Handling variability and incompleteness of biological data by flexible nets: a case study for Wilson disease.

Mathematical models that combine predictive accuracy with explanatory power are central to the progress of systems and synthetic biology, but the heterogeneity and incompleteness of biological data impede our ability to construct such models. Furthermore, the robustness displayed by many biological systems means that they have the flexibility to operate under a range of physiological conditions and this is difficult for many modeling formalisms to handle. Flexible nets (FNs) address these challenges and represent a paradigm shift in model-based analysis of biological systems. FNs can: (i) handle uncertainties, ranges and missing information in concentrations, stoichiometry, network topology, and transition rates without having to resort to statistical approaches; (ii) accommodate different types of data in a unified model that integrates various cellular mechanisms; and (iii) be employed for system optimization and model predictive control. We present FNs and illustrate their capabilities by modeling a well-established system, the dynamics of glucose consumption by a microbial population. We further demonstrate the ability of FNs to take control actions in response to genetic or metabolic perturbations. Having bench-marked the system, we then construct the first quantitative model for Wilson disease-a rare genetic disorder that impairs copper utilization in the liver. We used this model to investigate the feasibility of using vitamin E supplementation therapy for symptomatic improvement. Our results indicate that hepatocytic inflammation caused by copper accumulation was not aggravated by limitations on endogenous antioxidant supplies, which means that treating patients with antioxidants is unlikely to be effective.

Cheaper faster drug development validated by the repositioning of drugs against neglected tropical diseases.

There is an urgent need to make drug discovery cheaper and faster. This will enable the development of treatments for diseases currently neglected for economic reasons, such as tropical and orphan diseases, and generally increase the supply of new drugs. Here, we report the Robot Scientist 'Eve' designed to make drug discovery more economical. A Robot Scientist is a laboratory automation system that uses artificial intelligence (AI) techniques to discover scientific knowledge through cycles of experimentation. Eve integrates and automates library-screening, hit-confirmation, and lead generation through cycles of quantitative structure activity relationship learning and testing. Using econometric modelling we demonstrate that the use of AI to select compounds economically outperforms standard drug screening. For further efficiency Eve uses a standardized form of assay to compute Boolean functions of compound properties. These assays can be quickly and cheaply engineered using synthetic biology, enabling more targets to be assayed for a given budget. Eve has repositioned several drugs against specific targets in parasites that cause tropical diseases. One validated discovery is that the anti-cancer compound TNP-470 is a potent inhibitor of dihydrofolate reductase from the malaria-causing parasite Plasmodium vivax.

Functional expression of parasite drug targets and their human orthologs in yeast.

BACKGROUND: The exacting nutritional requirements and complicated life cycles of parasites mean that they are not always amenable to high-throughput drug screening using automated procedures. Therefore, we have engineered the yeast Saccharomyces cerevisiae to act as a surrogate for expressing anti-parasitic targets from a range of biomedically important pathogens, to facilitate the rapid identification of new therapeutic agents. METHODOLOGY/PRINCIPAL FINDINGS: Using pyrimethamine/dihydrofolate reductase (DHFR) as a model parasite drug/drug target system, we explore the potential of engineered yeast strains (expressing DHFR enzymes from Plasmodium falciparum, P. vivax, Homo sapiens, Schistosoma mansoni, Leishmania major, Trypanosoma brucei and T. cruzi) to exhibit appropriate differential sensitivity to pyrimethamine. Here, we demonstrate that yeast strains (lacking the major drug efflux pump, Pdr5p) expressing yeast ((Sc)DFR1), human ((Hs)DHFR), Schistosoma ((Sm)DHFR), and Trypanosoma ((Tb)DHFR and (Tc)DHFR) DHFRs are insensitive to pyrimethamine treatment, whereas yeast strains producing Plasmodium ((Pf)DHFR and (Pv)DHFR) DHFRs are hypersensitive. Reassuringly, yeast strains expressing field-verified, drug-resistant mutants of P. falciparum DHFR ((Pf)dhfr(51I,59R,108N)) are completely insensitive to pyrimethamine, further validating our approach to drug screening. We further show the versatility of the approach by replacing yeast essential genes with other potential drug targets, namely phosphoglycerate kinases (PGKs) and N-myristoyl transferases (NMTs). CONCLUSIONS/SIGNIFICANCE: We have generated a number of yeast strains that can be successfully harnessed for the rapid and selective identification of urgently needed anti-parasitic agents.

Genome-wide assessment of the carriers involved in the cellular uptake of drugs: a model system in yeast.

BACKGROUND: The uptake of drugs into cells has traditionally been considered to be predominantly via passive diffusion through the bilayer portion of the cell membrane. The recent recognition that drug uptake is mostly carrier-mediated raises the question of which drugs use which carriers. RESULTS: To answer this, we have constructed a chemical genomics platform built upon the yeast gene deletion collection, using competition experiments in batch fermenters and robotic automation of cytotoxicity screens, including protection by 'natural' substrates. Using these, we tested 26 different drugs and identified the carriers required for 18 of the drugs to gain entry into yeast cells. CONCLUSIONS: As well as providing a useful platform technology, these results further substantiate the notion that the cellular uptake of pharmaceutical drugs normally occurs via carrier-mediated transport and indicates that establishing the identity and tissue distribution of such carriers should be a major consideration in the design of safe and effective drugs.

