Measuring aggregation in parasite populations

Parasite abundance distribution as a model of host-parasite relationships between monogeneans Gyrodactylus spp. and cage-reared rainbow trout Oncorhynchus mykiss

Aggregation is a fundamental feature of parasite distribution in the host population, but the biological implications of the aggregation indices used to describe the relationships between the populations of parasites and hosts are not evident. It is speculated that the form of distribution in each case is predicated on the host's varying resistance to the infection, which is hard to control, making it difficult to adequately interpret the index values. This paper examines several cases from trout farms in Russian Karelia to explore the monogenean Gyrodactylus spp. infection in rainbow trout of varying ages. The genetic homogeneity of cage-reared fish and the direct life cycle of the helminths make the relationship between the species more lucid than in natural host-parasite systems. The results give no ground to speak of any specific patterns: as well as in the natural systems, the infection rates in trout vary widely, i.e., the helminth distribution has not become more uniform; the observed distributions in all cases are adequately approximated by the negative binomial model; the positive abundance-occupancy relationships (AORs) and abundance-variance relationships (AVRs) common for parasitic systems apply to the basic infection parameters. The form of the negative binomial distribution is shaped by two parameters-k and θ, the former being a metric of the infection variability, which depends on the host's individual resistance, and the latter representing the parasites' reproduction and establishment success rates. A rise in the parameter k indicates increased aggregation and a higher parameter θ points to a more uniform frequency distribution. These parameters can be used as a representative tool for monitoring the parasite communities in salmonid fishes, including in aquaculture.

Do fungi look like macroparasites? Quantifying the patterns and mechanisms of aggregation for host-fungal parasite relationships

Most hosts contain few parasites, whereas few hosts contain many. This pattern, known as aggregation, is well-documented in macroparasites where parasite intensity distribution among hosts affects host-parasite dynamics. Infection intensity also drives fungal disease dynamics, but we lack a basic understanding of host-fungal aggregation patterns, how they compare to macroparasites, and if they reflect biological processes. To address these gaps, we characterized aggregation of the fungal pathogen Batrachochytrium dendrobatidis (Bd) in amphibian hosts. Utilizing the slope of Taylor's Power Law, we found Bd intensity distributions were more aggregated than macroparasites, conforming closely to lognormal distributions. We observed that Bd aggregation patterns are strongly correlated with known biological processes operating in amphibian populations, such as epizoological phase-invasion, post-invasion, and enzootic-and intensity-dependent disease mortality. Using intensity-dependent mathematical models, we found evidence of evolution of host resistance based on aggregation shifts in systems persisting with Bd following disease-induced declines. Our results show that Bd aggregation is highly conserved across disparate systems and is distinct from aggregation patterns in macroparasites, and contains signatures of potential biological processes of amphibian-Bd systems. Our work lays a foundation to unite host-fungal dynamics under a common theoretical framework and inform future modeling approaches that may elucidate host-fungus interactions.

The Distribution and Host-Association of the Vector Chigger Species Leptotrombidium imphalum in Southwest China

Leptotrombidium imphalum is a species of chigger mites, and it can serve as a transmitting vector of scrub typhus. Southwest China is an important focus of scrub typhus. Based on the field investigation in southwest China from 2001 to 2022, this article presents the first report on the distribution and infestation of L. imphalum on rodents and other sympatric small mammals in the region. A total of 2161 L. imphalum were identified from 218 small mammal hosts in 21 of 114 survey sites. The 17 host species of L. imphalum crossed 13 genera and 5 families in 3 orders (Rodentia, Eulipotyphla, and Scandentia), indicating the low host specificity of the mite. The Asian house rat (Rattus tanezumi) was the dominant host species in the 21 sites where L. imphalum were collected, and 49.38% of mites were found on R. tanezumi. Different small mammals had different susceptibility to the infestation of L. imphalum. The prevalence (PM = 27.66%), infestation mean abundance (MA = 6 mites/per examined host), and mean intensity (MI = 21.69 mites/per infested host) for L. imphalum on the shrew gymnure (Neotetracus sinensis) were much higher than those on other host species (p < 0.05), indicating N. sinensis had a high susceptibility to the infestation of L. imphalum. The infestation indices for L. imphalum on small mammal hosts varied along different altitude and latitude gradients (p < 0.05), indicating the environmental heterogeneity of the mite infestation. Leptotrombidium imphalum exhibited an aggregated distribution among different individuals of its hosts. Besides the low host specificity of L. imphalum, the prevalence of the mite was positively correlated with the occurrence of scrub typhus, indicating the potential risk of the mite.

