The relation between dosage, bacterial growth and time for disease response during infection of bean leaves by Pseudomonas syringae pv. phaseolicola

Abstract

Pseudomonas syringae pv. phaseolicola 1L3 was infiltrated at a dosage of 0mD5 to 512 times the median effective dose (ED50) into the leaves of two bean cultivars, Borlotto di Vigevano (ED50 15 bacteria) and Saluggia (ED50 34 bacteria). The distributions of time for production of disease symptoms after inoculation with up to 64 ED50 were in agreement with those predicted by the simple birth‐death model for microbial infection. Individual times of response to higher doses were longer and more widely distributed than expected from the model. Growth curves of bacteria in leaves inoculated with 16, 64 or 512 ED50 could be viewed conventionally as a sequence of an exponential phase, a phase of decelerating growth and a stationary phase. Viable counts, however, were also compatible with parabolic population trends during the period preceding, accompanying and immediately following the appearance of disease symptoms. Bacterial growth parameters estimated from response times and infectivity titration data were consistent with those calculated from viable counts in vivo.

Characterisation of the distribution of individual response times in bacterial infection of plants

“…Therefore probit analysis did not yield conclusive evidence that response was normally distributed versus either logT or T-1. These findings were described earlier with respect to Expts 2 and 3 (Ercolani, 1985) but not to other host-pathogen combinations examined in this study.…”

“…The pattern of reaction of t to variation of 6 was difficult to explain. Independent analysis of response times using the methods of Shortley (1967) and Williams (1967) showed that distributions observed in Expts 2 and 3 were compatible with the predictions of the simple birth-death model for microbial infection (Ercolani, 1985) but those recorded in other experiments were not because, among other things, the EDso could not be reconciled with the expected rate of bacterial multiplication in vivo (G. L. Ercolani, unpublished results). Since t fluctuated around 2.0 and was more or less invariant to dosage in Expts 2 and 3 only, it was tempting to speculate that the value of the shape parameter together with its dependence on dosage would reflect the course of host-pathogen interactions in these and other experiments, but supporting evidence was lacking.…”

“…biovar 3 from grapevine (Ercolani & Ghaffar, 1983) was grown on 0 I986 Association of Applied Biologists nutrient agar for 2 days at 26"C, washed twice in sterile distilled water and injected at four dose levels (Table 1) into the apical internode of 2-wk-old plants of sunflower in a greenhouse at 20-23°C with a photoperiod of 12 h. Visible outgrowth distinct from a healing reaction at the site of inoculation was taken as an indicator of response to infection. Other experimental details conformed to the protocol described by Ercolani (1985).…”

Pathogen Growth in Insect Hosts: Inferring the Importance of Different Mechanisms Using Stochastic Models and Response-Time Data

“…Third, to produce a linear birth-death model, we began with M2 and we additionally fixed the number of immune cells y t at y 0 for all t, so that the death rate is set to the constant value by 0 . Note that this model was first introduced by Shortley (1965), and so we call this the "Shortley birth-death" model (M3) (Chang 1970;Ercolani 1985). Fourth, by reparameterizing M1 according to and by assumc p c /c 1 1 2 ing that dose D K c 2 , we produce a model in which virus establishment is a linear, nonsaturating function of dose.…”

The Mangotoxin Biosynthetic Operon ( mbo ) Is Specifically Distributed within Pseudomonas syringae Genomospecies 1 and Was Acquired Only Once during Evolution

“…actinidae in which the PCR resulted in a specific amplicon of this pathovar (16). A multiplex PCR assay has been developed for the identification and differentiation of P. fragi, P. lundensis, and P. putida on the basis of the coamplification of different carbamoyl phosphate synthase small-subunit gene fragments (17). Another example is the amplification of the gene iaaL, yielding a 454-bp fragment that allows the identification and detection of P. syringae pv.…”