1) The role of microbial oscillations in animal senescence
Understanding rates of animal senescence is crucial for predicting demographic processes, and the mechanisms underpinning senescence is an active area of research 72–74. Whilst research on animal senescence has focused on changes to immunity 75, telomeres 76, stress hormones 77, and gut microbiota composition 24, research on humans and primates have demonstrated that an additional characteristic of ageing is the dampening of circadian rhythms 77–79, leading to disrupted sleep-wake cycles and physiology. Changes to gut microbiome rhythmicity with age are implicated in this process 80–82.
The involvement of microbial oscillations in senescence suggests that microbial oscillations should decline in old age (Fig. 4a), yet this has rarely been tested in either captive or wild settings. In wild meerkats, there was little evidence for microbial senescence, with old meerkats demonstrating microbial rhythms that were as strong as younger individuals 26, despite old (and generally dominant) individuals generally losing body condition 83 and having higher rates of telomere loss 84. However, because only dominant individuals tend to reach old age in this species, physiological senescence may be mitigated by the benefits of group living and alpha status, which decrease mortality risk 72. Exploiting systems with high survival rates that have commonly been used to model senescence and demography, such as seabirds 85,86, may help clarify this question.
2) Gut microbial rhythms and pathogen defence
In mice, gut microbial oscillations reduce host susceptibility to gut pathogens such as Salmonella during the active phase by triggering the release of AMPs into the gut 13. Reducing the abundance of mucosal commensal SFB increases host susceptibility to Salmonella infection and also removes circadian rhythms in susceptibility 13, demonstrating that the rhythmic activity of gut mucosal commensals is a key mechanism governing microbiome-mediated pathogen defence. Testing for associations between the abundance and rhythmicity in mucosal commensals and infection status may therefore be a more effective method of uncovering the link between the gut microbiota and pathogen susceptibility than focusing on overall gut microbial diversity alone. Arhythmic gut microbial communities have been linked to disease in humans 34, and therefore it might be expected that individuals with disrupted or dampened gut microbiota rhythms are more susceptible to infection (Fig. 4b).
Circadian rhythms in animal susceptibility and pathogen reproduction and transmission are well documented 18,87, with hosts and pathogens having coevolved defensive and offensive rhythms, respectively 18. Nevertheless, many fundamental questions remain entirely unanswered: Do gut microbial rhythms protect the host against a broad range of pathogens, or are they only effective for specific gut pathogens? Microbial rhythms control the release of AMPs, which are effective against a wide range of pathogens including bacteria, fungi and viruses 88. Thus, it is likely that microbial rhythms protect the host against a broad range of pathogenic agents entering the gut. However, the gut is not the only entry point of pathogens and it remains unknown whether microbial rhythms also play a role in pathogen defence more generally.
Even less explored is the connection between gut microbial oscillations and adaptive immunity, which is an essential pillar of resistance again recurring pathogenic challenges in jawed vertebrates 89. Ample evidence that adaptive and innate immunity interact to regulate the gut microbiota exist. For example, the co-expression of MHC class II molecules together with LPS-activated TLR4 enhances the production of AMPs 90. In addition, gut microbial metabolites influence the expression of the mammalian circadian clock gene Per2 7,91, which is responsible for mounting both innate and adaptive responses to infection 92. The maintenance of gut microbial homeostasis, which is crucial for effective pathogen defence, might therefore represent a joint venture of adaptive and innate immunity 93. Still, information on whether gut microbial oscillations synergise with innate and adaptive immunity are lacking.
3) The adaptive significance of gut microbial oscillations
In which evolutionary contexts do we expect the evolution of gut microbial oscillations, and when would we expect food intake and the gut microbiome to entrain host immunity? Based on findings from murine models, one predicts that food intake, metabolic requirement, and pathogen exposure are synchronised to peak at the start of the active phase (i.e., at dusk for mice). Such correlation between feeding, metabolic processes and immune activity is expected to be the norm, given that feeding introduces both nutrients and pathogens to the gut. Hence, hosts appear to have co-opted the gut microbiota to mediate both metabolic and innate immune function simultaneously.
