How does T7 deal with Uncertainty

From OpenWetWare

(Redirected from T7 Uncertainty)
Jump to: navigation, search

Contents

Background

Bacteriophage T7 is an obligate lytic phage that infects E. coli. An individual T7 particular must undergo productive infection in the face of varying host states and infection conditions. One example is variation in the Multiplicity of Infection of T7. Transcription and translation of a few low copy genes is unlikely to pose a noticeable expression load on either cell. The initial production of mRNA and protein during infection is likely proportional to the amounts of phage DNA in the cell and therefore the multiplicity of infection (MOI). However, it has been observed that infection at an average MOI ranging from 1 to 20 has no effect on the total phage output or the latent period of the infection (Endy, unpublished). In addition, there are other sources of variation where T7 undergoes productive infection such as cell size, growth conditions, extrinsic noise, and genotype of the host.

The ability for T7 to efficiently undergo productive development in the face of such variation is, in our estimation, due in part to its feedback controls on transcription. These feedback controls are mediated by proteins encoded on the T7 genome. First Gp0.7, through an unknown mechanism, and then Gp2, by direct binding, act in concert to shut down transcription by host RNA polymerase (RNAP) and thus expression from host DNA (Nechaev & Severinov, 1999; Hesselbach & Nakada, 1977; Brunovskis & Summers, 1972). This feedback mechanism also allows for further differentiation between class I genes and those genes transcribed by the phage RNA polymerase, Gp1 (class II and class III genes). Later in the infection cycle, T7 lysozyme (gp3.5) inhibits the function of gp1 by the formation of a 1:1 complex. At, low gp3.5 concentrations, class III promoters are preferentially expressed over class II promoters (Villemain & Sousa, 1998), whereas at high concentrations of gp3.5, all transcription is repressed and only short abortive transcripts, necessary for T7 DNA replication, are produced (Moffat & Studier, 1987; Zhang & Studier, 1997).

Feedback control in T7 allows gene expression in the developmental phases to be controlled by the amount of protein production in those phases. RNAP transcribes class I genes, until the level of Gp0.7 and Gp2 is sufficient to stop RNAP transcription. This feedback mechanism may serve as a means to make Gp0.7 and Gp2 levels the critical parameter in the shutoff of protein production over the early region, and thus, decouple the relationship between amount of phage DNA or host resources and overall protein production. The process is analagous in the Gp1-mediated transcription and of the class II and III proteins and feedback by Gp3.5. Furthermore, since the timing of expression in T7 is regulated by the entry and thus the positioning of the genes, the spacing between genes 0.7 and 2.0 (encodes Gp0.7 and Gp2 respectively) from the beginning of the genome, and gene 3.5 relative to gene 1 (encodes Gp3.5 and Gp1), may serve as a mechanism for controlling the total amount of protein produced in each developmental phase.

We first intend to explore the extent to which different sources of variation affect gene expression and phage production. In order to do this, we must create mutants of T7 that are defective in feedback mechanisms for both the host and phage polymerase. Then we can screen these mutants against obvious sources of environmental variation. Finally, we can then move on to evaluate the how the positioning of these feedback mechanisms on the genome is optimized, if at all, for dealing with these sources of variation.

Experimental Plan

I am interested in how transcriptional feedback mechanisms in T7 may be acting to direct host resource allocation across the different phases of T7 gene expression (class I,II,III genes). My initial simulations show that the loss of feedback mechanisms leads to differences in the ability to direct host resources, especially towards class III gene expression (capsid, packaging and lysis genes). I want to run preliminary tests to see if I can find conditions that are sensitive to the loss in one of the feedback mechanisms (Gp3.5 ability to inhibit T7 RNA polymerase). Specifically, I am testing if the loss of feedback lowers the number of phage particles produced during infection under a range of multiplicity of infection and growth rates. Then, if promising, I will explore how the positioning of those feedback mechanisms may (or may not) be optimized to distribute resources.

Characterization of T7+ response to variation

Characterization of feedback knockout response to variation

Characterization of feedback ecto strains in response to variation

Personal tools