The Mammalian Clockwork Mechanism

Multiple gene-protein-gene feedback loops support the mammalian molecular clock mechanism that exists in almost all mammalian cell types (Reppert & Weaver, 2002). The genes in question consist of a group of highly conserved core components termed clock genes. The only known tissues that show constant, rather than cyclic, expression of clock genes are cells from the thymus and testis, and this is thought to be due to the immature, differentiating nature of cells from these tissues (Alvarez & Sehgal, 2005). Core clock components have been defined as genes whose protein products are necessary for the generation and/or regulation of circadian rhythms within individual cells (Takahashi, 2004). The core components can be assembled into a diagram of interconnecting loops involving multiple transcriptional feedback circuits, which are, in turn, regulated by post-translational modification processes (Figure 18.2).

Figure 18.2 Model of mammalian molecular clock. Transcription of Period (mPer) and Cryptochrome (Cry) genes is initiated by CLOCK–BMAL1 heterodimers. The CRY and PER2 proteins heterodimerise and enter into the nucleus where they shut off their own synthesis. PER2 has an additional role in the activation of the Bmal1 gene. The kinase CKIɛ may affect nuclear translocation and half-life of mPER proteins via phosphorylation. A second feedback loop comprising the opposing activities of the ROR and REVERB orphan nuclear receptors regulate Bmal1 transcription. The next cycle begins when the concentration of the repressors decreases. This interplay of genes and their protein products give rise to the temporal clock gene expression patterns observed in Figure 18.3. Adapted from Ripperger & Schibler (2001), with permission from Elsevier.

The primary feedback loop consists of three Period genes (Per1, Per2, and Per3), two cryptochrome genes (Cry1 and Cry2), a Clock gene, and the gene encoding brain-muscle-Arnt-like protein 1 (Bmal11) (Dunlap, 1999). With the exception of Clock, which is constitutively expressed in most tissues, all transcripts exhibit oscillatory expression, with Per and Cry transcripts peaking in reverse phase to those of Bmal1 (Morse & Sassone-Corsi, 2002). Positive regulation is provided by CLOCK and BMAL1, both members of the basic helix-loop-helix (bHLH)-PAS (Period-Arnt-Single-minded) transcription factor family. Dimerized CLOCK-BMAL1 complexes induce the expression of a large number of output genes, as well as binding to E-box enhancer motifs upstream of their own repressor genes, Cry1 and Cry2, and Per1 and Per2 to initiate their transcription (Gekakis et al., 1998; Kume et al., 1999; Bunger et al., 2000; Zheng et al., 2001). Over the course of the day, the PER and CRY proteins accumulate and form multimers in the cytoplasm, where they are targets for phosphorylation by casein kinase Iɛ (CKIɛ) and glycogen synthase kinase-3 (GSK3) (Iitaka et al., 2005). This facilitates translocation to the nucleus where they interact with the CLOCK-BMAL1 complexes to repress their own activation in a negative feedback manner (Kume et al., 1999; Okamura et al., 1999; Shearman et al., 2000; Lee et al., 2001; Sato et al., 2006). For each circadian cycle to end, the PER and CRY proteins are degraded by further CKIɛ phosphorylation and degradation, which releases the repression of the CLOCK-BMAL1 transcription and allows the next cycle to start (Gallego & Virshup, 2007).

Figure 18.3 Antiphase daily expressions of BMAL1 and rPer2 mRNA in peripheral tissues. Rats were housed in a 12-hour light–12-hour dark (LD) cycle (lights on at ZT 0). The graphs depict a comparison of the expression patterns of BMAL1 and rPer2 mRNA in each tissue. The maximum value was expressed as 100% in each gene as determined by Northern blot analysis of total RNA. Reprinted from Oishi et al. (1998), with permission from Elsevier.

CLOCK-BMAL1 induction of output genes contribute to rhythmical biological processes outside of the clockwork mechanism. Microarray studies have revealed that up to 10% of the transcriptome is under circadian regulation and that unique subsets of genes oscillate with 24-hour profiles in each individual tissue (Akhtar et al., 2002; Kita et al., 2002; Panda et al., 2002; Storch et al., 2002; Ueda et al., 2002; Zambon et al., 2003; Desai et al., 2004; Yamamoto et al., 2004). Recent studies have identified an additional stabilizing feedback loop within the molecular clock mechanism comprising the opposing activities of the RORα and REV-ERBα orphan nuclear receptors (Sato et al., 2004). RORα acts as a transcriptional activator of Bmal1 while REV-ERBα inhibits its expression (Sato et al., 2004). This combination of loops, in conjunction with important post-translational mechanisms contributing to the time delays needed for the 24-hour period of the clock (Reppert & Weaver, 2002), ensures perpetuation of the self-sustaining nature of the molecular clock. Increasing complexity within this molecular mechanism continues to be revealed with recent demonstrations of crucial roles for new clock genes (Honma et al., 2002; Godinho et al., 2007; Siepka et al., 2007).

