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Heterogeneity in helminth infections: factors influencing aggregation in a simple host–parasite system

Published online by Cambridge University Press:  30 September 2019

Richard C. Tinsley*
Affiliation:
School of Biological Sciences, Life Sciences Building, University of Bristol, BristolBS8 1TQ, UK
Hanna Rose Vineer
Affiliation:
School of Veterinary Sciences, University of Bristol, BristolBS40 5DU, UK
Rebecca Grainger-Wood
Affiliation:
School of Biological Sciences, Life Sciences Building, University of Bristol, BristolBS8 1TQ, UK
Eric R. Morgan
Affiliation:
School of Biological Sciences, Life Sciences Building, University of Bristol, BristolBS8 1TQ, UK
*
Author for correspondence: Richard C. Tinsley, E-mail: r.c.tinsley@bristol.ac.uk

Abstract

The almost universally-occurring aggregated distributions of helminth burdens in host populations have major significance for parasite population ecology and evolutionary biology, but the mechanisms generating heterogeneity remain poorly understood. For the direct life cycle monogenean Discocotyle sagittata infecting rainbow trout, Oncorhynchus mykiss, variables potentially influencing aggregation can be analysed individually. This study was based at a fish farm where every host individual becomes infected by D. sagittata during each annual transmission period. Worm burdens were examined in one trout population maintained in isolation for 9 years, exposed to self-contained transmission. After this year-on-year recruitment, prevalence was 100% with intensities 10–2628, mean 576, worms per host. Parasite distribution, amongst hosts with the same age and environmental experience, was highly aggregated with variance to mean ratio 834 and negative binomial parameter, k, 0.64. The most heavily infected 20% of fish carried around 80% of the total adult parasite population. Aggregation develops within the first weeks post-infection; hosts typically carried intensities of successive age-specific cohorts that were consistent for that individual, such that heavily-infected individuals carried high numbers of all parasite age classes. Results suggest that host factors alone, operating post-infection, are sufficient to generate strongly overdispersed parasite distributions, rather than heterogeneity in exposure and initial invasion.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2019
Figure 0

Fig. 1. Chronology of infections of Discocotyle sagitatta on rainbow trout, Oncorhynchus mykiss: schematic representation of the timeline of invasion relative to the study period, the life-cycle stages and duration of their occurrence on the hosts. Lower case letters in brackets link the parasite cohorts and their infection periods to the text (see Results).

Figure 1

Fig. 2. Frequency distribution of total parasites (all developmental stages) in the host population sample (n = 20 fish, n = 11 526 worms). For summary statistics and measures of aggregation see Table 1.

Figure 2

Table 1. Infections of Discocotyle sagittata in Oncorhynchus mykiss: summary of population data

Figure 3

Fig. 3. Frequency distributions of the successive age classes of parasites in the host population sample: (A) adult parasites (n  =  2902); (B) pre-adults (n  =  3032); (C) juveniles (n  =  2350); (D) post-larvae (n  =  3242, defined in Fig. 1 and text, ⩽1 month p.i.). Prevalence of infection is 100% for post-larval and juvenile stages (bottom two panels), but pre-adult and adult parasites were absent from 10 to 30% of hosts (top two panels). For summary statistics and measures of aggregation see Table 1.

Figure 4

Fig. 4. Pairwise comparison of the age-structured parasite burden of individual hosts. Axes values show untransformed numbers of parasites of each age class, but the spacing of tick marks on the axes represents a logarithmic scale. The distributions of age-structured data were not significantly different, with the exception of the adults and post-larvae (P  =  0.03; Table 2) and adults and juveniles (approaching significance, P  =  0.08; Table 2).

Figure 5

Table 2. Results of pairwise statistical tests on the age-structured data to test for significant differences in the distribution of each age class (D  =  Kolmogorov–Smirnoff test) and pairwise differences in the ranking of individuals by parasite age class (V  =  Wilcoxon Signed-Rank test)

Figure 6

Fig. 5. The number of parasites of each age class harboured by the individual hosts sampled, shown on a natural (top panel) and logarithmic (bottom panel) scale. Hosts are ranked on the horizontal axis from the host with the lowest to the highest total parasite burden. The size of the points used for adult (light blue), pre-adult (dark blue), juvenile (light green) and post-larvae (dark green) parasites is for clarity only and does not reflect the number of individuals or any other numerical statistic. Hosts with the highest total parasite burden tended to have higher burdens of all age classes (and vice versa).