Variation in Host Specificity between Avian Malarial Parasite Lineages

Introduction

Host specificity is known to be a major contributor to parasite transmission and prevalence. It acts as the compatibility filter for a parasite, determining if a parasite can survive once it enters a host (1). Host specificity has many facets. Traditional host specificity looks at the number of unique hosts that a parasite can infect. Evolutionary host specificity looks deeper and compares the taxonomy of the hosts (2). Parasites that are generalists can infect many host species that are less evolutionarily related, whereas specialist parasites infect few, closely related hosts (Figure 1). The 3 genera of avian malaria, Plasmodium, Haemoproteus, and Leucocytozoon, vary in their hosts and host specificity, giving a useful model to study host specificity and its effects on host health. Plasmodium is often considered the most generalist of the three (4).

In this study, we attempted to categorize the host specificity of lineages found in the ongoing survey of avian blood parasites by the Avian Research and Education Institute (AREI) and the Love lab. We also compared host specificity to the likelihood of a lineage being part of a co-infection (a bird found with multiple parasite lineages) to determine if generalist or specialist parasites were more likely to be involved.

Our hypothesis:

Plasmodium lineages will be the least host specific (most generalist) with the highest SPD value and the greatest number of host species.
Generalist lineages will be more common in co-infections.

Figure 1: A diagram showing the two facets of host specificity. Plasmodium 1 has two red arrows to two different birds, showing it can infect both of them. Plasmodium 2 has a red arrow to just one bird.

Figure 1. A diagram of host specificity. Plasmodium 1 has both greater traditional and evolutionary host specificity compared to Plasmodium 2. Credit for Plasmodium drawing: Valkiūnas, G., & Iezhova, T. A. (2018) (3).

Methods

Blood samples were collected from birds at the AREI banding station. DNA was extracted from blood samples to check for infection using PCR and gel electrophoresis. Positive samples were sequenced and assigned Lineage IDs. For each lineage, the number of hosts was counted, and the SPD (Standard Phylogenetic Distinctiveness) was calculated (Figure 2). The number of co-infections was compared with SPD.

Figure 2. Example of how varying taxonomic differences between hosts are displayed by SPD. Figure from Poulin et al. (2003) (5), which described the metric.

Figure 2. An image showing how SPD values represent the variation in taxonomic difference between hosts of a parasite. There are 4 steps up the taxonomic ladder: species, genus, family, and order. In example a, all 4 of the host species share a genus, creating an SPD value of 1.00. In example 2, hosts a and b share a genus and hosts c and d share a genus, and these genera share a family, creating an SPD value of 1.67. In example c, hosts a and b share a family and hosts c and d share a family, and the families share an order, creating an SPD value of 2.67.

Results

We found a total of 25 lineages in 19 host species, with 12 Plasmodium lineages, 6 Parahaemoproteus lineages, and 7 Leucocytozoon lineages (Figure 6). Plasmodium A, B, D, F, J, and Parahaemoproteus A and C are all generalist lineages (SPD values greater than 2.5) (Figure 3). Plasmodium lineages were the most generalist (least host specific) in both traditional (GLM: 𝜒 ² = 15.359, p < 0.001) (Figure 4) and evolutionary host specificity metrics (GLM: 𝜒 ² = 19.75, p < 0.001) (Figure 5). We found a nonsignificant trend that more generalist lineages (larger SPD values) were more frequently in co-infections (GLM: 𝜒 ² = 19.75, p = 0.715) (Figure 7).

Figure 3. A graph showing the number of host species found in each lineage, with each host species represented by a color.

Figure 3. Number of host species (colors) each lineage was infecting in our study. SPD values are on top of the bars. SPD cannot be calculated in lineages found in only one host species.

Figure 4. A graph showing the traditional host specificity (the number of host species) of each lineage, with the lineages grouped into genera. Plasmodium has a traditional host specificity that is significantly higher than Leucocytozoon and Parahaemoproteus.

