Calibrating estimates of phage-induced mortality in marine bacteria: Ultrastructural studies of marine bacteriophage development from one-step growth experiments

Abstract

The timing of lytic phage development and the relationship between host generation times and latent periods were investigated by electron microscopy of one-step growth experiments in two strains of marine Vibrio species. Results were used in a correction factor developed to interpret field studies of phage-infected marine bacteria. Both the number of mature phage per average cell section and the percentage of cells with mature phage increased exponentially by 73-86% into the latent periods. Assuming that bacterial infection and lysis take place continually in the ocean, conversion factors for relating the percentage of visibly infected bacteria to the total percentage of the bacterial community that are phage-infected were calculated as 3.70-7.14. When this range of factors was applied to previously-collected field data [Proctor LM, Fuhrman JA (1990) Nature (Lond) 343:60-62; Proctor LM, Fuhrman JA (1991) Mar Ecol Prog Ser 69:133-142] from 3 to 31% of the free-living bacteria and 3 to 26% of particulate-associated bacteria appeared to be phage-infected at any given time. Based upon a steady-state model in which half the daughter cells survive to divide again, the percent of total mortality would be twice the total percentage of phage-infected cells. From 6 to 62% and from 6 to 52% of mortality for the free-living and particulate-associated bacterial community, respectively, may be due to viruses.

High control of bacterial production by viruses in a eutrophic oxbow lake

“…According to the model of Proctor et al (1993), the FVIC was converted to the FIC using the low (3.70), high (7.14) and average (5.42) conversion factors. A new model was used to calculate the FIC taking into account the effect of grazing mortality on the relationship between FVIC and FIC (Binder 1999).…”

“…Some of them preclude information on viral production, which can be monitored by viral decay (Heldal & Bratbak 1991), dilution technique (Wilhelm et al 1998a, Hewson et al 2001 H-thymidine incorporation or 32 P incorporation (Steward et al 1992). Moreover, the frequency of infected bacterial cells (FIC) can be estimated by applying conversion factors presented by Proctor et al (1993) to the frequency of visibly infected cells (FVIC), which can be determined by transmission electron microscopy (TEM). Assuming that bacteria undergo binary fission (1 daughter cell survives to divide again), the proportion of total bacterial mortality due to viral lysis is equal to the FIC multiplied by a factor of 2.…”

“…limnic systems or marine systems of different trophic status has never been tested. The model of Proctor et al (1993) fails to take into account the continuous nature of viral infection, growth and mortality of bacterial cells in a population, and the possibility that grazing mortality is an alternative fate for infected bacterial cells. A mathematical model has been developed recently which incorporates grazing of bacterivores in the assessment of the viral impact on bacterial production (Binder 1999).…”

“…Many studies investigated virusbacteria interactions, but most of them used only 1 method to determine phage-induced bacterial mortality. As mentioned earlier, the model of Proctor et al (1993) has been widely used, even though the validity of the conversion factors for different aquatic systems is debatable. In contrast, the decay method has rarely been applied (Heldal & Bratbak 1991, Mathias et al 1995, Guixa-Boixereu et al 1996, Tuomi et al 1999, and only 2 authors used this method simultaneously with the model of Proctor et al (1993) (Mathias et al 1995, Guixa-Boixereu et al 1996.…”

“…Although our estimations of phage-induced bacterial mortality were based primarily on data from viral decay experiments, mean burst size and bacterial secondary production (BSP), we also calculated the FIC, applying the model of Proctor et al (1993) and the model of Binder (1999). It was expected that a discussion on the quality of the observed data could be improved by comparing the results of different approaches.…”