Dina Petranovic

Symptomatic atherosclerosis is associated with an altered gut metagenome

Recent findings have implicated the gut microbiota as a contributor of metabolic diseases through the modulation of host metabolism and inflammation. Atherosclerosis is associated with lipid accumulation and inflammation in the arterial wall, and bacteria have been suggested as a causative agent of this disease. Here we use shotgun sequencing of the gut metagenome to demonstrate that the genus Collinsella was enriched in patients with symptomatic atherosclerosis, defined as stenotic atherosclerotic plaques in the carotid artery leading to cerebrovascular events, whereas Roseburia and Eubacterium were enriched in healthy controls. Further characterization of the functional capacity of the metagenomes revealed that patient gut metagenomes were enriched in genes encoding peptidoglycan synthesis and depleted in phytoene dehydrogenase; patients also had reduced serum levels of β-carotene. Our findings suggest that the gut metagenome is associated with the inflammatory status of the host and patients with symptomatic atherosclerosis harbor characteristic changes in the gut metagenome.

Altered sterol composition renders yeast thermotolerant

Tricks for boosting yeasts ethanol yields To become a widely used source of fuel, widespread industrial production of ethanol using yeast needs to be simple and efficient. However, two conditions ideal for boosting production—tolerance of higher temperatures and high concentrations of ethanol—have been limiting (see the Perspective by Cheng and Kao). Now, Caspeta et al. have used adaptive laboratory evolution to find yeast strains that can tolerate high temperatures and Lam et al. have identified a route to improve yeasts resistance to high concentrations of ethanol. Science, this issue p. 75, p. 71; see also p. 35 Adaptive laboratory evolution can select for increased production of ethanol by yeast above 40°C. [Also see Perspective by Cheng and Kao] Ethanol production for use as a biofuel is mainly achieved through simultaneous saccharification and fermentation by yeast. Operating at ≥40°C would be beneficial in terms of increasing efficiency of the process and reducing costs, but yeast does not grow efficiently at those temperatures. We used adaptive laboratory evolution to select yeast strains with improved growth and ethanol production at ≥40°C. Sequencing of the whole genome, genome-wide gene expression, and metabolic-flux analyses revealed a change in sterol composition, from ergosterol to fecosterol, caused by mutations in the C-5 sterol desaturase gene, and increased expression of genes involved in sterol biosynthesis. Additionally, large chromosome III rearrangements and mutations in genes associated with DNA damage and respiration were found, but contributed less to the thermotolerant phenotype.

Bacterial single-stranded DNA-binding proteins are phosphorylated on tyrosine

Single-stranded DNA-binding proteins (SSBs) are required for repair, recombination and replication in all organisms. Eukaryotic SSBs are regulated by phosphorylation on serine and threonine residues. To our knowledge, phosphorylation of SSBs in bacteria has not been reported. A systematic search for phosphotyrosine-containing proteins in Streptomyces griseus by immunoaffinity chromatography identified bacterial SSBs as a novel target of bacterial tyrosine kinases. Since genes encoding protein-tyrosine kinases (PTKs) have not been recognized in streptomycetes, and SSBs from Streptomyces coelicolor (ScSSB) and Bacillus subtilis (BsSSB) share 38.7% identity, we used a B.subtilis protein-tyrosine kinase YwqD to phosphorylate two cognate SSBs (BsSSB and YwpH) in vitro. We demonstrate that in vivo phosphorylation of B.subtilis SSB occurs on tyrosine residue 82, and this reaction is affected antagonistically by kinase YwqD and phosphatase YwqE. Phosphorylation of B.subtilis SSB increased binding almost 200-fold to single-stranded DNA in vitro. Tyrosine phosphorylation of B.subtilis, S.coelicolor and Escherichia coli SSBs occured while they were expressed in E.coli, indicating that tyrosine phosphorylation of SSBs is a conserved process of post-translational modification in taxonomically distant bacteria.

Metabolic engineering of recombinant protein secretion by Saccharomyces cerevisiae

The yeast Saccharomyces cerevisiae is a widely used cell factory for the production of fuels and chemicals, and it is also provides a platform for the production of many heterologous proteins of medical or industrial interest. Therefore, many studies have focused on metabolic engineering S. cerevisiae to improve the recombinant protein production, and with the development of systems biology, it is interesting to see how this approach can be applied both to gain further insight into protein production and secretion and to further engineer the cell for improved production of valuable proteins. In this review, the protein post-translational modification such as folding, trafficking, and secretion, steps that are traditionally studied in isolation will here be described in the context of the whole system of protein secretion. Furthermore, examples of engineering secretion pathways, high-throughput screening and systems biology applications of studying protein production and secretion are also given to show how the protein production can be improved by different approaches. The objective of the review is to describe individual biological processes in the context of the larger, complex protein synthesis network.