Conversely, microbiota-independent mechanisms may be expected in species where metabolic requirements are not circadian, as well as in species where metabolic requirements and pathogen exposure are uncoupled. For example, ectotherms exhibit circadian rhythms in body temperature and activity 94–96, and have some level of circadian cycles in metabolism 97 and immunity 98,99, but feeding patterns are often not circadian (e.g. for large reptiles such as snakes and crocodiles that are infrequent feeders). In these cases, does the gut microbiota undergo diurnal oscillations, and is the entrainment of innate immunity completely independent of the gut microbiota? Given findings from laboratory mice, one might expect that diurnal rhythms of the gut microbiota to be strongest after feeding (Fig. 4c). However, evidence from Burmese pythons suggests that shifts in the post-prandial gut microbiota last for many days 100, although this study did not record time of day samples were harvested, therefore it is unknown whether feeding shifted microbial rhythms (if any) as well as composition.
Species where pathogen exposure is not closely correlated with timing of feeding provide an addition example where mechanisms regulating circadian rhythms in immunity are microbiota-independent. In social or gregarious animals, microbiota are often shared 101 and pathogen exposure is high 102–104. Peaks in pathogen exposure or activation of immunity may therefore not be limited to mealtimes. This raises the question as to whether social animals have altered circadian rhythms in immune function compared to solitary species, and whether such adaptations are mediated by the gut microbiota.
Considering microbial rhythms in the context of metabolic and immune requirements throughout the day may provide a useful framework to predict the strength and the functional role of gut microbial oscillations that goes beyond light and temperature cycles. Nevertheless, investigating microbial oscillations across latitudes and in environments with extreme light or temperature conditions (e.g. cave, arctic, or desert animals) will aid our understanding of the circumstances under which microbial rhythms occur. For example, gut microbiome rhythms in meerkats may be particular strong due to the arid environment they inhabit 26, which is characterised by steep temperature differentials between day and night. This extreme fluctuation induces nightly torpor in small desert mammals 105, and whilst it is unclear whether meerkats undergo a similar process, it might be expected that extreme temperatures exert metabolic constraints that both influence and are influenced by the gut microbiota.
4) Interactions between circadian and seasonal rhythms
Many species undergo striking changes in life-history strategies between seasons, with hibernation and long-distance migration representing two of the most extreme life-history responses to seasonal changes in climate. Seasonal shifts in gut microbiome composition and function have been well described 43,106–110, but emerging evidence suggests that changes in function may be mediated via increasing or decreasing the amplitude of host circadian rhythms 91. In giant pandas, seasonal switching of diet from bamboo leaves to shoots causes an increase in the bacterial metabolite butyrate in the gut microbiota, and when transferred to mice, this causes the upregulation of clock gene Per2, which increases lipid production and fat deposition in spring 91. This study does not measure gut microbial oscillations directly however, and it is unclear whether microbial rhythms also increase in amplitude during spring. Yet, the findings suggest that seasonal cycling of the gut microbiota functions via interacting with host circadian rhythms.
In addition to seasonal diet switches, seasonal changes to life history stages that involve metabolic restructuring such as hibernation (Fig. 4d), and migration (Fig. 4e), and even reproduction may also be paired with changes to the amplitude of their gut microbial rhythms. Shifts in the gut microbiota during hibernation adaptively lower metabolism and recycle nitrogen 42,44,111, yet it remains unknown how these functional changes interact with or are mediated by diurnal rhythms. Seasonal switches in strategies may take more unpredictable and fascinating forms. For instance, the circadian rhythms of some arctic-breeding shorebirds become uncoupled from environmental cues during breeding due to pressures of incubation and predators, with social cues becoming the dominant form of entrainment 112. How might such changes be reflected in the gut microbiome?
5) The effect of urbanisation on gut microbial rhythms
Urbanization is rapidly altering wildlife environments and activity patterns. Medium to large mammals are becoming more nocturnal to escape human disturbance 113, whereas small mammals that are normally nocturnal are active around the clock in urban areas 114. Artificial light is causing birds and bats to extend and reduce their activity periods, respectively 115,116, and is also associated with altered physiology and immune responses 117–119. Urban habitats also offer different diets, with many urban animals becoming scavengers or being provisioned by humans 120, and are associated with pollution 121 and higher pathogen diversity 122 than natural habitats. How these shifts in behaviour and exposure to pathogens and pollution are affecting health for both humans and wildlife via circadian mismatching is an outstanding question of urgent need of attention 69,123,124, given ongoing and rapid human encroachment into natural habitats.
