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Budding yeasts and fission yeasts are fascinating expression systems for industrial biotechnology. Yeasts are regarded as workhorses and the development of their molecular strategies have advanced the establishment of yeast expression systems for heterologous expression in relation to the production of valuable industrial-related compounds, such as biofuels, chemicals, pharmaceuticals, enzymes and food ingredients. Concerning the complexity of the host and product specific expression system, design and development therefore further leads to a requirement of systems biology. Throughout integrative analysis, a range of efficient yeast expression platforms have been designed and developed for the optimization of desirable recombinant product formation in industrial applications.

Metabolome profiling of biological systems has the powerful ability to provide the biological understanding of their metabolic functional states responding to the environmental factors or other perturbations. Tons of accumulative metabolomics data have thus been established since pre-metabolomics era. This is directly influenced by the high-throughput analytical techniques, especially mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based techniques. Continuously, the significant numbers of informatics techniques for data processing, statistical analysis, and data mining have been developed. The following tools and databases are advanced for the metabolomics society which provide the useful metabolomics information, e.g., the chemical structures, mass spectrum patterns for peak identification, metabolite profiles, biological functions, dynamic metabolite changes, and biochemical transformations of thousands of small molecules. In this chapter, we aim to introduce overall metabolomics studies from pre- to post-metabolomics era and their impact on society. Directing on post-metabolomics era, we provide a conceptual framework of informatics techniques for metabolomics and show useful examples of techniques, tools, and databases for metabolomics data analysis starting from preprocessing toward functional interpretation. Throughout the framework of informatics techniques for metabolomics provided, it can be further used as a scaffold for translational biomedical research which can thus lead to reveal new metabolite biomarkers, potential metabolic targets, or key metabolic pathways for future disease therapy.

In the yeast Saccharomyces cerevisiae many genes involved in lipid biosynthesis are transcriptionally controlled by inositol-choline and the protein kinase Snf1. Here we undertook a global study on how inositol-choline and Snf1 interact in controlling lipid metabolism in yeast. Using both a reference strain (CEN.PK113-7D) and a snf1Δ strain cultured at different nutrient limitations (carbon and nitrogen), at a fixed specific growth rate of 0.1 h(-1), and at different inositol choline concentrations, we quantified the expression of genes involved in lipid biosynthesis and the fluxes towards the different lipid components. Through integrated analysis of the transcriptome, the lipid profiling and the fluxome, it was possible to obtain a high quality, large-scale dataset that could be used to identify correlations and associations between the different components. At the transcription level, Snf1 and inositol-choline interact either directly through the main phospholipid-involving transcription factors (i.e. Ino2, Ino4, and Opi1) or through other transcription factors e.g. Gis1, Mga2, and Hac1. However, there seems to be flux regulation at the enzyme levels of several lipid involving enzymes. The analysis showed the strength of using both transcriptome and lipid profiling analysis for mapping the co-influence of inositol-choline and Snf1 on phospholipid metabolism.

The morphological development and the sequence of organogenesis from glochidium to the early juvenile stage of the freshwater pearl mussel, Hyriopsis bialatus, were observed. Larvae of H. bialatus were cultured in standard tissue culture medium (M199) supplemented with common carp (Cyprinus carpio) plasma and they showed transformation within 10 days. Larval samples were collected every 2 days during glochidia development and subjected to histological processing. Three types of cell masses were developed during this period: the ventral plate (the foot rudiment), lateral pits (the gill rudiment), and the oral plate or endodermic sac (the origin of the digestive tract). The ventral plate gave rise to two foot lobes which fused into a single lobe. The gills were developed from the lateral pits next to the ventral plate, forming a pair of gill buds that became elongated and turned into gill bars. The digestive tract began with the formation of mouth by invagination of the oral plate (or endodermic sac) and fo...

We present a fast and accurate method for preparation of fatty acid methyl esters (FAMEs) using microwave-assisted derivatization of fatty acids present in yeast samples. The esterification of free/bound fatty acids to FAMEs was completed within 5 min, which is 24 times faster than with conventional heating methods. The developed method was validated in two ways: (1) through comparison with a conventional method (hot plate) and (2) through validation with the standard reference material (SRM) 3275-2 omega-3 and omega-6 fatty acids in fish oil (from the Nation Institute of Standards and Technology, USA). There were no significant differences (P > 0.05) in yields of FAMEs with both validations. By performing a simple modification of closed-vessel microwave heating, it was possible to carry out the esterification in Pyrex glass tubes kept inside the closed vessel. Hereby, we are able to increase the number of sample preparations to several hundred samples per day as the time for preparation of reused vessels was eliminated. Pretreated cell disruption steps are not required, since the direct FAME preparation provides equally quantitative results. The new microwave-assisted derivatization method facilitates the preparation of FAMEs directly from yeast cells, but the method is likely to also be applicable for other biological samples.

