Attenuated strains of mycobacteria can be exploited to determine genes essential for their pathogenesis and persistence. To this goal, we sequenced the genome of H37Ra, an attenuated variant of Mycobacterium tuberculosis H37Rv strain. Comparison with H37Rv revealed three unique coding region polymorphisms. One polymorphism was located in the DNA-binding domain of the transcriptional regulator PhoP, causing the protein's diminished DNA-binding capacity. Temporal gene expression profiles showed that several genes with reduced expression in H37Ra were also repressed in an H37Rv phoP knockout strain. At later time points, genes of the dormancy regulon, typically expressed in a state of nonreplicating persistence, were upregulated in H37Ra. Complementation of H37Ra with H37Rv phoP partially restored its persistence in a murine macrophage infection model. Our approach demonstrates the feasibility of identifying minute but distinct differences between isogenic strains and illustrates the consequences of single point mutations on the survival stratagem of M. tuberculosis.

We propose a facile fluorometric system for detection of gene mutations using graphene oxide (GO). A fluorescent probe DNA anneals to a specific mutant gene and is degraded by the 5'→ 3' exonuclease activity of Taq polymerase during PCR, and the released fluorophore retains fluorescence after addition of GO without quenching.

Organisms respond to changes in their environment over a wide range of biological and temporal scales. Such phenotypic plasticity can involve developmental, behavioral, physiological, and genetic shifts. The adaptive value of a plastic response is known to depend on the nature of the information that is available to the organism as well as the direct and indirect costs of the plastic response. We modeled the dynamic process of simple gene regulatory networks as they responded to temporal fluctuations in environmental conditions. We simulated the evolution of networks to determine when genes that function solely as transcription factors, with no direct function of their own, are beneficial to the function of the network. When there is perfect information about the environment and there is no timing information to be extracted then there is no advantage to adding pure transcription factor genes to the network. In contrast, when there is either timing information that can be extracted or only indirect information about the current state of the environment then additional transcription factor genes improve the evolved network fitness.