Hierarchy of Master and Peripheral Clocks

The mammalian circadian system is organized as a hierarchy of oscillators. The “master” clock in the SCN resides at the top of this hierarchy and is responsible for receiving and transducing the light information from the retina to directly drive many rhythms throughout the organism via neural and hormonal pathways. In this manner, the SCN synchronizes peripheral tissue clocks much as a conductor might conduct an orchestra, thereby achieving harmony in the many physiological and biochemical rhythms of the body.

The SCN regulates diverse physiological processes, such as blood pressure, heart rate (Arraj & Lemmer, 2006), activity cycles (Aston-Jones et al., 2001), hormone secretion (Weibel & Brandenberger, 2002), metabolism (Kita et al., 2002), immune function (Born et al., 1997; Petrovsky et al., 1998; Arjona & Sarkar, 2006), and body temperature (Moore & Danchenko, 2002). Robust diurnal variations in many physiological parameters have recently been reported in horses and are discussed later in the chapter. Importantly, the molecular components and temporal relationships of clock gene mRNA expression rhythms within rodent peripheral oscillators appear identical to those of the SCN, as exemplified by the antiphase oscillations of PER2 and BMAL1 (Oishi et al., 1998; Yagita et al., 2001; Muhlbauer et al., 2004) (Figure 18.3). A recent exception to this rule is the Clock transcript, which expression has been shown to be rhythmic, as opposed to constitutive, in some tissues outside of the SCN (Lowrey & Takahashi, 2004).

Timing signals from the SCN reach peripheral clocks to ensure that each tissue can then adapt its specific function to the correct time of day by means of tissue-specific circadian regulation of transcription. This phenomenon has been revealed by microarray studies in rodents, which identify unique subsets of genes under circadian regulation in different peripheral tissues (Kita et al., 2002; Panda et al., 2002; Storch et al., 2002; Zambon et al., 2003; Desai et al., 2004; Yamamoto et al., 2004). For example, clock-controlled genes relating to metabolism and detoxification are found to be differentially expressed in microarray analyses of the liver (Akhtar et al., 2002; Kita et al., 2002). Moreover, very little overlap was found between groups of oscillating circadian genes identified in the heart and the liver in one study (Storch et al., 2002), and between the liver and the SCN in another (Panda et al., 2002). These findings support a specialized and local role for circadian clocks in each tissue.

An important differentiation between the SCN clock and peripheral clocks was identified using transgenic rats in which luciferase was rhythmically expressed under the control of a Per1 promoter (Yamazaki et al., 2000). It was shown that cultured SCN explants are capable of sustaining synchronous 24-hour rhythms of bioluminescence for weeks, whereas rhythmical clock gene expression from explanted peripheral tissues quickly lose amplitude and dampen in the absence of resetting stimuli from the SCN. Dampening of peripheral circadian rhythms ex vivo is now understood to reflect a gradual desynchronizing of many independent cellular oscillators (Welsh et al., 2004), thus defining the role of the SCN as a conductor rather than a driver of the circadian orchestra. Further important studies using cultured rat fibroblast cell lines revealed that the component oscillators within individual cells could be temporarily resynchronized by a number of different methods, most commonly by a change of culture medium to one containing high serum concentration (Balsalobre et al., 1998; Balsalobre et al., 2000). It is therefore very important that researchers involved in cell culture experiments are cognizant of the fact that each change of media likely resets a phase for the cultured cells and, depending on the tissue they are derived from, will influence specific circadian regulated pathways downstream from the clock.

