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Original Research

Exercise, But Not Acute Sleep Loss, Increases Salivary Antimicrobial Protein Secretion

Gillum, Trevor L.1; Kuennen, Matthew R.2; Castillo, Micaela N.1; Williams, Nicole L.1; Jordan-Patterson, Alex T.1

Author Information
Journal of Strength and Conditioning Research: May 2015 - Volume 29 - Issue 5 - p 1359-1366
doi: 10.1519/JSC.0000000000000828
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Military personnel, shift workers, and athletes traveling across time zones are often required to perform arduous physical activity with limited sleep. Exercise is known to affect immune parameters in the form of a “J”-shaped curve (32). Moderate-intensity exercise can enhance immune function, whereas heavy exercise may suppress immunity and subsequently increase the risk of upper respiratory infections in athletes (22,23,30). For example, acute running at 75% of

has been shown to increase a number of salivary antimicrobial proteins (AMPs), including IgA (21), lactoferrin (Lac) (1,21), and lysozyme (Lys) (1,21) suggesting a potential enhancement of protection against pathogens, a downregulation of inflammation, or both (40). However, prolonged exercise has been shown to decrease salivary IgA (20,33) and Lys (11).

The quantity of sleep can also alter immune function. Complete sleep loss of 1 night, or even partial sleep loss over the course of 1 night, decreased natural killer (NK) cell number (14,28,29), activity (29), and mobility (41). One night of sleep loss has also been shown to decrease CD4+, CD16+, and CD57+ lymphocytes (14). Taken together, these studies suggest that just 1 night of missed or interrupted sleep may contribute to increased host susceptibility to invading pathogens.

Salivary AMPs are recognized as the first line of defense against viruses that can cause the common cold by protecting against invading pathogens at the mucosal surface (24,39,40). Antimicrobial proteins represent 2 lines of protection: immunomodulatory and antimicrobial, and these 2 effects seem to be independent of each other. Antimicrobial proteins are immunomodulatory in that they can suppress or activate inflammation. For example, the addition of Lac before or after an inflammatory agent blocked TNF-α, IL-1β, IL-6, and IL-8 release from monocytes (27). However, the production of AMPs during inflammation augmented the immune response by causing the release of IL-8 and TNF-α from neutrophils and macrophages (36). In addition, LL-37 recruits neutrophils, monocytes, and T cells (13). Thus, AMPs represent a link between innate and adaptive immunity. Finally, AMPs are immunomodulatory by inhibiting interaction between microorganisms and host cells, and this prevents the induction of the immune response. Antimicrobial proteins are antimicrobial by inhibiting growth of microorganisms or creating a hostile environment. In addition, AMPs can directly kill microbes by a variety of mechanisms, including DNA/RNA disruption, disruption of membranes, degradation of ATP, and initiation of autolysins (40).

Thus, although the antimicrobial and immunomodulatory effects of AMPs may be independent, their functions operate synergistically to control chronic inflammation at the mucosal surface. This is important because the mucosal surface is constantly being exposed to antigens, and were it not for AMPs, the mucosal surface would be chronically inflamed. Thus, the limiting of inflammation and the anti-inflammatory properties of AMPs are critical to regulate local inflammation at the mucosal surface. Given the multifaceted importance of AMPs, it is important to note that key AMPs like cathelicidins, α-defensins, Lys, and Lac have not been quantified in response to sleep loss.

Despite the isolated information regarding the impact of sleep or exercise on immune function, little is known about the synergistic effect of exercise after sleep loss and its impact on immunity, particularly regarding mucosal immune parameters. The only study to address this topic demonstrated that 30 hours of sleep deprivation had no impact on postexercise salivary IgA compared with exercise after a night of normal sleep (7). While IgA has been examined, researchers in this field have taken great care to underscore the importance of quantifying other elements of the mucosal immune system that are important to immune protection (23). Since as little as 1 night of disrupted sleep has been shown to alter immune variables, it is important and practically relevant for many occupations and traveling athletes to examine mucosal immunity's response to acute sleep deprivation. Thus, the purpose of this study was to assess the effect of 1 night without sleep on salivary AMPs, including cathelicidin (LL-37), α-defensins (HNP1-3), Lac, and Lys before and after exercise.


