Food ingestion is one of the most basic features of all organisms. However, obtaining precise—and high‐throughput—estimates of feeding rates remains challenging, particularly for small, aquatic herbivores such as zooplankton, snails, and tadpoles. These animals typically consume low volumes of food that are time‐consuming to accurately measure. We extend a standard high‐throughput fluorometry technique, which uses a microplate reader and 96‐well plates, as a practical tool for studies in ecology, evolution, and disease biology. We outline technical and methodological details to optimize quantification of individual feeding rates, improve accuracy, and minimize sampling error. This high‐throughput assay offers several advantages over previous methods, including i) substantially reduced time allotments per sample to facilitate larger, more efficient experiments; ii) technical replicates; and iii) conversion of in vivo measurements to units (mL‐1 hr‐1 ind‐1) which enables broad‐scale comparisons across an array of taxa and studies. To evaluate the accuracy and feasibility of our approach, we use the zooplankton, Daphnia dentifera, as a case study. Our results indicate that this procedure accurately quantifies feeding rates and highlights differences among seven genotypes. The method detailed here has broad applicability to a diverse array of aquatic taxa, their resources, environmental contaminants (e.g., plastics), and infectious agents. We discuss simple extensions to quantify epidemiologically relevant traits, such as pathogen exposure and transmission rates, for infectious agents with oral or trophic transmission.
Circadian rhythms enable organisms to mediate their molecular and physiological processes with changes in their environment. Although feeding behavior directly affects within-organism processes, there are few examples of a circadian rhythm in this key behavior. Here, we show that Daphnia have a nocturnal circadian rhythm in feeding behavior that corresponds with their diel vertical migration (DVM), an important life history strategy for predator and UV avoidance. In addition, this feeding rhythm appears to be temperature compensated, which suggests that feeding behavior is robust to seasonal changes in water temperature. A circadian rhythm in feeding behavior can impact energetically demanding processes like metabolism and immunity, which may have drastic effects on susceptibility to disease, starvation risk, and ultimately, fitness.
The incidence of zoonotic diseases is increasing worldwide, which makes identifying parasites likely to become zoonotic and hosts likely to harbour zoonotic parasites a critical concern. Prior work indicates that there is a higher risk of zoonotic spillover accruing from closely related hosts and from hosts that are infected with a high phylogenetic diversity of parasites. This suggests that host and parasite evolutionary history may be important drivers of spillover, but identifying whether host–parasite associations are more strongly structured by the host, parasite or both requires co-phylogenetic analyses that combine host–parasite association data with host and parasite phylogenies. Here, we use host–parasite datasets containing associations between helminth taxa and free-range mammals in combination with phylogenetic models to explore whether host, parasite, or both host and parasite evolutionary history influences host–parasite associations. We find that host phylogenetic history is most important for driving patterns of helminth-mammal association, indicating that zoonoses are most likely to come from a host's close relatives. More broadly, our results suggest that co-phylogenetic analyses across broad taxonomic scales can provide a novel perspective for surveying potential emerging infectious diseases. This article is part of the theme issue ‘Infectious disease macroecology: parasite diversity and dynamics across the globe’.
Host-associated microbial communities are impacted by external and within-host factors, i.e., diet and feeding behavior. For organisms known to have a circadian rhythm in feeding behavior, microbiome composition is likely impacted by the different rates of microbe introduction and removal across a daily cycle, in addition to any diet-induced changes in microbial interactions. Here, we measured feeding behavior and used 16S rRNA sequencing to compare the microbial community across a diel cycle in two distantly related species of Daphnia, that differ in their life history traits, to assess how daily feeding patterns impact microbiome composition. We find that Daphnia species reared under similar laboratory conditions have significantly different microbial communities. Additionally, we reveal that Daphnia have daily differences in their microbial composition that correspond with feeding behavior, such that there is greater microbiome diversity at night during the host’s active feeding phase. These results highlight that zooplankton microbiomes are relatively distinct and are likely influenced by host phylogeny.
Biological rhythms mediate important within‐host processes such as metabolism, immunity, and behavior which are often linked to combating disease exposure. For many hosts, exposure to pathogens occurs while feeding. However, the link between feeding rhythms and infection risk is unclear because feeding behavior is tightly coupled with immune and metabolic processes which may decrease susceptibility to infection. Here, we use the Daphnia dentifera–Metschnikowia bicuspidata host–pathogen system to determine how rhythms in feeding rate and immune function mediate infection risk. The host is known to have a nocturnal circadian rhythm in feeding rate, yet we found that they do not exhibit a circadian rhythm in phenoloxidase activity. We found that the time of day when individuals are exposed to pathogens affects the probability of infection with higher infection prevalence at night, indicating that infection risk is driven by a host's circadian rhythm in feeding behavior. These results suggest that the natural circadian rhythm of the host should be considered when addressing epidemiological dynamics.
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