Equine Peripheral Clocks

The equine core clock genes were identified, sequenced, and their chromosomal locations determined in 2006 (Murphy et al., 2007b). This was quickly followed by the first investigation of clock gene expression in the horse by examining temporal profiles of equine Per2, Bmal1, Cry1, and Clock in equine fibroblasts, peripheral blood, and adipose tissue (Murphy et al., 2006) using real-time quantitative PCR detection methods. Blood and adipose tissue were chosen as they permitted minimally invasive tissue collection methods and multiple collection times. Equine fibroblasts of dermal origin were synchronized by shocking the cells with a high-percent serum media for two hours before transfer into a serum-free media. The robust rhythmic oscillations of equine Per2, BMAL1, and Cry1 are clearly evident in Figure 18.4 in response to this treatment. The temporal relationships between the genes closely mimicked those observed in the SCN and peripheral tissues of other species. As fibroblasts are thought to serve as a valid model for investigation of core circadian clock function in mammals (Rosbash, 1998; Yagita et al., 2001), it was hypothesized that a similar molecular clockwork mechanism functioned in the horse. Surprisingly, in vivo results yielded unexpected findings. While low-amplitude clock gene rhythms were revealed in equine adipose tissue, there was no discernible oscillation in equine peripheral blood (Murphy et al., 2006).

Figure 18.4 mRNA levels of Per2, Bmal1, and Cry1 in equine fibroblast cells over a 52-hour period as determined by Real Time quantitative PCR. Expression levels of clock genes are reported as the number of transcripts relative to the number of molecules of housekeeping gene product β-glucuronidase (GUS). Each time point represents the mean ± SEM for three separate experiments (n = 3). Evidence of antiphase expression profiles of Per2 and Bmal1 suggests a similar temporal profile of clock gene expression to that previously observed in the SCN and peripheral tissues of rodents. From data presented in Murphy et al. (2006) and reviewed in Murphy (2009), with permission from Elsevier.

The physiological advantage of a blood clock could be to temporally regulate transcriptional output from circulating leukocyte populations. As a heterogeneous tissue, it might be argued that failure to detect a rhythmic peripheral clock in whole blood is due to different temporal patterns of expression, contributed by a number of differentially synchronized cell types, resulting in a dampened overall rhythm. This hypothesis is supported by a recent finding that more robust clock gene temporal variation is observed in bovine neutrophils than in lymphocytes (Nebzydoski et al., 2010). Clock gene oscillations in human (Takata et al., 2002; Boivin et al., 2003) and rat (Oishi et al., 1998) peripheral blood cells have also been reported. However, Kusanagi et al. (2004) demonstrated that Per1 rhythms in both human mononuclear and polymorphonuclear cell types oscillate in phase with each other, supporting the opposing view that different cell types within a tissue are entrained at the same phase angle.

To make matters more complicated, highly variable inter-individual clock gene expression profiles have recently been documented in human subjects (Teboul et al., 2005), leading to the suggestion that the circadian oscillator in peripheral blood may be regulated differently from other known peripheral clocks. In addition, the absence of a neural communication pathway between the SCN and peripheral blood lends further support to this assumption, as communication between the SCN and peripheral tissues is thought to occur via both neural and humoral mechanisms (Allen et al., 2001; Terazono et al., 2003; Guo et al., 2005). Future studies investigating clock gene expression in specific blood cell subpopulations may shed more light on the absence of oscillating clock genes in equine whole blood.

The evidence that equine adipose tissue possesses an oscillating peripheral clock was the first of its kind in a large mammal (Murphy et al., 2006). Adipose tissue is known to secrete a variety of biologically active molecules including leptin, resistin, and adiponectin (Matsuzawa et al., 2004), many of which have been shown to exhibit diurnal rhythms in humans (Gavrila et al., 2003) and horses (Piccione et al., 2004b; Gordon & McKeever, 2005). Bmal1 is known to regulate adipogenesis in the mouse (Shimba et al., 2005). Furthermore, evidence of an obese phenotype in the Clock mutant mouse (Turek et al., 2005) strongly supports a regulatory role for clock genes in the production of adipocytokines (Ando et al., 2005). It is therefore clear that the circadian regulation of adipose tissue has significant metabolic implications. Further characterization of its role in the horse may provide new therapeutic possibilities with respect to the pathogenesis and treatment of diseases such as laminitis and hyperlipidemia.

