Biology subjects

Krone, S. M.

Publications and source records attributed to Krone, S. M..

4 recordsLinked to original sources

bioRxiv2025

Modeling the phage properties best for therapy

The phages used to treat bacterial infections in phage therapy are commonly chosen based on their abilities to form plaques on the infecting bacterium - on host range. In practice, phage therapy is not always successful, leaving room for improvement. Here we use computational models to investigate whether some standard phage properties (burst size, lysis, adsorption, decay rate, growth rate) might serve as predictors of treatment success. As our measure of treatment success, we deviate from many other approaches by calculating the number of phage needed to suppress bacterial densities 100-fold in the short term, given that the patients immune system is expected to regain control once bacterial numbers are reduced. Numerical analysis of 2400 combinations of different values of phage phenotypes reveals that, on average, adsorption rate and growth rate provide the most useful predictive values, decay rate provides some value, whereas burst size and lysis time offer essentially little or no value. Bacterial density is especially informative of the number of phage required for treatment. There is nonetheless often considerable variation around average behavior for a single phenotype. These results raise the possibility that adsorption rate and growth rate may be especially important in phage therapy performance for both high and low bacterial densities. Given that therapeutic phages are often evolved in vitro for broad host ranges rather than for individual hosts, it should be considered that selection for broad host range may have a downside of compromising adsorption to and growth rate on individual bacterial hosts.

microbiology↗

bioRxiv2020

Vector dynamics influence spatially imperfect genetic interventions against disease

Background and objectivesGenetic engineering and similar technologies offer promising new approaches to controlling human diseases by blocking transmission from vectors. However, in spatially structured populations, imperfect coverage of the vector will leave pockets in which the parasite can persist. Yet movement by humans may disrupt this local persistence and facilitate eradication when these pockets are small, essentially distributing parasite reproduction out of unprotected areas and into areas that block its reproduction. MethodologyWe develop formal mathematical models of this process similar to standard Ross-Macdonald models, but (i) specifying spatial structure of two patches, with transmission blocked in one patch but not in the other, (ii) allowing temporary human movement (travel instead of migration), and (iii) considering two different modes of mosquito biting. ResultsWe find that there is no invariant effect of disrupting spatial structure with travel. For both biting models, travel out of the unprotected patch has different consequences than travel by visitors into the patch, but the effects are reversed between the two biting models. Conclusions and implicationsOverall, the effect of human travel on the maintenance of vector-borne diseases in structured habitats must be considered in light of the actual biology of mosquito abundances and biting dynamics. Lay summaryGenetic interventions against pathogens transmitted by insect vectors are promising methods of controlling infectious diseases. These interventions may be imperfect, leaving pockets where the parasite persists. How will human movement between protected and unprotected areas affect persistence? Mathematical models developed here show that the answer is ecology-dependent, depending on vector biting behavior.

ecology↗

bioRxiv2019

Spatial structure undermines parasite suppression by gene drive cargo

Gene drives may be used in two ways to curtail vectored diseases. Both involve engineering the drive to spread in the vector population. One approach uses the drive to directly depress vector numbers, possibly to extinction. The other approach leaves intact the vector population but suppresses the disease agent during its interaction with the vector. This second application may use a drive engineered to carry a genetic cargo that blocks the disease agent. An advantage of the second application is that it is far less likely to select vector resistance to block the drive, but the disease agent may instead evolve resistance to the inhibitory cargo. However, some gene drives are expected to spread so fast and attain such high coverage in the vector population that, if the disease agent can evolve resistance only gradually, disease eradication may be feasible. Here we use simple models to show that spatial structure in the vector population can greatly facilitate persistence and evolution of resistance by the disease agent. We suggest simple approaches to avoid some types of spatial structure, but others may be intrinsic to the populations being challenged and difficult to overcome.

evolutionary biology↗

bioRxiv2019

Gene-drive-mediated extinction is thwarted by evolution of sib mating

Genetic engineering combined with CRISPR technology has developed to the point that gene drives can, in theory, be engineered to cause extinction in countless species. Success of extinction programs now rests on the possibility of resistance evolution, which is largely unknown. For CRISPR technology, resistance may take many forms, from mutations in the nuclease target sequence to specific types of non-random population structures that limit the drive. We develop mathematical models of various deviations from random mating to consider escapes from extinction-causing gene drives. We use a version of Maynard Smiths haystack model to show that population structure can enable drive-free subpopulations to be maintained against gene drives. Our main emphasis, however, is sib mating in the face of recessive-lethal and Y-chromosome drives. Sib mating easily evolves in response to both kinds of gene drives and maintains mean fitness above 0, with equilibrium fitness depending on the level of inbreeding depression. Environmental determination of sib mating (as might stem from population density crashes) can also maintain mean fitness above 0. Translation of mean fitness into population size depends on ecological details, so understanding mean fitness evolution and dynamics is merely the first step in predicting extinction. Nonetheless, these results point to possible escapes from gene drive-mediated extinctions that lie beyond the control of genome engineering.

evolutionary biology↗