Nutrient sensing and coordination of metabolic pathways are crucial functions for living cells. A combined analysis of the yeast transcriptome, phosphoproteome and metabolome is used to investigate the interactions between the Snf1 and TORC1 pathways under nutrient-limited conditions., Snf1 regulates a broad range of biological processes, while target of rapamycin complex 1 (TORC1) seems to be repressed under both glucose- and ammonium-limited conditions. Snf1 has a role in regulating amino acids by upregulating the NADP+-dependent glutamate dehydrogenase (encoded by GDH3) under glucose-limited condition. In addition to the accepted role of Snf1 in regulating fatty acid (FA) metabolism, TORC1 may also regulate FA metabolism. Direct interactions between Snf1 and TORC1 pathways are unlikely under nutrient-limited conditions and TORC1 might be repressed in a manner that is independent of Snf1., Nutrient sensing and coordination of metabolic pathways are crucial functions for all living cells, but details of the coordination under different environmental conditions remain elusive. We therefore undertook a systems biology approach to investigate the interactions between the Snf1 and the target of rapamycin complex 1 (TORC1) in Saccharomyces cerevisiae. We show that Snf1 regulates a much broader range of biological processes compared with TORC1 under both glucose- and ammonium-limited conditions. We also find that Snf1 has a role in upregulating the NADP+-dependent glutamate dehydrogenase (encoded by GDH3) under derepressing condition, and therefore may also have a role in ammonium assimilation and amino-acid biosynthesis, which can be considered as a convergence of Snf1 and TORC1 pathways. In addition to the accepted role of Snf1 in regulating fatty acid (FA) metabolism, we show that TORC1 also regulates FA metabolism, likely through modulating the peroxisome and β-oxidation. Finally, we conclude that direct interactions between Snf1 and TORC1 pathways are unlikely under nutrient-limited conditions and propose that TORC1 is repressed in a manner that is independent of Snf1.

There is increasing interest in bioengineering of lipids for use in functional foods, pharmaceuticals, and biofuels. Saccharomyces cerevisiae is a widely utilized cell factory for biotechnological production, thus a tempting alternative. Herein, we show how its neutral lipid accumulation varies throughout metabolic phases under nutritional conditions relevant for large-scale fermentation. Population-averaged metabolic data were correlated with lipid storage at the single-cell level monitored at submicron resolution by label-free coherent anti-Stokes Raman scattering (CARS) microscopy. While lipid droplet sizes are fairly constant, the number of droplets is a dynamic parameter determined by glucose and ethanol levels. The lowest number of lipid droplets is observed in the transition phase between glucose and ethanol fermentation. It is followed by a buildup during the ethanol phase. The surplus of accumulated lipids is then mobilized at concurrent glucose and ethanol starvation in the subsequent stationary phase. Thus, the highest amount of lipids is found in the ethanol phase, which is about 0.3 fL/cell. Our results indicate that the budding yeast, S. cerevisiae, can be used for the biosynthesis of lipids and demonstrate the strength of CARS microscopy for monitoring the dynamics of lipid metabolism at the single-cell level of importance for optimized lipid production.

The field of systems biology is often held back by difficulties in obtaining comprehensive, high-quality, quantitative data sets. In this paper, we undertook an interlaboratory effort to generate such a data set for a very large number of cellular components in the yeast Saccharomyces cerevisiae, a widely used model organism that is also used in the production of fuels, chemicals, food ingredients and pharmaceuticals. With the current focus on biofuels and sustainability, there is much interest in harnessing this species as a general cell factory. In this study, we characterized two yeast strains, under two standard growth conditions. We ensured the high quality of the experimental data by evaluating a wide range of sampling and analytical techniques. Here we show significant differences in the maximum specific growth rate and biomass yield between the two strains. On the basis of the integrated analysis of the high-throughput data, we hypothesize that differences in phenotype are due to differences in protein metabolism. © 2010 Macmillan Publishers Limited. All rights reserved.

Several reports have shown antimicrobial and anticancer activities of mucous glycoproteins extracted from the giant African snail Achatina fulica. Anticancer properties of the snail mucous peptides remain incompletely revealed. The aim of this study was to predict anticancer peptides from A. fulica mucus. Two of HPLC-separated mucous fractions (F2 and F5) showed in vitro cytotoxicity against the breast cancer cell line (MCF-7) and normal epithelium cell line (Vero). According to the mass spectrometric analysis, 404 and 424 peptides from the F2 and F5 fractions were identified. Our comprehensive bioinformatics workflow predicted 16 putative cationic and amphipathic anticancer peptides with diverse structures from these two peptidome data. These peptides would be promising molecules for new anti-breast cancer drug development.