Circadian Regulation of Performance

The recent demonstration that a large subset of genes undergo circadian regulation in mouse skeletal muscle (McCarthy et al., 2007b) corroborates numerous reports of daily variations in athletic performance parameters such as muscle force, strength, and power in humans (Zhang et al., 2009). A circadian rhythm in human athletic performance was recently clearly demonstrated in professional swimmers (Kline et al., 2007). It is considered likely that circadian variation in muscle transcription may contribute to this rhythm in performance (Zhang et al., 2009), in addition to 24-hour rhythmicity in many other cardio-respiratory factors (Millar-Craig et al., 1978; Giacomoni et al., 1999; Spengler et al., 2000).

Secondary to light stimuli, exercise acts as another important synchronizer of circadian rhythms (Edgar & Dement, 1991; Atkinson et al., 2007), supporting a hypothesis that enhanced performance may occur when times of training and competition coincide (Hill et al., 1989). This theory is especially important for equine athletes, particularly racehorses that are trained in the early morning hours and are then expected to perform optimally in the late afternoon. It could be postulated that there is an increased risk of musculoskeletal injury on racetracks if strenuous activity occurs at times that conflict with entrained rhythms. This is supported by evidence that some equine diurnal rhythms, such as those of platelet aggregation, shift in response to an exercise regime (Piccione et al., 2008b) (Figure 18.5). The nadir of the platelet aggregation rhythm was shown to shift to the time of day closest to the time of training, potentially functioning to reduce clotting capacity at a time associated with microvascular bleeding.

Figure 18.5 Daily rhythms of platelet aggregation (%) in horses. Platelet aggregation was measured every 4 hour for 48 hours in groups of A) sedentary horses, B1) athletic horses following a 60-day training program, and B2) the same athletic horses following two weeks of inactivity. Each point represents the mean (±SEM) (n = 6) of parameters. Grey bars indicate the dark phase of the 48-hour LD cycle. Adapted from Piccione et al. (2008a), with permission from Elsevier.

In order to provide a foundation for future studies investigating circadian regulation of performance in the equine athlete, an initial set of experiments investigating circadian gene expression profiles in equine skeletal muscle and their relationship to activity patterns in the horse were conducted (Martin et al., 2010). Up until this point there had been some confusion in the literature with regard to the diurnal (day-active) or ultradian (multiple activity bouts <24 hours throughout day and night) nature of horse activity rhythms. Studies from housed animals demonstrated diurnal patterns (Piccione et al., 2005), whereas observations of feral herds reported a predominantly ultradian behavioral pattern (Berger, 1999). Six healthy, untrained, sedentary mares were studied to determine whether locomotor activity behavior and skeletal muscle gene expression reflect endogenous circadian regulation. Activity was recorded for three consecutive 48-hour periods using halter-mounted Actiwatch-L® data-loggers, as a group at pasture (P), individually stabled under a light-dark (LD) cycle, and in constant darkness (DD). Animals had ad libitum access to hay and water while housed indoors. Figure 18.6 shows representative actograms displaying temporal patterns of activity (counts/min, Actiwatch L) and light exposure for two representative mares from the study. Visual inspection of the raw activity data supports the subjective summary that in P, the temporal variation in activity was predominantly ultradian, with multiple bouts of elevated activity distributed rather equally over day and night; by contrast, in LD and DD, there is a substantial decrease in overall activity levels along with the emergence of diurnality, exemplified by increased activity during daytime hours. Quantitative time series analysis of circadian cosinor parameters corroborated the predominantly ultradian (8.9 ± 0.7 bouts/24 hours) and weakly circadian pattern of activity in all three conditions (P, LD, DD). A more robust circadian pattern was observed during LD and DD (Figure 18.7). The cosinor method calculated estimates of four rhythm parameters: acrophase (time of peak value of the fitted cosine function), mesor (middle value of the fitted cosine curve representing the rhythm adjusted mean), amplitude (difference between maximum and mesor of the fitted cosine function), and Q value (goodness of fit, i.e., how well the rhythm reflected a circadian waveform).

Figure 18.6 Actograms representing recorded activity from two representative mares. Black vertical lines represent activity (counts/min) and superimposed curves indicate light intensity. Days 1–7 (y-axis label) represent successive 24-hour periods (noon to noon). Mares were at pasture (P) on Days 1–3 and moved into the barn on the morning of Day 3 (0700), where they remained on an artificial light-dark (LD) cycle (14 hours – 10 hours) until lights out on Day 5. Thereafter (Days 6–7), they remained in continuous darkness (DD). White and grey bars above each actograph represent light and dark periods, respectively, of the environmental LD cycle present naturally at P and artificially in Barn LD conditions. Note the prominence of ultradian activity bouts (multiple peaks per 24 hours) when horses are outdoors and the subsequent emergence of a 24-hour rhythm when mares are stabled both in LD and DD. From Martin et al. (2010), with permission from the American Physiological Society.

