Not surprisingly, all models predicted that a shorter latent period would result in a lower plaque productivity. However, in some models, the long latent TGF-beta tumor period did not influence the productivity

much, thus assuming a plateau-like relationship, while others predicted an optimal latent period, maximizing the plaque productivity [16]; their Figure 3]. The problem with studies on phage plaque formation is that there are few empirical tests of the various proposed mathematical models [9, 19, 23]. Most observations are anecdotal, lacking a systematic focus. Typically, only a narrow facet of the model was tested [20]. The main obstacle to conducting experimental tests of these models is that values of various phage traits are not easily changed, unlike in mathematical models and computer simulations. However, the difficulty of experimentally assessing the impacts of phage traits on plaque size and productivity can be overcome by using a series of isogenic phage strains that only differ in one or two traits. In this study, we constructed and assembled

a collection of isogenic λ phage strains Erismodegib order that only differed in one, two, or all three phage traits: adsorption rate, lysis time, and morphology. By measuring the plaque sizes with digital image analysis and estimating the plaque productivities of these isogenic phages, we were able to assess the impact of each phage trait while holding other variables constant. We also tested the model predictions using our current results. We found that

some of the models were able to capture the empirical results qualitatively but not always quantitatively. Results Effect of adsorption rate To assess the impact of adsorption rate on plaque size (surface area of the plaque) and plaque productivity (number of phages per plaque), we constructed eight isogenic strains of phage ADP ribosylation factor λ that only differed in their adsorption rate and click here virion size. This was accomplished by combining four J alleles (J WT , J 245-2 , J 1077-1 , and J 1127-1 ) [17, 24], which encode the tail fiber proteins (gpJ), and two stf alleles (stf + and stf – ), which encode the side-tail fibers (Stf) [17]. Since there is no practical way to determine adsorption rate in the agar gel, we used the rates determined in the liquid culture to serve as surrogates for how these phages would behave in the agar gel. The adsorption rate, as determined here, is a function of phage diffusion coefficient (or diffusivity), which is a function of medium viscosity and phage virion radius [25]. Since all our Stf+ and Stf- phages would have the same shape within the group and experience the same viscosity, therefore we expect the ranking of the adsorption rates within each Stf group to remain the same.