Virus del bacteriofago t4

Etiquetas: fago, tasmania, amarillo, rojo, naranja, hojas, alpino. Construido fago arcoiris Lienzo De Jellie. Lysogenesis Lienzo De FMelo. Columpio Lienzo De Jellie. Etiquetas: supreme box logo, box logo, supreme, japan, arizona, tea, smiley, sad, vaporwave, blossoms, nature, black, green, pink, sadboys, yung lean, photoshop, aesthetics, aesthetic, vapor wave, yung lean boys, sad boys, emotional, cloud rap, astar, i astvri, cloud, rap, emotions, japanese, harmony, symbol, white, yin and yang, water, gameboy, fiji, bones, waterboy, nike, yung lean doer, trap, grills.

Please refer to the supplemental data section for details of strain construction. The BigDye Terminator cycle sequencing kit v. The filtrate was plated on IN25 for plaque counting. The nonlinear fit was performed using the statistical package JMP v. Three replicate experiments were conducted to estimate adsorption rate.

The cell concentrations at the beginning and the end of each experiment were determined and were used separately for the estimation of each replicate adsorption rate. The previously described procedure W ang was used for the determination of phage lysis time. Three replicates were conducted for each lysis time determination.

In most cases, the initial ratio of blue and white phages was kept when competition was conducted within each stf background. Standardized protocol and precautions W ang were followed for phage plating. To differentiate the standard and the competing strains, XL-1 Blue was used as the plating host with the same IPTG and X-gal conditions as described above.

Emerging blue and clear plaques were counted separately. Three replicates were conducted for each pairwise competition. Since most data were collected with few replicate experiments usually three , the calculated standard errors have all been corrected for small sample sizes according to S okal and R ohlf , p.

The correction would result in a larger standard deviation and standard error than the typically calculated ones. The reduced adsorption rate is due to a frameshift mutation a deletion of cytosine in the side tail fiber stf gene that resulted in the loss of side tail fibers H endrix and D uda A similar pattern was also shown elsewhere H endrix and D uda Clearly, the presence of the side tail fibers greatly increases the rate of adsorbing onto the cell surface.

After mixing with exponentially grown E. Ratios of unadsorbed phages were logarithmically transformed and plotted against time. Different symbols represent different replicate assays. Traditionally, the adsorption rate is estimated by fitting the logarithmically transformed relative phage concentration data with a linear regression line.

The slope of the line is the product of adsorption rate and bacteria cell concentration. Assuming constant host density during the assay period, the adsorption rate can thus be calculated by dividing the value of the slope by the host density.

Since the length of time used for adsorption rate determination 28 min in this study is about the generation time of bacterial growth in a rich medium, the host density is not kept constant.

To account for the changing host density, thus affecting the estimated adsorption rate, a nonlinear regression model was used to estimate the adsorption rates see appendix a for equation derivation. Six different S alleles, each resulting in different lysis times, were used in this study. Table 2 lists the genotypes and the estimated lysis times for the phage strains that carry these alleles.

In this study, the lysis times ranged from the shortest of For simplicity of strain notation, each S allele is referred to by its phenotypic effect, namely the lysis times.

For example, the S wt allele is named Swt, which has a lysis time of As shown in Figure 3 , neither the HA nor the LA strains showed discernible marker effect on phage relative fitness. Effects of adsorption rates on optimal lysis times. In this plot, only phage strains with the same adsorption rate were competed against each other. Phage strains used in competitions are shown in Figure 1. The lysis times and relative fitness for each pairwise competition are listed in Table 2.

Some values are too small to appear in the plot. All the competition experiments were conducted by competing the standard strains against the competing strains. Since the standard strains are the same in each pairwise competition, the standard strains can be seen as an internal control for the culture environments.

If the growth rates of the standard strains are similar across all pairwise competitions, then it can be argued that all phage strains that participated in pairwise competitions have experienced a similar culture environment. Table 2 lists the growth rates of the standard and the competing strains for various pairwise competitions.

For competitions among the LA phages, there is no significant difference among the growth rates of the standard strain. With one exception [ i. This result suggests that the culture environment, especially the host density, is quite similar across these pairwise competition experiments. The phage strain with a higher adsorption rate would on average have a shorter time in encountering and attacking a host; therefore, based on the reinterpreted optimality model, it would have a shorter optimal lysis time when compared to the phage strain with a lower adsorption rate.

Note that each pairwise competition was conducted among the HA or LA phages. As shown in Figure 3 , the relative fitness curves peaked at different lysis times, depending on phage adsorption rates. As predicted by the model, the HA phages have a shorter optimal lysis time with the fitness curve peaking at Interestingly, the relative fitness curves are not symmetrical around either optimum.

In the case of HA phages, there is a steep decline of relative fitness when the lysis time is below the optimum, but a very shallow decline, almost plateau-like, when the lysis time is longer than the optimum.

On the other hand, for the LA phages, the optimum peak is more prominent, with notable declines on relative fitness when the lysis times are suboptimal. It is interesting to note that simulation studies B ull ; W ang also tend to find sharp declines on the left side of the fitness curves. The results shown in Figure 3 may give an erroneous impression that both phage traits—adsorption rate and lysis time—have a similar impact on relative fitness.

In reality, under the current assay conditions, adsorption rate has a much larger effect on phage relative fitness than the lysis time our unpublished results. As shown in Figure 4 , only under such a disparate configuration can we observe the fitness advantage conferred by high adsorption rate being overcome by the disadvantage incurred by suboptimal lysis times. However, if the standard strain is replaced with a strain with a slightly longer lysis time [ i.

Relative fitness was determined and plotted against the lysis time of competing strains. That is, as the lysis time approaches the optimum, the effect of the adsorption rate becomes more important.