Interrelationships and properties of parasite aggregation measures: a user's guide

Aggregation of macroparasites among hosts is nearly universal among parasite-host associations. Researchers testing hypotheses on origins of parasite aggregation and its importance to parasite and host population ecology have used different measures of aggregation that are not necessarily measuring the same thing, potentially clouding our understanding of underlying epidemiological processes. We highlight these differences in meanings by exploring properties and interrelationships of six common measures of parasite aggregation, and provide a "user's guide" to inform researchers' decisions regarding their application. We compared the mathematical expressions of the different measures of aggregation, and ran two series of simulations and analyses. The first simulations tested the effect of random removals of parasites on aggregation levels under different conditions, while the second explored interrelationships between the measures, as well as between other individual parasitological sample measures (i.e. mean abundance, prevalence) and aggregation. Results of simulations and analyses showed that the six measures of aggregation could be separated readily into three groups: the variance-to-mean ratio (VMR) together with mean crowding, patchiness with k of the negative binomial, and Poulin's D with Hoover's index. These three pairs of measures showed differing responses to random parasite removals and differing relations with mean abundance and/or prevalence, highlighting that metrics capture different variation in other sample measures and different attributes of aggregation. We used results of our simulations and analyses, and a literature review, to list the properties, advantages, and disadvantages of each aggregation metric. We provide a comprehensive exploration of what is assessed by each metric, as a guide to metric choice. We implore researchers to provide enough information such that aggregation measures from each group are reported or can be readily calculated. Such steps are needed to allow large-scale analyses of variation in degrees of aggregation within and among parasite-host associations, to uncover epidemiological processes shaping parasite distributions.

Toward Predicting Nanoparticle Distribution in Heterogeneous Tumor Tissues

Nanobio interaction studies have generated a significant amount of data. An important next step is to organize the data and design computational techniques to analyze the nanobio interactions. Here we developed a computational technique to correlate the nanoparticle spatial distribution within heterogeneous solid tumors. This approach led to greater than 88% predictive accuracy of nanoparticle location within a tumor tissue. This proof-of-concept study shows that tumor heterogeneity might be defined computationally by the patterns of biological structures within the tissue, enabling the identification of tumor patterns for nanoparticle accumulation.

On Spatiotemporal Overdispersion and Macroparasite Accumulation in Hosts Leading to Aggregation: A Quantitative Framework

In many host-parasite systems, overdispersion in the distribution of macroparasites leads to parasite aggregation in the host population. This overdispersed distribution is often characterized by the negative binomial or by the power law. The aggregation is shown by a clustering of parasites in certain hosts, while other hosts have few or none. Here, I present a theory behind the overdispersion in complex spatiotemporal systems as well as a computational analysis for tracking the behavior of transmissible diseases with this kind of dynamics. I present a framework where heterogeneity and complexity in host-parasite systems are related to aggregation. I discuss the problem of focusing only on the average parasite burden without observing the risk posed by the associated variance; the consequences of under- or overestimation of disease transmission in a heterogenous system and environment; the advantage of including the network of social interaction in epidemiological modeling; and the implication of overdispersion in the management of health systems during outbreaks.

Identifying sources of variation in parasite aggregation

Aggregation of macroparasites among hosts is a near-universal pattern, and has important consequences for the stability of host-parasite associations and the impacts of disease. Identifying which potential drivers are contributing to levels of aggregation observed in parasite-host associations is challenging, particularly for observational studies. We apply beta regressions in a Bayesian framework to determine predictors of aggregation, quantified using Poulin's index of discrepancy (D), for 13 species of parasites infecting Icelandic Rock Ptarmigan (Lagopus muta) collected over 12 years. 1,140 ptarmigan were collected using sampling protocols maximizing consistency of sample sizes and of composition of host ages and sexes represented across years from 2006-2017. Parasite species, taxonomic group (insect, mite, coccidian, or nematode), and whether the parasite was an ecto- or endoparasite were tested as predictors of aggregation, either alone or by modulating an effect of parasite mean abundance on D. Parasite species was an important predictor of aggregation in models. Despite variation in D across samples and years, relatively consistent aggregation was demonstrated for each specific host-parasite association, but not for broader taxonomic groups, after taking sample mean abundance into account. Furthermore, sample mean abundance was consistently and inversely related to aggregation among the nine ectoparasites, however no relationship between mean abundance and aggregation was observed among the four endoparasites. We discuss sources of variation in observed aggregation, sources both statistical and biological in nature, and show that aggregation is predictable, and distinguishable, among infecting species. We propose explanations for observed patterns and call for the review and re-analysis of parasite and other symbiont distributions using beta regression to identify important drivers of aggregation-both broad and association-specific.