Can yeast systems biology contribute to the understanding of human disease

Saccharomyces cerevisiae is a unicellular eukaryal microorganism that has traditionally been regarded either as a model system for investigating cellular physiology or as a cell factory for biotechnological use, for example for the production of fuels and commodity chemicals such as lactate or pharmaceuticals, including human insulin and HPV vaccines. Systems biology has recently gained momentum and has successfully been used for mapping complex regulatory networks and resolving the dynamics of signal transduction pathways. So far, yeast systems biology has mainly focused on the development of new methods and concepts. There are also some examples of the application of yeast systems biology for improving biotechnological processes. We discuss here how yeast systems biology could be used in elucidating fundamental cellular principles such as those relevant for the study of molecular mechanisms underlying complex human diseases, including the metabolic syndrome and ageing.

Integrated multilaboratory systems biology reveals differences in protein metabolism between two reference yeast strains

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.

Engineering of vesicle trafficking improves heterologous protein secretion in Saccharomyces cerevisiae

The yeast Saccharomyces cerevisiae is a widely used platform for the production of heterologous proteins of medical or industrial interest. However, heterologous protein productivity is often restricted due to the limitations of the host strain. In the protein secretory pathway, the protein trafficking between different organelles is catalyzed by the soluble NSF (N-ethylmaleimide-sensitive factor) receptor (SNARE) complex and regulated by the Sec1/Munc18 (SM) proteins. In this study, we report that over-expression of the SM protein encoding genes SEC1 and SLY1, improves the protein secretion in S. cerevisiae. Engineering Sec1p, the SM protein that is involved in vesicle trafficking from Golgi to cell membrane, improves the secretion of heterologous proteins human insulin precursor and α-amylase, and also the secretion of an endogenous protein invertase. Enhancing Sly1p, the SM protein regulating the vesicle fusion from endoplasmic reticulum (ER) to Golgi, increases α-amylase production only. Our study demonstrates that strengthening the protein trafficking in ER-to-Golgi and Golgi-to-plasma membrane process is a novel secretory engineering strategy for improving heterologous protein production in S. cerevisiae.

Different expression systems for production of recombinant proteins in Saccharomyces cerevisiae

Yeast Saccharomyces cerevisiae has become an attractive cell factory for production of commodity and speciality chemicals and proteins, such as industrial enzymes and pharmaceutical proteins. Here we evaluate most important expression factors for recombinant protein secretion: we chose two different proteins (insulin precursor (IP) and α‐amylase), two different expression vectors (POTud plasmid and CPOTud plasmid) and two kinds of leader sequences (the glycosylated alpha factor leader and a synthetic leader with no glycosylation sites). We used IP and α‐amylase as representatives of a simple protein and a multi‐domain protein, as well as a non‐glycosylated protein and a glycosylated protein, respectively. The genes coding for the two recombinant proteins were fused independently with two different leader sequences and were expressed using two different plasmid systems, resulting in eight different strains that were evaluated by batch fermentations. The secretion level (µmol/L) of IP was found to be higher than that of α‐amylase for all expression systems and we also found larger variation in IP production for the different vectors. We also found that there is a change in protein production kinetics during the diauxic shift, that is, the IP was produced at higher rate during the glucose uptake phase, whereas amylase was produced at a higher rate in the ethanol uptake phase. For comparison, we also refer to data from another study, (Tyo et al. submitted) in which we used the p426GPD plasmid (standard vector using URA3 as marker gene and pGPD1 as expression promoter). For the IP there is more than 10‐fold higher protein production with the CPOTud vector compared with the standard URA3‐based vector, and this vector system therefore represent a valuable resource for future studies and optimization of recombinant protein production in yeast. Biotechnol. Bioeng. 2012; 109:1259–1268.

Pharmaceutical protein production by yeast: Towards production of human blood proteins by microbial fermentation

Since the approval of recombinant insulin from Escherichia coli for its clinical use in the early 1980s, the amount of recombinant pharmaceutical proteins obtained by microbial fermentations has significantly increased. The recent advances in genomics together with high throughput analysis techniques (the so-called-omics approaches) and integrative approaches (systems biology) allow the development of novel microbial cell factories as valuable platforms for large scale production of therapeutic proteins. This review summarizes the main achievements and the current situation in the field of recombinant therapeutics using yeast Saccharomyces cerevisiae as a model platform, and discusses the future potential of this platform for production of blood proteins and substitutes.

Genome-Scale Modeling of the Protein Secretory Machinery in Yeast

The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking. Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm was developed which mimics secretory machinery and assigns each secretory protein to a particular secretory class that determines the set of PTMs and transport steps specific to each protein. Protein abundances were integrated with the model in order to gain system level estimation of the metabolic demands associated with the processing of each specific protein as well as a quantitative estimation of the activity of each component of the secretory machinery.