Experimental Approach to the Problem

In a counterbalanced order, 8 subjects completed 2 exercise trials consisting of running at 75%

: 1 trial after a night of normal sleep and 1 trial after a night without sleep. Two sleep-wake cycles before each trial were monitored to ensure similar quality and quantity of sleep between conditions. Subjects were instructed to not eat after 11:00 the night before the exercise trial. Saliva was collected 10 minutes before exercise, immediately after exercise, and 1 hour after exercise. Saliva was analyzed for key AMPs, including cathelicidin (LL-37), α-defensins (HNP1-3), Lac, and Lys.


Nine subjects (5 men and 4 women) volunteered to participate in this study (age: 22.8 ± 2.1 years; 66.4 ± 6.3 kg; 18.6 ± 9% body fat;

: 49.1 ± 7.1 ml·kg−1·min−1). No subjects were under 18 years of age. One male participant completed the experimental trial before experiencing an orthopedic injury that was unrelated to the study. Thus, data are analyzed with n = 8. All procedures were approved by the Institutional Review Board at California Baptist University and subjects gave their informed written consent before participation. Subjects were free of cardiovascular, pulmonary, and metabolic disease and were recreationally active according to the American College of Sports Medicine's weekly physical activity recommendations (19).

Preliminary Assessment

Body composition,

, and treadmill workload equivalent to 75%

were determined for each subject. Three-site skinfold (Lange; Beta Technology, Santa Cruz, CA, USA) measurements (men: chest, abdomen, and thigh; women: triceps, suprailiac, and thigh) were used to estimate body density. Sites were measured twice in a rotational order; the mean values for each of the 3 sites were summed and incorporated into a standardized regression equation to estimate body density. Body density was converted to body composition (3). A continuous treadmill test to volitional fatigue was used to determine each subject's

. Women started the test at 6.4 km·h−1 and 1% grade, whereas men began at 8 km·h−1 and 1% grade. The grade remained constant and the speed increased 1.6 km·h−1 every minute.

was assessed through open circuit spirometry (Viasys, San Diego, CA, USA) and defined as the highest 10-second value when 2 of the following conditions were met: (a) a plateau in

(change in

<150 ml·min−1) with increased workload, (b) a maximal respiratory exchange ratio greater than 1.1, and (c) heart rate (HR) greater than 90% of the age-predicted maximum (220-age). A speed that would elicit 75%

was selected from the

testing procedure and used for the experimental trials because this workload is known to increase AMP expression (1,21).


During the 24 hours that preceded testing, subjects were asked to abstain from exercise and alcohol. Subjects arrived at the laboratory at 07:00 after an overnight fast. Subjects were instructed to consume 500 ml of water 1 hour before testing to control for hydration. After voiding their bowel and bladder, nude body weight was assessed. Subjects ran on a treadmill (Trackmaster, Newton, KS, USA) for 45 minutes in a 20° C, 15–20% relative humidity room at a predetermined speed that elicited 75% of

. To ensure appropriate exercise intensity, expired gases were collected every 15 minutes, rating of perceived exertion (RPE) recorded every 10 minutes, and HR was recorded every 5 minutes. Nude body weight was again assessed after the postexercise saliva collection.

All subjects completed 2 exercise trials separated by 10 ± 3 days in a counterbalanced design. The sleep condition consisted of exercise after a normal night of sleep. The without-sleep condition consisted of exercise after a night without sleep. For the without-sleep condition, 5 of the 8 subjects were grouped with another participant to ensure that both subjects stayed awake through the night. Data from 2 sleep-wake cycles before the exercise trial (sleep condition) and 2 sleep-wake cycles before the night without sleep that preceded the exercise trial (without-sleep condition) were manually recorded by each subject. Amount of time in bed (time between bedtime and get up time), sleep onset (period of time between bedtime and sleep start), amount of time slept, sleep efficiency (sleep duration as a percentage of time in bed), and the number of times awakened during the night were calculated (16) (Table 1). Sleep-wake information acquired through manual entry has been shown to be reliable (17,26). In addition, diet and exercise over the previous 48 hours before testing was collected (data not shown). Exercise trials for an individual subject were identical in speed, grade, duration, and time of day to minimize diurnal variation. Subjects were asked to continue their habitual exercise between trials.