Figure 18.7 Cosinor analysis of activity data for circadian rhythmicity. Panels A–D plot bar graphs illustrating differences in cosine analysis parameters (mean±SE). The cosinor method gave estimates of four rhythm parameters: acrophase (time of peak value of the fitted cosine function), mesor (middle value of the fitted cosine curve representing the rhythm adjusted mean), amplitude (difference between maximum, and mesor of the fitted cosine function), and Q value (goodness of fit – a value that relates to the degree of robustness of the circadian rhythm). Activity data was compared for horses observed sequentially in three contrasting environments: at Pasture (P), and while stabled in light-controlled barn, first in a light cycle (LD) and second in continuous darkness (DD). Shared letters (a, b, c) indicate group means that differ from each other (P < 0.05). From Martin et al. (2010), with permission from the American Physiological Society.

Muscle biopsies were then obtained from the horses’ middle gluteal muscle every 4 hours for 24 hours under DD. Quantitative RT-PCR results from isolated total RNA confirmed the circadian expression (P < 0.05) of five core clock genes (Arntl, Per1, Per2, Nr1d1, Nr1d2), the clock-controlled gene Dbp, and the muscle-specific transcript Myf6 (Figure 18.8). Additional genes, Ucp3, MyoD1, and Vegfa, while not significant, did clearly display circadian-like waveform expression profiles (Figure 18.8). Myf6 is a member of the myogenic regulatory transcription factor (MRF) family, along with Myf5 (myogenic factor 5), Myod1 (myogenic differentiation 1) and myogenin (Megeney & Rudnicki, 1995). The identification of Myf6 as a circadianly regulated transcript suggests that this MRF plays a role in the normal daily functioning of equine skeletal muscle. Myf6 is the most abundantly expressed gene of the MRF family in adult muscle, and is therefore purported to play a role in the maintenance of skeletal muscle phenotype (Wyszynska-Koko et al., 2006). Recent studies have identified Myf6 in newly developed myotubes of regenerating muscle in the amphibian Xenopus (Becker et al., 2003) and the rat (Zhou & Bornemann, 2001). These observations are consistent with numerous reports of the role of this gene in myogenesis (Montarras et al., 1991). Furthermore, elevated levels of Myf6 mRNA have been detected in human skeletal muscle following heavy-resistance training, indicating that this gene may also play a role in skeletal muscle hypertrophy (Psilander et al., 2003). Lowe et al. (1998) reported elevated levels of Myf6 mRNA in stretch-overloaded muscles of adult quails (Lowe et al., 1998), further supporting this theory. In untrained, sedentary horses, Myf6 mRNA peaked between 0300 and 0700 (local time), exactly opposite the timing of the circadian peak in the observed activity rhythm (see Figure 18.7). This supports the known function of Myf6 in muscle regeneration and repair during the rest phase of the activity cycle (Goetsch et al., 2003).

Figure 18.8 Twenty-four-hour profiles of skeletal muscle gene expression. Plotted are mRNA levels of candidate genes relative to the internal control gene Ttn, in equine skeletal muscle over 24 hours in constant darkness. Top: Genes that displayed a significant variation over time: Per1, Per2, Arntl, Nr1d1, Nr1d2, Dbp, and Myf6 (P < 0.05). Bottom: Non-significant core clock genes: Cry1, Cry2, Clock, and Rora (P > 0.05); and potential clock-controlled genes; Nrip1, Myod1, Ucp3, and Vegfa (P > 0.05). Each time point represents the mean±SE (n = 6). The barn light cycle in effect prior to entry into constant darkness (DD) is depicted above each graph with the dark grey shading representing subjective night (∼CT14-CT24) and light grey shading representing subjective day (∼CT0-CT14), corresponding to times of natural or simulated night and day existing prior to DD. From Martin et al. (2010), with permission from the American Physiological Society.