A Census of Human Methionine-Rich Prion-like Domain-Containing Proteins

Methionine-rich prion-like proteins can regulate liquid–liquid phase separation processes in response to stresses. To date, however, very few proteins have been identified as methionine-rich prion-like. Herein, we have performed a computational survey of the human proteome to search for methionine-rich prion-like domains. We present a census of 51 manually curated methionine-rich prion-like proteins. Our results show that these proteins tend to be modular in nature, with molecular sizes significantly greater than those we would expect due to random sampling effects. These proteins also exhibit a remarkably high degree of spatial compaction when compared to average human proteins, even when protein size is accounted for. Computational evidence suggests that such a high degree of compactness might be due to the aggregation of methionine residues, pointing to a potential redox regulation of compactness. Gene ontology and network analyses, performed to shed light on the biological processes in which these proteins might participate, indicate that methionine-rich and non-methionine-rich prion-like proteins share gene ontology terms related to the regulation of transcription and translation but, more interestingly, these analyses also reveal that proteins from the methionine-rich group tend to share more gene ontology terms among them than they do with their non-methionine-rich prion-like counterparts.

Parasite communities and their ecological implications: comparative approach on three sympatric clupeiform fish populations (Actinopterygii: Clupeiformes), off Rio de Janeiro, Brazil

Fish parasite communities can be directly influenced by characteristics of host species. However, little is known about the host-parasite relationships in commercially important fish of the southeastern Atlantic. To address this knowledge gap, a comparative analysis of the parasite communities of three sympatric Clupeiformes was conducted. Cetengraulis edentulus (Engraulidae), Opisthonema oglinum (Clupeidae) and Sardinella brasiliensis (Clupeidae) were collected from an estuarine lagoon near Rio de Janeiro, Brazil. Prevalence, abundance and aggregation were estimated for infrapopulations; richness, diversity, evenness and dominance for infracommunities. The three component communities were compared using both quantitative and qualitative components. Canonical discriminant analysis was used to determine if a host population could be characterised by the component community of its parasites. Multivariate models revealed that host species, a proxy for diet and phylogenetic relationships, was the main factor influencing the composition of parasite infracommunities. Diet was found to be the main factor shaping the communities of endoparasites, in which digeneans were dominant and best indicator of host population. Ectoparasites (copepods, isopods and monogeneans) displayed strong host-specificity with some species restricted to a single host population. The similarity of the component communities of the two clupeid populations demonstrated the influence of host phylogeny. Parasite infracommunities exhibited low diversity and high dominance, with many taxa restricted to a single host species (specialists) and few occurring in more than one (generalists). Host phylogeny and by extension, diet, morphology and coevolution with parasites appear to be important factors in determining the host-parasite relationships of clupeiform fish in the southeastern Atlantic.

Context-dependent host dispersal and habitat fragmentation determine heterogeneity in infected tick burdens: an agent-based modelling study

As the incidence of tick-borne diseases has sharply increased over the past decade, with serious consequences for human and animal health, there is a need to identify ecological drivers contributing to heterogeneity in tick-borne disease risk. In particular, the relative importance of animal host dispersal behaviour in its three context-dependent phases of emigration, transfer and settlement is relatively unexplored. We built a spatially explicit agent-based model to investigate how the host dispersal process, in concert with the tick and host demographic processes, habitat fragmentation and the pathogen transmission process, affects infected tick distributions among hosts. A sensitivity analysis explored the impacts of different input parameters on infected tick burdens on hosts and infected tick distributions among hosts. Our simulations indicate that ecological predictors of infected tick burdens differed among the post-egg life stages of ticks, with tick attachment and detachment, tick questing activity and pathogen transmission dynamics identified as key processes, in a coherent way. We also found that the type of host settlement strategy and the proportion of habitat suitable for hosts determined super-spreading of infected ticks. We developed a theoretical mechanistic framework that can serve as a first step towards applied studies of on-the-ground public health intervention strategies.

Context-dependent host dispersal and habitat fragmentation determine heterogeneity in infected tick burdens: an agent-based modelling study

As the incidence of tick-borne diseases has sharply increased over the past decade, with serious consequences for human and animal health, there is a need to identify ecological drivers contributing to heterogeneity in tick-borne disease risk. In particular, the relative importance of animal host dispersal behaviour in its three context-dependent phases of emigration, transfer and settlement is relatively unexplored. We built a spatially explicit agent-based model to investigate how the host dispersal process, in concert with the tick and host demographic processes, habitat fragmentation and the pathogen transmission process, affects infected tick distributions among hosts. A sensitivity analysis explored the impacts of different input parameters on infected tick burdens on hosts and infected tick distributions among hosts. Our simulations indicate that ecological predictors of infected tick burdens differed among the post-egg life stages of ticks, with tick attachment and detachment, tick questing activity and pathogen transmission dynamics identified as key processes, in a coherent way. We also found that the type of host settlement strategy and the proportion of habitat suitable for hosts determined super-spreading of infected ticks. We developed a theoretical mechanistic framework that can serve as a first step towards applied studies of on-the-ground public health intervention strategies.