These numbers support the fact that our hubs are not essential ge

These numbers support the fact that our hubs are not essential genes for

growth, because a higher number of coincidences would be expected if hubs were essential genes. Two of the essential genes reported by Knuth et al. [58], siiF (STM4262) and dcoC, were among the genes selected for knockouts construction in our work, and contrary to their results, our analysis resulted in viable mutants. Similarly, at least another 46 of the reported essential genes in that study may actually be non-essential as independent studies AZD9291 concentration demonstrated that gene inactivation resulted in viable Metabolism inhibitor mutants [18]. We observed that the majority of double mutations did not result in growth defects or reduced ability to adapt to stress conditions with the exception of oxidative stress. On the other hand, two out of five double mutants showed JPH203 datasheet attenuation in mouse virulence. Many of the single non-redundant metabolic targets are already identified or too specific for Salmonella to be antibiotics targets [18]. A systematic approach to identify lethal double deletion using in silico modeling

has been undertaken resulting in a list of 56 putative synthetic double deletions affecting 80 genes [59]; however the phenotype of the predicted double mutants was not experimentally assessed. Only four of those 80 genes proposed as targets for double deletions, cysK and cysM, rfbA and rfbB, were detected as hubs in our networks. Indeed, the in silico approach of Thiele et al. [59] targeted to find essential pairs of genes and hubs seem to be non-essential genes. However, the hypothesis that targeting a number of hubs could cause the disruption of the cell main functionalities sooner than

if other less connected gene products are affected may lead to alternative approaches for identification of antibiotics targets. We have seen that the number of deleted hubs required for disruption of stress resistance and virulence in S. Typhimurium seems to be equal to or greater than 2. Adaptive laboratory evolution experiments with E. coli have Obatoclax Mesylate (GX15-070) demonstrated a linear increase of the number of accumulated mutations as the number of generations increases, so that 45 mutations were detected after 20000 generations [60]. Assuming that the number of virulence and stress genes affected by random mutation follows a hypergeometric distribution, the probability that 2 successive random mutations affect two hubs is approximately 10-4 and 14 mutations, i.e. more than 6000 generations, are needed to get a value greater than 0.01 for the probability of at least two hubs are randomly mutated. This probability may be lower if considering that cellular networks can be rewired and cell behavior completely different after such a number of mutations and generations take place.

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