Ucp3 is purported to play a role in the protection of muscle from reactive oxygen species (ROS) damage during oxidative stress (MacLellan et al., 2005). ROS are normal by-products of mitochondrial respiration (MacLellan et al., 2005) that rise during physical exercise and may result in oxidative stress – a state in which ROS production exceeds the body’s antioxidant defence mechanisms and subsequently induces lipid, protein, and DNA damage (Kinnunen et al., 2005). Exercise-induced oxidative stress is associated with muscle damage and decreased muscle performance (Kinnunen et al., 2005), an important consideration for horse trainers, as musculoskeletal injury is the most common reason for wastage in racehorses (Rose et al., 1983). Jiang et al. (2009) reported that Ucp3 expression increased dramatically in response to intense exercise in rat skeletal muscle and coincided with a reduction in ROS levels (Jiang et al., 2009). These findings led the authors to suggest that Ucp3 may promote uncoupling respiration during prolonged exercise and thus reduce ROS generation. This implies that Ucp3 upregulation could act as an antioxidant defense mechanism to protect skeletal muscle mitochondria from exercise-induced oxidative insults (Jiang et al., 2009). It will be interesting to determine via future studies when this gene peaks in skeletal muscle from trained horses.

Vegfa regulates angiogenesis (Ferrara, 1999a) and has been proposed to play an important role in the maintenance of adult skeletal muscle microvasculature (Olfert et al., 2009). Vegfa stimulates vascular endothelial cell growth, survival, and proliferation and in addition promotes vascular permeability (Ferrara, 1999b). Exercise-induced increases in Vegfa expression are thus associated with the formation of new capillaries within skeletal muscle (Amaral et al., 2001). Expanded capillary network formation in response to aerobic exercise training serves to promote O2 transport between the microcirculation and mitochondria by increasing the surface area available for diffusion of O2 and decreasing the diffusional distance of O2 to the mitochondria (Kraus et al., 2004). As a result, increases in the level of this growth factor likely contribute to improvements in skeletal muscle oxidative capacity and performance. Furthering our knowledge of when the potential for angiogenesis is highest in equine athletes will have important implications for trainers.

While Myod1 did not display significant circadian regulation, this gene clearly demonstrated a 24-hour waveform (Figure 18.8). A central player in skeletal myogenesis (Weintraub, 1993), Myod1 specifies skeletal muscle lineage in mice (Rudnicki et al., 1993; Tapscott, 2005) and is required for proliferation of muscle satellite cells (Yoshida et al., 1998). Furthermore, it was proposed that Myod1 may function in regulating skeletal muscle hypertrophy and/or fiber-type transitions, due to up-regulation of this gene following heavy-resistance training (Psilander et al., 2003). It was also suggested that Myod1 acts as an important clock-controlled gene and thus is regulated directly by the skeletal muscle molecular clock rather than by neural or humoral circadian signals from the SCN (McCarthy et al., 2007a; Zhang et al., 2009). The same authors also propose that the cellular clock contributes to the maintenance of muscle structure via its direct effects on Myod1 and consequent effects on Myod1-regulated genes. Our findings further highlight the importance of elucidating the role of this gene in daily regulation and maintenance of muscle tissue, especially in routinely exercised performance horses.

These findings demonstrate the diurnal nature of horse activity rhythms, evidenced by the presence of a circadian molecular clock in the skeletal muscle that regulates muscle function. Because of the greater circadianicity of activity rhythms under DD, it is clear that human management regimes may strengthen, or unmask, equine circadian behavioral outputs (Martin et al., 2010). As exercise acts as a known synchronizer of circadian rhythms, these findings provide a basis for future work determining peak times for training and competing horses, to reduce injury and to achieve optimal performance.

Immune-Circadian Interaction

The immune system functions to protect and defend an organism’s physiological status quo and thus represents an integral component of homeostasis. Homeostasis encompasses the mechanisms that react to maintain a constant, fixed set point of a physiological variable (reactive homeostasis), but also incorporates those mechanisms that are active in advance to maintain a set point that in itself is rhythmic (predictive homeostasis) (Moore-Ede, 1986). Hence, the ability to adaptively anticipate predictable changes in the environment, as conferred by the circadian system, is an important and often overlooked component of homeostasis. Consequently, interaction between these two systems is fundamental to survival.