Urbanised environments offer the rare opportunity to experimentally test the impact of changes to abiotic (e.g., light, temperature) and biotic (e.g., diet, pathogen pressure) condition on microbial circadian rhythms compared with wildlife inhabiting natural environments 125. How might the interacting pressures faced by urban-adapted species affect the gut microbiota, and what are the consequences for wildlife health? Accumulating evidence from across phylogenetically-diverse species suggests that urbanization generates a more ‘humanized’ gut microbiota, with a higher proportion of opportunistic pathogens 126–131. Yet, whether urbanisation is altering microbial rhythms is still unclear. In humans, urbanisation is associated with a loss of seasonal rhythms in the gut microbiota 106,132, indicating that biological rhythms might be disrupted by urban lifestyles. Wildlife health may be negatively affected by urbanisation and artificial light if changes to activity patters (e.g., timing of feeding) or altered diet disrupts gut microbial oscillations (Fig. 4e). Constant light or dark leads to a loss of microbial rhythms in both chickens 32 and mice 35, and this alteration is at least in part due to sensory signalling from the brain rather than changes to feeding times 133. Diets high in fat also dampen microbial rhythms and thereby lead to dysbiosis – an imbalance in the microbiome that has negative health outcomes 39,134,135. Together, these indicate that urbanisation may alter microbial rhythms via multiple mechanisms.
Studying gut microbial rhythms in wildlife
Field ecologists face a number of challenges that may have acted to delay the integration of circadian rhythms into field ecology, such as limited availability of study animals across a 24-hour period. However, as long as individuals can be sampled over the morning and preferably also the afternoon (e.g. 26), many questions on microbial oscillations can be tackled. Indeed, the period after the start of the active phase is often when the largest changes occur and therefore reporting just this part of the diurnal cycle can be informative. Whilst a longitudinal study design is preferable, the strength of microbial oscillations reported so far suggest that cross-sectional study designs may also have sufficient statistical power to detect predictable microbial oscillations. For example, in meerkats, sensitivity analyses that restricted analysis to only 20 (cross-sectional) samples per hour during daylight hours (total n ≈ 240) still detected the same microbial oscillations reported with the full dataset (total n ≈1100) 26. Notably, a huge array of wildlife gut microbial datasets exists, and where the time of collection is known, these can be reanalysed to further our understanding of microbial diurnal rhythms, with comparative studies across species being particularly informative.
A common obstacle in identifying meaningful associations between the gut microbiota and host physiology is the sheer diversity of gut microbial communities and available physiological markers. Future studies on non-model organisms may therefore benefit from focusing on the key taxa and physiological markers identified from experimental studies to date. Findings from mice indicate that mucosal-associated commensals, in particular SFBs which are found across vertebrates 136, play a fundamental role in mediating physiological homeostasis and immunomodulation by attaching to the intestinal epithelium at the start of the active phase. The identity and oscillations of these specific commensals are therefore likely to be disproportionally important for identifying associations between the gut microbiota and host physiology in natural populations. In addition, gut sIgA and AMPs are two facets of immunity that have been strongly implicated in circadian interactions with the gut microbiota, whilst the microbial metabolites butyrate, flagellin, and LPS have been implicated in circadian interactions that regulate metabolic signalling pathways and innate immunity. Applying these physiological markers may therefore be particularly suitable for determining whether mechanisms identified in laboratory systems have broad biological relevance for natural populations.
Conclusions
Microbial diurnal rhythms are likely widespread and pivotal for mediating physiological homeostasis and pathogen defence, yet their study has been neglected in wild populations. Whilst the mechanisms underpinning the circadian crosstalk between the host immune system and the gut microbiota is still an active area of research, key commensal taxa that rhythmically attach to the host intestinal epithelium play a critical role in triggering the upregulation of metabolism and at innate immunity the start of the active phase. A future focus on how gut microbiomes change over the day across host species with diverse biology (e.g., ectotherms, hibernating animals) and ecology (e.g., social animals, urban wildlife) will advance our understanding of their function and adaptive significance, and may illuminate the processes underpinning the breakdown of gut microbiota function during infection, senescence, and global change.
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