Figure 4. Traditional host specificity (number of hosts) of each lineage, organized by genus. Black circles and error bars represent the mean ± SE.

Figure 5. A graph showing the SPD values of each lineage, with the lineages grouped into genera. Plasmodium has an average SPD that is significantly higher than Leucocytozoon.

Figure 5. SPD values of each lineage, organized by genus. Black circles and error bars represent the mean ± SE. Lineages with a single host were assigned an SPD of zero.

Figure 6. The phylogeny showing the evolutionary relationship of the lineages found and the host species each sample came from. Leucocytozoon splits off before Haemoproteus does.

Figure 6. Phylogeny showing the 25 unique lineages that were found in 19 different host species.

Figure 7. A graph showing the trend of SPD values compared to the percentage of infections found that were coinfections for each lineage. The trend line slopes up as the percent coinfected increases.

Figure 7. Graph of the percent co-infections and the SPD value for each lineage. Lineages where the SPD value was not calculable were excluded. Co-infections were most common in Plasmodium F, Plasmodium J, and Leucocytozoon A.

Conclusions and Future Study

Of the three genera, Plasmodium was found to be the least host specific, which follows previous research (4). Leucocytozoon was the most specific, with 6 out of 7 lineages only being found in one host species, the Swainson’s Thrush. Parahaemoproteus lineages A and C each infected 2 host species of different families (SPD =3), leading to differences in traditional and evolutionary host specificity metrics. Also, generalist lineages were not more likely to be in hosts co-infected with multiple lineages. This could indicate that the encounter filter may be more important than the compatibility filter in determining host specificity of vector-borne parasites. For future research building on this project, we will add host data from AviMal (an online database of avian malarial lineages) to get a better picture of host specificity and compare host health metrics to SPD values to determine if generalist or specialist lineages are more damaging to hosts.

The following is an image of the poster presented at the 2026 Undergraduate Research Forum.

Acknowledgements

We thank the AREI banding station and the Love Lab for collecting blood samples and the CBFG for sequencing service. We also thank the King family for their support of the Applied Sciences Partnership Lab.

References

Agosta, S. J., Janz, N., & Brooks, D. R. (2010). How specialists can be generalists: resolving the “parasite paradox” and implications for emerging infectious disease. Zoologia (Curitiba), 27(2), 151–162. https://doi.org/10.1590/s1984-46702010000200001
Poulin, R., Krasnov, B. R., & Mouillot, D. (2011). Host specificity in phylogenetic and geographic space. Trends in Parasitology, 27(8), 355–361. https://doi.org/10.1016/j.pt.2011.05.003
Valkiūnas, G., & Iezhova, T. A. (2018). Keys to the avian malaria parasites. Malaria Journal, 17(1). https://doi.org/10.1186/s12936-018-2359-5
Ndlovu, M., Wardjomto, M. B., Pori, T., & Nangammbi, T. C. (2024). Diversity and Host Specificity of Avian Haemosporidians in an Afrotropical Conservation Region. Animals, 14(19), 2906. https://doi.org/10.3390/ani14192906
POULIN, R., & MOUILLOT, D. (2003). Parasite specialization from a phylogenetic perspective: a new index of host specificity. Parasitology, 126(5), 473–480. https://doi.org/10.1017/s0031182003002993

NACE Career Readiness Competencies

Critical Thinking: This project has allowed me to explore various ideas related to bird health and synthesize methods from previous studies to create a unique perspective.
Communication: This project has encouraged me to communicate with others from my research class to have a greater understanding of the various aspects of parasite prevalence, along with writing and designing a poster for a more general audience without previous knowledge about avian malaria.
Technology: This project allowed me to work with the programs MEGA12 and R, which will be key to working with genetic data in the future.
Career Development: This project has given me the opportunity to explore genetic research and develop a skill set that will be useful as I continue working in genetics in the future.

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