Table 1:
Sleep variables for 2 sleep-wake cycles immediately before exercise after a normal night of sleep (CON) and 2 sleep-wake cycles immediately before the night without sleep before exercise (WS).*

Saliva Collection

Subjects were seated during each collection and were instructed to swallow to empty their mouth before unstimulated collection into preweighed tubes. Subjects sat quietly with their head tilted forward during collection. Saliva volumes were estimated by weighing to the nearest mg. Density of saliva was assumed to be 1.00 g·ml−1 (5). Flow rate was calculated as the volume of saliva collected divided by the collection time. Secretion rate was calculated as the product of the flow rate and concentration of salivary protein. Saliva was collected at 3 time points: before exercise, immediately after exercise, and 1 hour after exercise, as done previously (1,21). In accordance with previous work, participants were given 250 ml of water after the postexercise saliva collection to minimize the impact of dehydration on mucosal parameters (1,21). Beyond this, subjects were not permitted to ingest any other food or drink until after their 1 hour postexercise saliva collection was completed.

Saliva Analysis

After collection, saliva was mixed and osmolality was assessed using a freeze point depression osmometer (Advanced Instruments, Norwood, MA, USA). Saliva aliquots were then stored at −80° C for subsequent analysis of salivary AMP, with minimal freeze-thaw cycles. These samples were later thawed and analyzed with ELISA according to manufacturer's instruction. Lac (AssayPro, St. Charles, MO, USA) was detectable at 0.1 ng·ml−1 with an intra-assay coefficient of 4.1% and an interassay coefficient of 7.1%. Lys (AssayPro) was detectable at 0.3 ng·ml−1 with an intra-assay coefficient of 4.3% and an interassay coefficient of 7.3%. LL-37 (Hycult Biotech, Plymouth Meeting, PA, USA) was detectable at 0.14 ng·ml−1 and HNP1-3 (Hycult Biotech) was detectable at 156 pg·ml−1. Intra- and inter-assay coefficients for HNP1-3 were 3.7 and 5.1%, respectively. Intra- and inter-assay coefficients for LL-37 were 4.2 and 11.0%, respectively. Data were generated using Gen5 software (BioTek Instruments, Inc., Winooski, VT, USA). Samples were diluted before analysis: 2000× for Lac, 8000× for Lys, 1000× for HNP1-3, and 5× for LL-37. All samples for individual subjects were analyzed on the same plate.

Statistical Analyses

A dependent t-test was used to confirm that subjects did not differ on hydration status at the onset of their 2 exercise trials. A repeated-measures analysis of variance (ANOVA) was used to determine whether differences in sleep quality and quantity existed between conditions. A 2-way repeated-measures ANOVA (exercise time × trial), was used to determine the effect of exercise on dependent variables. Significant differences were further evaluated using Tukey's post hoc analysis. Statistical significance was set at p ≤ 0.05. All salivary analytes were log transformed to correct for violations of normality. When appropriate, adjustments were made using Greenhouse-Geisser to account for violations against sphericity. Statistica version 8 (Statsoft, Tulsa, OK, USA) was used to analyze the data. Data in text and in tables are mean ± SD. For clarity, data on figures are mean ± SEM. Although we could not find published work regarding exercise after acute sleep loss in mucosal immunity (specifically for LL-37, HNP1-3, Lac and Lys), the estimated sample size was 8 subjects, using an alpha level of 0.05 and a beta level of 0.80, to find differences in mucosal immunity (LL-37 and HNP1-3) after exercise (10).


Sleep, Diet, and Physical Activity

Both groups experienced the same quality and quantity of sleep leading up to each exercise trial. There was no difference in the amount of time in bed (hours), time asleep (hours), sleep onset (minute), sleep efficiency, or in the number of times awakened in the 2 nights that preceded the exercise trial (sleep condition) compared with the 2 nights that proceeded the night without sleep that was followed by the exercise trial (without-sleep condition) (Table 1). In addition, diet and exercise did not differ between groups leading up to the exercise trial.

Exercise Challenge, Dehydration, and Saliva Collection Parameters


, HR, and RPE did not differ between conditions. CON %

was 78.9 ± 2.8 ml·kg−1·min−1, whereas the without-sleep condition was 77.1 ± 1.4 ml·kg−1·min−1. CON HR was 171 ± 14 b·min−1, whereas the without-sleep condition was 170 ± 12 b·min−1. Rating of perceived exertion for CON was 13.3 ± 1.7 compared with 13.5 ± 1.5 for the -leep group. Furthermore, dehydration was impacted to similar extent for subjects across both study conditions according to body weight loss (0.72 ± 0.32% for CON; 0.71 ± 0.23% for without sleep), saliva osmolality, and saliva flow rate (Table 2). Exercise increased saliva osmolality as immediately after exercise was higher than before or 1 hour postvalues (p ≤ 0.05). Saliva flow rate was highest 1 hour after exercise compared with pre- and post-values (p ≤ 0.05) (Table 2).