Genetic markers are routinely used to differentiate between different bacterial or viral strains in competition experiments. Typically, the methods for differentiation are based on selection, e. With few exceptions [ e. The marker effect is especially frequent when viruses are used as the study organisms; although the fitness cost is usually taken into account when estimating relative fitness. We adopted a screening-based marker system, specifically color screening, which is unlike the selection-based marker system.

Although the marker does impose a slight fitness cost when compared to the phage strain without the marker. To eliminate the potential marker effect, it is important to construct isogenic markers with minimal differences; in our case, the difference is five amino acid residues. Also, the screening-based system has its own limit as well. Because of this, the screening-based method would have a smaller dynamic range in detecting phage concentration differences.

Consequently, the ability to determine large fitness differences is more limited in the screening-based than the selection-based methods. In our case, it is unclear which trait s is affected and hence responsible for the fitness cost.

Comparison between these two sets of results showed that the lysis time was slightly affected by the marker insertion. But there is no consistent direction of bias in lysis time. Furthermore, the timing usually differs within 2—3 min. Since we have not determined the burst size for the marked phage strains, we do not know the impact of marker insertion. However, it is not unreasonable to speculate that both the lysis time and the burst size have been somewhat affected by the marker insertion.

Currently, there are two seemingly different theoretical approaches to the question of optimal lysis time. The first one, as described in this study, explicitly incorporates phage life-history traits into the commonly used formula for growth rate calculation. That is, the phage growth rate is expressed as , where b is the burst size, t S the search time, and t L the lysis time W ang et al.

The other approach is derived from comprehensive phage population dynamics in a chemostat culture B ull ; B ull et al. The phage growth rate is found to be , where s is the free phage death rate, r the adsorption rate, N the host concentration, and d the washout rate of the chemostat B ull , Equation 2b. In fact, as shown in appendix b , the same solution for the optimal lysis time can also be derived from the first theoretical approach of calculating phage growth rate.

Although different in perspectives, both approaches arrived at the same solution for the optimal lysis time. According to the above equation, a maximum growth rate of 0.

At present, it seems that the solution based on the current optimality models is able to predict the optimal lysis time for the HA phages with reasonable accuracy predicted But the failure in prediction is not due to the LA phages per se. Analysis of the data from a previous study W ang showed a somewhat different conclusion. Based on the maximum growth rate of 0. That is, the search time thus the generation time of the LA phages would be shorter, and consequently the growth rate higher, in this study.

But the main reason for such an uncertainty in predicting the optimal lysis time may be because of the nonequilibrium nature of the batch culture. For both optimality models, the phage growth rate, and thus the optimal lysis time, should be evaluated under the condition of constant host density.

However, for most batch culture experiments, the phage growth rate is usually determined under the condition of exponential host growth, resulting in a progressively shortened search time and thus a progressively higher instantaneous growth rate. The empirically determined growth rate is simply an average over the assay period. Therefore, it seems that caution is needed in interpreting quantitative predictions of the optimal lysis time when the study is conducted under the batch culture condition.

This conclusion does not deny the utility of the batch culture. Besides its easy setup, studies conducted with the batch culture can nevertheless provide us the qualitative predictions of optimality models, as is demonstrated in this study. Implicitly, this study presumes a Fisherian fitness landscape with one global maximum.

That is, for a given environment, there is one best combination of life-history traits that results in maximal fitness. Given a long enough time, we also assume that each part of the phage genome will coadapt to a particular environment, resulting in the highest fitness possible.

In this discussion, we presume that all strains will eventually arrive at the combined traits of HA, S 46 or one close to it. Results from this study allow us to speculate on the possible evolutionary pathways to achieve this maximum fitness. A hypothetical fitness landscape in which the phage relative fitness is expressed as a function of adsorption rate and lysis time. The two solid curves are redrawn from Figure 3.

The positions of adsorption rates and lysis times are not to scale and are for reference only. The dotted lines with arrowheads indicate the speculated evolutionary sequences from suboptimal strains to the optimal strain. An observation from this study provides circumstantial support for the above speculation.

An independent study showed that the slightly increased plaque size is consistent with a lengthened lysis time our unpublished results. In Figure 3 of the study B ull , the relationship between phage growth rate and lysis time is shown with three curves, some representing different host densities. Since the effect of host density and adsorption rate on phage growth rate can be treated as equivalent, these curves can be interpreted as representing phages with different adsorption rates.

Closer inspection of these curves suggests that, regardless of the lysis time, it is always evolutionarily profitable for phages to evolve to a higher adsorption rate first. It is not clear how general this conclusion is. One problem is that the ideas of a high or a low adsorption rate and a long or a short lysis time are context dependent and should be evaluated in the presence of other life-history traits and environmental conditions.

Nevertheless, it would be interesting to develop a theoretical basis for understanding the nature of the phage fitness landscape such that we would be able to predict the evolutionary sequences of climbing up the fitness peak.

For the above discussion, we have solely focused on the phenotypic imperatives derived from optimality analysis, i. Whether the evolution of the suboptimal strain would follow the most profitable pathway would depend on the genetic basis underlying these traits.

The evolution of phenotype is always constrained by the underlying genotype. In the case of adsorption rate, there are at least two mechanisms to achieve a high adsorption rate: mutations at the tail fiber gene J our unpublished data or reacquisition of the side tail fiber through a revertant, or possibly a compensatory, mutation. It has advanced our understanding of viral infection, and may someday help to control pathogenic bacteria.

Complementation, deletion, and recombination tests can be used to map out the rII gene locus by bactteriofago T4. This website uses cookies to improve your experience while you navigate through the website.

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