The yin and yang of yeast: biodiversity research and systems biology as complementary forces driving innovation in biotechnology.

The aim of this article is to review how yeast has contributed to contemporary biotechnology and to seek underlying principles relevant to its future exploitation for human benefit. Recent advances in systems biology combined with new knowledge of genome diversity promise to make yeast the eukaryotic workhorse of choice for production of everything from probiotics and pharmaceuticals to fuels and chemicals. The ability to engineer new capabilities through introduction of controlled diversity based on a complete understanding of genome complexity and metabolic flux is key. Here, we briefly summarise the history that has led to these apparently simple organisms being employed in such a broad range of commercial applications. Subsequently, we discuss the likely consequences of current yeast research for the future of biotechnological innovation.

Nutrient control of eukaryote cell growth: a systems biology study in yeast.

BACKGROUND: To elucidate the biological processes affected by changes in growth rate and nutrient availability, we have performed a comprehensive analysis of the transcriptome, proteome and metabolome responses of chemostat cultures of the yeast, Saccharomyces cerevisiae, growing at a range of growth rates and in four different nutrient-limiting conditions. RESULTS: We find significant changes in expression for many genes in each of the four nutrient-limited conditions tested. We also observe several processes that respond differently to changes in growth rate and are specific to each nutrient-limiting condition. These include carbohydrate storage, mitochondrial function, ribosome synthesis, and phosphate transport. Integrating transcriptome data with proteome measurements allows us to identify previously unrecognized examples of post-transcriptional regulation in response to both nutrient and growth-rate signals. CONCLUSIONS: Our results emphasize the unique properties of carbon metabolism and the carbon substrate, the limitation of which induces significant changes in gene regulation at the transcriptional and post-transcriptional level, as well as altering how many genes respond to growth rate. By comparison, the responses to growth limitation by other nutrients involve a smaller set of genes that participate in specific pathways. See associated commentary http://www.biomedcentral.com/1741-7007/8/62.

Conditional cell-wall mutants of Saccharomyces cerevisiae as delivery vehicles for therapeutic agents in vivo to the GI tract.

Strains of Saccharomyces cerevisiae capable of lysis upon conditional down-regulation of cell-wall biogenesis genes (SRB1 and PKC1) have been reported. Here, we show that they lyse and release recombinant protein not only under laboratory conditions, but (more importantly) under conditions found in the human stomach and duodenum. These findings provide proof that, in principle, such conditional lysis strains could be used as an integral part of a system for the oral delivery of therapeutic proteins. However, the current mechanism of conditional lysis is based on the use of the MET3 promoter which requires addition of methionine and cysteine for down-regulation of SRB1 and PKC1. This requirement makes it difficult to apply in vivo. We reasoned that promoters, suitable for in vivo down-regulation of lysis-inducing genes, could be identified amongst yeast genes whose transcript abundance is reduced under conditions found in the human gut. A microarray experiment identified a number of candidate genes with significantly reduced transcript levels under simulated human gut conditions. The greatest effects were seen with ANB1, TIR1, and MF(ALPHA)2), and we propose that their promoters have the potential to be used in vivo to achieve yeast lysis in the gut.

Using yeast to place human genes in functional categories.

The availability of the draft sequence of the human genome has created a pressing need to assign functions to each of the 35,000 or so genes that it defines. One useful approach for this purpose is to use model organisms for both bioinformatic and functional comparisons. We have developed a complementation system, based on the model eukaryote Saccharomyces cerevisiae, to clone human cDNAs that can functionally complement yeast essential genes. The system employs two regulatable promoters. One promoter, tetO (determining doxycycline-repressible expression), is used to control essential S. cerevisiae genes. The other, pMET3 (which is switched off in the presence of methionine), is employed to regulate the expression of mammalian cDNAs in yeast. We have demonstrated that this system is effective for both individual cDNA clones and for cDNA libraries, permitting the direct selection of functionally complementing clones. Three human cDNA libraries have been constructed and screened for clones that can complement specific essential yeast genes whose expression is switched off by the addition of doxycycline to the culture medium. The validity of each complementation was checked by showing that the yeast cells stop their growth in the presence of doxycycline and methionine, which represses the expression of the yeast and mammalian coding sequence, respectively. Using this system, we have screened 25 tetO replacement strains and succeeded in isolating human cDNAs complementing six essential yeast genes. In this way, we have uncovered a novel human ubiquitin-conjugating enzyme, have isolated a human cDNA clone that may function as a signal peptidase and have demonstrated that the functional segment of the human Psmd12 proteosome sub-unit contains a PINT domain.