Computational Design of Auxotrophy-Dependent Microbial Biosensors for Combinatorial Metabolic Engineering Experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools)

Genetical genomic determinants of alcohol consumption in rats and humans

Background: We have used a genetical genomic approach, in conjunction with phenotypic analysis of alcohol consumption, to identify candidate genes that predispose to varying levels of alcohol intake by HXB/BXH recombinant inbred rat strains. In addition, in two populations of humans, we assessed genetic polymorphisms associated with alcohol consumption using a custom genotyping array for 1,350 single nucleotide polymorphisms (SNPs). Our goal was to ascertain whether our approach, which relies on statistical and informatics techniques, and non-human animal models of alcohol drinking behavior, could inform interpretation of genetic association studies with human populations. Results: In the HXB/BXH recombinant inbred (RI) rats, correlation analysis of brain gene expression levels with alcohol consumption in a two-bottle choice paradigm, and filtering based on behavioral and gene expression quantitative trait locus (QTL) analyses, generated a list of candidate genes. A literature-based, functional analysis of the interactions of the products of these candidate genes defined pathways linked to presynaptic GABA release, activation of dopamine neurons, and postsynaptic GABA receptor trafficking, in brain regions including the hypothalamus, ventral tegmentum and amygdala. The analysis also implicated energy metabolism and caloric intake control as potential influences on alcohol consumption by the recombinant inbred rats. In the human populations, polymorphisms in genes associated with GABA synthesis and GABA receptors, as well as genes related to dopaminergic transmission, were associated with alcohol consumption. Conclusion: Our results emphasize the importance of the signaling pathways identified using the non-human animal models, rather than single gene products, in identifying factors responsible for complex traits such as alcohol consumption. The results suggest cross-species similarities in pathways that influence predisposition to consume alcohol by rats and humans. The importance of a well-defined phenotype is also illustrated. Our results also suggest that different genetic factors predispose alcohol dependence versus the phenotype of alcohol consumption

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Not AvailableThe increasing demand for crop production, given worldwide increases in the human population, puts pressure on moving natural resources towards sus-tainable development. This creates a big challenge for the upcoming generation. If improvement is not successful, there exists the unfortunate consequence that global food production may soon become insufficient to feed all of the world’s people. It is therefore essential that agricultural productivity be significantly increased in a more sustainable and environmentally friendly approach. Plant-beneficiary rhizo-bacteria (PBR) naturally activate microorganisms found in the soil. Because they are inexpensive, effective, and environmentally friendly, PBR are gaining impor-tance for use in crop production by restoring the soil’s natural fertility and protect-ing it against drought and soil diseases, thereby stimulating plant growth. PBR decrease the use of chemical fertilisers, pesticides, and artificial growth regulators; the intensive use of these inputs has led to severe health and environmental hazards, such as soil erosion, water contamination, pesticide poisoning, decreased ground-water table, water logging, surface crusting and depletion of biodiversity. The use of PBR has been proven to be an environmentally sound way of increasing crop yields by facilitating plant growth through either a direct or indirect mechanism with the aim of sustaining soil health over the long term. (7) (PDF) Towards Plant-Beneficiary Rhizobacteria and Agricultural Sustainability. Available from: https://www.researchgate.net/publication/325854138_Towards_Plant-Beneficiary_Rhizobacteria_and_Agricultural_Sustainability [accessed Nov 19 2018].Not Availabl