Closely-related Borrelia burgdorferi (sensu stricto) strains exhibit similar fitness in single infections and asymmetric competition in multiple infections

Abstract

Background: Wild hosts are commonly co-infected with complex, genetically diverse, pathogen communities. Competition is expected between genetically or ecologically similar pathogen strains which may influence patterns of coexistence. However, there is little data on how specific strains of these diverse pathogen species interact within the host and how this impacts pathogen persistence in nature. Ticks are the most common disease vector in temperate regions with Borrelia burgdorferi, the causative agent of Lyme disease, being the most common vector-borne pathogen in North America. Borrelia burgdorferi is a pathogen of high public health concern and there is significant variation in infection phenotype between strains, which influences predictions of pathogen dynamics and spread.

Methods: In a laboratory experiment, we investigated whether two closely-related strains of B. burgdorferi (sensu stricto) showed similar transmission phenotypes, how the transmission of these strains changed when a host was infected with one strain, re-infected with the same strain, or co-infected with two strains. Ixodes scapularis, the black-legged tick, nymphs were used to sequentially infect laboratory-bred Peromyscus leucopus, white-footed mice, with one strain only, homologous infection with the same stain, or heterologous infection with both strains. We used the results of this laboratory experiment to simulate long-term persistence and maintenance of each strain in a simple simulation model.

Results: Strain LG734 was more competitive than BL206, showing no difference in transmission between the heterologous infection groups and single-infection controls, while strain BL206 transmission was significantly reduced when strain LG734 infected first. The results of the model show that this asymmetry in competition could lead to extinction of strain BL206 unless there was a tick-to-host transmission advantage to this less competitive strain.

Conclusions: This asymmetric competitive interaction suggests that strain identity and the biotic context of co-infection is important to predict strain dynamics and persistence.

Keywords: Co-infection; Ixodes scapularis; Peromyscus leucopus; Strain diversity.

Fig. 1

Illustration of laboratory infection of hosts and xenodiagnoses. Infected nymphs were used to infect hosts at days 0 and 21 (uninfected nymphs were used on day 21 for single-infection controls). Uninfected larvae were used to assess pathogen transmission at days 7, 14, 28, 35 and 49

Fig. 2

Illustration of the simulation model. Each generation consisted of 100 mice. Nymphs from the previous generation were used to create a virtual pool from which nymphs were drawn to infect mice at the next generation (with first generation using results from the final day of the laboratory experiment). One nymph was randomly drawn at day 0 and again at day 21 for the infections. Possible outcomes include extinction of either strain or coexistence

Fig. 3

Transmission dynamics of strains BL206 and LG734 over the course of the laboratory experiment for each infection group (panels). The total proportion of ticks infected with strain BL206 is shown in blue (solid line) and LG734 in red (dashed line). The proportion of ticks infected with each strain is the sum of those singly-infected with a strain and co-infected ticks

Fig. 4

The observed and expected number of ticks co-infected from each heterologous infection group at the three time points post-secondary infection (observed values: dark green triangles, expected values: light green circles)

Fig. 5

Results of the simulation model in response to variation in p, the probability of a mouse becoming infected with strain LG734 from a co-infected nymph (1-p denotes probability of infection with strain BL206). Infection prevalence of each type of infection in ticks (a), and each type of infection in host determined by all possible sequential infections (b)