Extensive evidence exists for circadian regulation of immune parameters exemplified by rhythmic secretion of the neuroendocrine hormone cortisol and the pineal hormone melatonin, both of which exhibit diurnal variation in the horse (Hoffsis et al., 1970; Bottoms et al., 1972; Larsson et al., 1979; Piccione et al., 2005; Murphy et al., 2006). Glucocorticoids act as potent inhibitors of inflammatory mediators (Russo-Marie, 1992), and the ability of cortisol to suppress the pro-inflammatory cytokines, such as interferon (IFN)-γ, interleukin (IL)-12, tumour necrosis factor (TNF)-α, IL-1 and, to a lesser extent, IL-6 and IL-10 production has been described in humans (Petrovsky et al., 1998). The finding that cytokine production is negatively entrained by cortisol explains why the symptoms of immuno-inflammatory disorders, such as rheumatoid arthritis and asthma (Reinberg et al., 1963; Harkness et al., 1982; Bush, 1991; Martin et al., 1991), are exacerbated at the time of the early-morning nadir in plasma concentrations (Petrovsky et al., 1998). For this reason the importance of chronotherapeutics (circadian-time-specified drug administration or treatment) is of increasing importance in human medicine (Smolensky & Peppas, 2007) and should soon become increasingly relevant to veterinary practitioners as further advances are made in large animal chronobiology.

The immunomodulatory action of the pineal hormone melatonin is also well established (Colombo et al., 1992; Morrey et al., 1994; Carrillo-Vico et al., 2005), and numerous studies have described the interaction between photoperiod and the immune system (Nelson, 2004). It has been known for some time that exogenously administered melatonin can improve the outcome of acute and chronic inflammation (Maestroni, 1996). This immunosuppressant effect is elicited partly via the hormone’s ability to inhibit TNFα levels (Wu et al., 2001) and reduce the levels of IL6 (Sullivan et al., 1996) in mouse models of endotoxin-induced inflammation. Studies that investigate this therapeutic application of melatonin during inflammatory conditions (such as septic shock) in larger mammals are warranted.

Furthermore, the cytokine environment in which T lymphocytes are initially activated determines whether an immune response develops in a Type 1 (cellular) or Type 2 (humoral) direction (Petrovsky & Harrison, 1997). As IFN-γ and IL10 are markers of Type 1 and Type 2 immune activation, respectively, and under the opposing regulation of melatonin and cortisol, findings from the Petrovsky and Harrison’s (1997) study strongly suggest that the time of day of antigen presentation will determine the direction of the immune response.

It has been proposed that responses to vaccination may be significantly modulated by time of vaccine administration relevant to the light/dark (LD) cycle, and that therapeutic manipulation using cortisol or melatonin may improve vaccine efficiency (Petrovsky & Harrison, 1997). An initial investigation of diurnal variation in circadian clock and immune mediator response to antigenic challenge in the horse was recently conducted (McGlynn et al., 2010). Blood samples were collected from young healthy animals at 4-hour intervals for 24 hours and immediately incubated for 6 hours in the presence or absence of lipopolysaccharide – a gram negative bacterial endotoxin that elicits strong immune cell activation. Quantitative RT-PCR analysis of total RNA harvested from cells post incubation revealed a significant effect of time on expression of the clock genes Per2, Cry1, Arntl, Nr1d2 (p<.001, p<.05, p<.05, p<.01; respectively) and the immunomodulatory cytokine interleukin (IL)6 (p<.0001) (Figure 18.9). These results confirmed that equine peripheral blood differentially responds to antigenic challenge over the 24-hour cycle, impacting upon our understanding of the pathophysiology of inflammatory responses. IL6 was found to be up-regulated midway through the dark phase of the 24-hour photoperiod in equine circulation, in direct contrast to the temporal pattern observed in mice (Marpegan et al., 2009). This is likely indicative of a contrasting temporal immune surveillance regulation between diurnal and nocturnal species. The results of this preliminary study suggest that equine Th1 humoral responses may be favored when antigen exposure occurs in the evening as the involvement of IL6 in the transition from innate to acquired immunity is known. This has clear implications regarding the potential optimal time of day for vaccination in the horse, emphasizing the importance of further research in this area.

Figure 18.9 Time of day influences cytokine and clock gene response to immune stimulation in equine whole blood. Diurnal variation in gene expression from equine whole blood collected at 4-hour intervals over the 24-hour LD cycle and cultured for 6 hours with (solid line) or without (dotted line) LPS. Data are presented as means±SE (n = 4 per time point). Within time point significant Bonferoni statistical post hoc differences are indicated by superscript lettering; a, b = P < 0.05; c, d = P < .01; e, f = P < .001. From McGlynn et al. (in press), Animal Genetics.

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