The habits of highly effective phages: population dynamics as a framework for identifying therapeutic phages

Abstract

The use of bacteriophages as antibacterial agents is being actively researched on a global scale. Typically, the phages used are isolated from the wild by plating on the bacteria of interest, and a far larger set of candidate phages is often available than can be used in any application. When an excess of phages is available, how should the best phages be identified? Here we consider phage-bacterial population dynamics as a basis for evaluating and predicting phage success. A central question is whether the innate dynamical properties of phages are the determinants of success, or instead, whether extrinsic, indirect effects can be responsible. We address the dynamical perspective, motivated in part by the absence of dynamics in previously suggested principles of phage therapy. Current mathematical models of bacterial-phage dynamics do not capture the realities of in vivo dynamics, nor is this likely to change, but they do give insight to qualitative properties that may be generalizable. In particular, phage adsorption rate may be critical to treatment success, so understanding the effects of the in vivo environment on host availability may allow prediction of useful phages prior to in vivo experimentation. Principles for predicting efficacy may be derived by developing a greater understanding of the in vivo system, or such principles could be determined empirically by comparing phages with known differences in their dynamic properties. The comparative approach promises to be a powerful method of discovering the key to phage success. We offer five recommendations for future study: (i) compare phages differing in treatment efficacy to identify the phage properties associated with success, (ii) assay dynamics in vivo, (iii) understand mechanisms of bacterial escape from phages, (iv) test phages in model infections that are relevant to the intended clinical applications, and (v) develop new classes of models for phage growth in spatially heterogeneous environments.

Antipseudomonal Bacteriophage Reduces Infective Burden and Inflammatory Response in Murine Lung

“…Furthermore, a correlation between bacteriophage activity in vitro and subsequent success in vivo has been reported before (36). This study supports the importance of this correlation, although care should be taken not to assume that this is the only property required for efficacy (37). Subsequently, bacteriophage reduced the infective burden and inflammatory responses in a murine infection model when used at an initial theoretical multiplicity of infection (MOI) of ϳ100.…”

Microencapsulation with alginate/CaCO3: A strategy for improved phage therapy

“…The requirement for continuous administration of bacteriophages along the time to achieve a low population of Samonella has also been suggested by other authors1136. Several factors as partial emergence of bacteriophage-resistant Salmonella , bacterial phenotypic changes, physical refuges or slow growth rate of bacterial cells could explain this fact3536. By contrast, when the encapsulated bacteriophage cocktail was administered, the Salmonella concentration decreased gradually during all the experiment, regardless of whether treatment was ongoing or had stopped.…”

“…Therefore, the success of phage therapy is largely determined by the relationship between the concentration of the bacteriophages and that of their bacterial host34. However, the in vivo dynamics are presumably much more complex because multiple external factors (e.g., rapid clearance of the bacteriophages by passive/active host immunity, spatial refuges, and intestinal mucous) influence treatment success35.…”

Sustainability of spatially distributed bacteria-phage systems

“…Traditionally, phage-bacteria ecosystems are modelled by generalized versions of the classical Lotka-Volterra equations [11][12][13][14][15][16][17][18][19][20][21][22][23] . In their simplest form, such mass action equations predict sustained oscillations which become damped when one takes into account resource limitations 20 .…”