Growth-associated gene essentiality in Streptomyces coelicolor.

Lead Research Organisation: University of Surrey
Department Name: Microbial & Cellular Sciences


Streptomyces species have a large number of characteristics that are, presumably, redundant during rapid growth in submerged culture. These include morphological differentiation and secondary metabolism (e.g. antibiotic production). Despite this, Streptomyces fermenter cultures are used for the production of many bioproducts, in processes in which rapid, high density growth is of paramount importance. Many laboratories are trying to identify characteristics that would enhance the performance of Streptomyces species in fermenters, thereby defining the characteristics of a 'superhost' strain, capable of synthesising new products, with high efficiency. Streptomyces coelicolor was the first species in the genus to be sequenced and more is known about its molecular biology than that of any other species, so it is potentially a good candidate for development into a superhost. However, many find it very difficult to grow at rapid rates in fermenter culture. These ideas form the background to our interest in knowing how the requirements for different genes change as a function of growth rate. We are particularly interested in genes coding for enzymes that are part of the recently-published S coelicolor genome scale metabolic network, as we can carry out computer modelling that predicts the effect of deletion of each gene, represented in the network, on growth rate. Gene essentially is therefore, a relative term in modelling studies, some genes being 'more essential than others' depending on the effect that their deletion has on the growth rate. In this study, we plan to extend this quantitative essentiality concept to in vivo experimentation, with the application of one of two gene essentiality measurement protocols to cells growing at different rates. Thus we will determine which genes are essential at each growth rate and compare these findings to the computer predictions. We also have ideas for improving on existing prediction techniques and, a successful outcome to this project will enable us to validate the predictions with laboratory experiments, for the first time. We will compare those genes that seem to have growth rate related essentiality to those that are expressed in a rapidly growing strain, selected in a chemostat, a device that forces cells to grow at the rate that we specify. We will also force the parental strain to grow at different rates, using this apparatus, so that we can determine whether the genes whose expression responds to growth rate, are the same genes whose essentiality varies with the growth rate. Our in vivo gene essentiality experiment, using existing techniques, involves plating a population of mutants, in which every possible gene knock-out is represented, onto agar before we put them in the chemostat to determine which mutants can survive in the chemostat at each of a number of growth rates. It could be argued that this initial plating step is, itself, selective as only those capable of forming colonies on plates will make it into the chemostat. It may be that this will be inevitable, and should not unduly detract from the validity of our findings. However, we also plan an approach, never previously attempted in Streptomyces, that will not allow gene silencing mutations to manifest themselves, until the mutants are in the chemostat under the conditions that force them to grow at each specified rate. If we can make this new approach work (we have a team whose breadth of experience give us confidence that we will) then it will be used. If not, we will fall back on the more conventional approach.

Technical Summary

Using genome scale metabolic reaction networks, it is possible to estimate gene (reaction) essentiality by calculating the effect of a theoretical gene deletion on the predicted growth rate value. Hitherto, it has not been possible to test the validity of such predictions experimentally, using high-throughput methodology. Our intention is to perform a quantitative gene essentiality determination, using either a novel antisense gene silencing technique or transposon mutagenesis in chemostats in order to test the in silico predictions. The proposed experimental methodology is designed to identify genes whose essentiality varies as a function of growth rate so that we can do a direct comparison with model-generated essentiality values. We will also use microarray analysis to identify those genes whose expression varies with growth rate in our model strain (Streptomyces coelicolor M145) in order to determine whether they could have been predicted the by model. This experiment will also generate data that can be plugged into (constrain) the model to test our hypothesis that the response of calculated metabolic flux distributions to changes in growth rate can be used to generate a more precise quantitative estimate of gene essentiality. Finally, we will use chemostat culture, without mutagenesis, to select strains of S. coelicolor M145, adapted to vegetative growth in liquid culture at high growth rates. Microarray based examination of these strains will determine the value of in silico essentiality calculations for predicting genotypes for strains with bioproduction super-host properties (fast, reliable growth in fermenter culture). This programme offers the first opportunity to test predictions made using in silico gene essentiality estimation, a well-accepted technique whose validity has never been systematically evaluated. We will, therefore determine its utility as a resource for metabolic engineering and gene function investigation.


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