Physical Cues Controlling Seasonal Immune Allocation in a Natural Piscine Model

Abstract

Seasonal patterns in immunity are frequently observed in vertebrates but are poorly understood. Here, we focused on a natural piscine model, the three-spined stickleback (Gasterosteus aculeatus), and asked how seasonal immune allocation is driven by physical variables (time, light, and heat). Using functionally-relevant gene expression metrics as a reporter of seasonal immune allocation, we synchronously sampled fish monthly from the wild (two habitats), and from semi-natural outdoors mesocosms (stocked from one of the wild habitats). This was repeated across two annual cycles, with continuous within-habitat monitoring of environmental temperature and implementing a manipulation of temperature in the mesocosms. We also conducted a long-term laboratory experiment, subjecting acclimated wild fish to natural and accelerated (×2) photoperiodic change at 7 and 15°C. The laboratory experiment demonstrated that immune allocation was independent of photoperiod and only a very modest effect, at most, was controlled by a tentative endogenous circannual rhythm. On the other hand, experimentally-determined thermal effects were able to quantitatively predict much of the summer–winter fluctuation observed in the field and mesocosms. Importantly, however, temperature was insufficient to fully predict, and occasionally was a poor predictor of, natural patterns. Thermal effects can thus be overridden by other (unidentified) natural environmental variation and do not take the form of an unavoidable constraint due to cold-blooded physiology. This is consistent with a context-dependent strategic control of immunity in response to temperature variation, and points to the existence of temperature-sensitive regulatory circuits that might be conserved in other vertebrates.

Not going with the flow: Locomotor activity does not constrain immunity in a wild fish

“…Monthly data were missing for October and December 2014 due to inclement weather. Gene expression data for the RHD fish have previously been reported (Stewart, Hablutzel, et al, ). As previously described, fish were individually captured with dipnets and immediately killed by concussion and decerebration, then conserved in RNA stabilization solution and transferred to −80°C for long‐term storage (Brown et al, ).…”

“…In employing fish from a lentic habitat for our experiment, we expected that these might be less preconditioned to sustained swimming and thus allow more sensitive detection of any locomotion effect on immune gene expression. We also note that natural variation in the gene expression readouts that we employ below is largely due to consistent environmental responses, with fish of different genetic identity in different habitats responding similarly to seasonal change (Brown et al, ; Stewart, Hablutzel, et al, ). Thus, differences in the genetic background of the study fish are expected to be unimportant.…”

“…We quantified gene expression in RNA extracted from homogenized whole fish by reverse transcription quantitative real‐time PCR (QPCR) following previously described methods (Brown et al, ; Hablützel et al, ; Stewart, Hablutzel, et al, ). The advantages of using whole fish samples are considered in (Hablützel et al, ).…”

“…In both the field and experiment, we used a standard set of gene expression measurements that we have previously demonstrated to precisely report a dominant genome‐wide seasonal oscillation in immune‐associated gene expression in wild sticklebacks (Brown et al, ; Stewart, Hablutzel, et al, ). This oscillation corresponds to experimentally determined infection resistance (Stewart, Hablützel, et al, ; Stewart, Hablutzel, et al, ) and is partly driven directly by environmental temperature and partly by other, as yet unidentified, seasonal environmental variation that might include variation in flow effects (Stewart, Hablützel, et al, ; Stewart, Hablutzel, et al, ). Seasonal progression explains more genome‐wide variation in immune‐associated gene expression than other relevant factors (including geographic site, sex, and ontogeny) and is characterized by outlying expression values in the late winter and late summer (Brown et al, ).…”

“…Seasonal progression explains more genome‐wide variation in immune‐associated gene expression than other relevant factors (including geographic site, sex, and ontogeny) and is characterized by outlying expression values in the late winter and late summer (Brown et al, ). For simplicity, as previously described (Stewart, Hablutzel, et al, ), we are able to combine our set of gene expression measurements into a single representative index (seasonal reporter index, SRI). Moreover, to cross‐reference gene expression variation and our experimental treatments to a functional phenotype, we also directly measured infection resistance in our flow experiment.…”