanoyl-CoA to butanal is a possible rate-limiting step. In addition, improvement of the butanoyl-CoA to butanal reaction resulted in an increased rate of acetyl-CoA synthesis by possibly compensating for the limitation of free CoA species. We inferred that the efficient recycling of free CoA played a key role in enhancing the conversion of pyruvate to acetyl-CoA.

A metabolomics-based strategy for identification of gene targets for phenotype improvement and its application to 1-butanol tolerance in Saccharomyces cerevisiae

BackgroundTraditional approaches to phenotype improvement include rational selection of genes for modification, and probability-driven processes such as laboratory evolution or random mutagenesis. A promising middle-ground approach is semi-rational engineering, where genetic modification targets are inferred from system-wide comparison of strains. Here, we have applied a metabolomics-based, semi-rational strategy of phenotype improvement to 1-butanol tolerance in Saccharomyces cerevisiae.ResultsNineteen yeast single-deletion mutant strains with varying growth rates under 1-butanol stress were subjected to non-targeted metabolome analysis by GC/MS, and a regression model was constructed using metabolite peak intensities as predictors and stress growth rates as the response. From this model, metabolites positively and negatively correlated with growth rate were identified including threonine and citric acid. Based on the assumption that these metabolites were linked to 1-butanol tolerance, new deletion strains accumulating higher threonine or lower citric acid were selected and subjected to tolerance measurement and metabolome analysis. The new strains exhibiting the predicted changes in metabolite levels also displayed significantly higher growth rate under stress over the control strain, thus validating the link between these metabolites and 1-butanol tolerance.ConclusionsA strategy for semi-rational phenotype improvement using metabolomics was proposed and applied to the 1-butanol tolerance of S. cerevisiae. Metabolites correlated with growth rate under 1-butanol stress were identified, and new mutant strains showing higher growth rate under stress could be selected based on these metabolites. The results demonstrate the potential of metabolomics in semi-rational strain engineering.

Metabolic distance estimation based on principle component analysis of metabolic turnover

Visualization of metabolic dynamism is important for various types of metabolic studies including studies on optimization of bio-production processes and studies of metabolism-related diseases. Many methodologies have been developed for metabolic studies. Among these, metabolic turnover analysis (MTA) is often used to analyze metabolic dynamics. MTA involves observation of changes in the isotopomer ratio of metabolites over time following introduction of isotope-labeled substrates. MTA has several advantages compared with (13)C-metabolic flux analysis, including the diversity of applicable samples, the variety of isotope tracers, and the wide range of target pathways. However, MTA produces highly complex data from which mining useful information becomes difficult. For easy understanding of MTA data, a new approach was developed using principal component analysis (PCA). The resulting PCA score plot visualizes the metabolic distance, which is defined as distance between metabolites on the real metabolic map. And the score plot gives us some hints of interesting metabolism for further study. We used this method to analyze the central metabolism of Saccharomyces cerevisiae under moderated aerobic conditions, and time course data for 77 isotopomers of 14 metabolites were obtained. The PCA score plot for this dataset represented a metabolic map and indicated interesting phenomena such as activity of fumarate reductase under aerated condition. These findings show the importance of a multivariate analysis to MTA. In addition, because the approach is not biased, this method has potential application for analysis of less-studied pathways and organisms.

Ophiosetin, a new tetramic acid derivative from the mycopathogenic fungus Elaphocordyceps ophioglossoides.

Ophiosetin, a new tetramic acid derivative from the mycopathogenic fungus Elaphocordyceps ophioglossoides

Quantification of coffee blends for authentication of Asian palm civet coffee (Kopi Luwak) via metabolomics: A proof of concept

Asian palm civet coffee (Kopi Luwak), an animal-digested coffee with an exotic feature, carries a notorious reputation of being the rarest and most expensive coffee beverage in the world. Considering that illegal mixture of cheap coffee into civet coffee is a growing concern among consumers, we evaluated the use of metabolomics approach and orthogonal projection to latent structures (OPLS) prediction technique to quantify the degree of coffee adulteration. Two prediction sets, consisting of certified and commercial coffee, were made from a blend of civet and regular coffee with eleven mixing percentages. The prediction model exhibited accurate estimation of coffee blend percentage thus, successfully validating the prediction and quantification of the mixing composition of known-unknown samples. This work highlighted proof of concept of metabolomics application to predict degree of coffee adulteration by determining the civet coffee fraction in blends.

Gas chromatography-mass spectrometry based metabolic profiling for the identification of discrimination markers of Angelicae Radix and its application to gas chromatography-flame ionization detector system.

Gas chromatography (GC)-based metabolomics technologies were applied for quality control of Angelicae Radix, an herbal medicine commonly used in Japan and China. Since Angelica roots are priced and graded differently based on their species and cultivation area, there is a need for a simple and reproducible method to discriminate Angelica roots. Here, we used GC-MS profiling data to construct a discrimination method for species and cultivation area of A. Radix. Seventy-six primary metabolites were identified. The quality factors of A. Radix were successfully classified using metabolic profiling and the orthogonal projections to latent structures-discriminant analysis (OPLS-DA) technique. Sorbitol and a glucose/4-aminobutyric acid combination were chosen as bio-markers from S-plot of OPLS-DA. Application of these selected bio-markers to a more practical and cost-efficient system, namely gas chromatography-flame ionization detector (GC-FID) system were also assessed. As a result, the same separations of sorbitol, glucose and 4-aminobutyric acid in box plots were obtained from GC-FID data. Our results demonstrate that GC-based metabolic markers can be readily applied for the establishment of a practical quality control method for A. Radix.