Table 2

Antimicrobial Proteins

Acute sleep loss did not affect the concentration, secretion rate, or protein concentration:Osm of any AMP. Exercise, however, increased the concentration and secretion rate of each AMP (p ≤ 0.05) (Figures 1–4). Specifically, the concentration of AMPs were higher after exercise compared with before exercise. For Lac, Lys, and HNP1-3 concentration, the +1 hour remained elevated compared with pre-exercise values. Similarly, the secretion rate of AMPs increased after exercise and remained elevated +1 hour postexercise. Lac:Osm and Lys:Osm were higher after exercise compared with before exercise (p ≤ 0.05), whereas HNP1-3:osm and LL37:osm were not affected by exercise.

Figure 1:
Saliva HNP1-3 analysis after 45 minutes of treadmill running at 75%
. Black bars represent exercise after a normal night of sleep, whereas gray bars represent exercise after a night without sleep. Data represented as mean ± SEM. HNP1-3 concentration: *p ≤ 0.05 main effect of time, pre-exercise compared with postexercise and 1 hour postexercise. HNP1-3 secretion rate: *p ≤ 0.05 main effect of time, pre-exercise compared with postexercise and 1 hour postexercise. HNP1-3 μg:mOsm.
Figure 2:
Saliva LL-37 analysis after 45 minutes of treadmill running at 75%
. Black bars represent exercise after a normal night of sleep, whereas gray bars represent exercise after a night without sleep. Data represented as mean ± SEM. LL-37 concentration: *p ≤ 0.05 main effect of time, pre-exercise compared with postexercise. LL-37 secretion rate: *p ≤ 0.05 main effect of time, pre-exercise compared with postexercise and 1 hour postexercise. LL-37 μg:mOsm.
Figure 3:
Saliva Lac analysis after 45 minutes of treadmill running at 75%
. Black bars represent exercise after a normal night of sleep, whereas gray bars represent exercise after a night without sleep. Data represented as mean ± SEM. Lac concentration: *p ≤ 0.05 main effect of time, immediately after exercise compared with before and 1 hour after exercise. Lac secretion rate: *p ≤ 0.05 main effect of time, pre-exercise compared with postexercise and 1 hour postexercise. Lac μg:mOsm: *p ≤ 0.05 main effect of time, pre-exercise compared with postexercise.
Figure 4:
Saliva Lys analysis after 45 minutes of treadmill running at 75%
. Black bars represent exercise after a normal night of sleep, whereas gray bars represent exercise after a night without sleep. Data represented as mean ± SEM. Lys concentration: *p ≤ 0.05 main effect of time, immediately after compared with before exercise and 1 hour after exercise. Lys secretion rate: *p ≤ 0.05 before exercise compared with immediately after exercise. Lys ng:mOsm: *p ≤ 0.05 before exercise compared with immediately after exercise.


The main finding from this study was that acute sleep loss did not affect salivary AMP expression, nor did sleep loss alter the AMP response to running. In addition, salvia flow rate was unaltered between conditions. However, treadmill running for 45 minutes at 75%

increased the concentration and secretion rate of each AMP analyzed. Taken together, these data suggest that short-term sleep loss has a limited effect on salivary AMPs before and after moderate acute exercise.

Although a variety of immune parameter variations have been reported after sleep loss, to the best of our knowledge, this is the first study to analyze the exercise responses to AMPs after sleep loss. Although there was a trend toward increased postexercise LL-37 and cathelicidin expression after sleep loss compared with a normal night of sleep (p = 0.07), the current data suggest that exercise after acute sleep loss does not affect salivary AMPs and consequently not increase the risk of respiratory infections or alter the ability to downregulation of inflammation (40).

Immune indices have been shown to increase, decrease, or stay the same after sleep loss. These disparate findings seem to be due to the amount of time subjects spent without sleep, which varies widely across the limited literature that is available on this topic at the present time. For example, 1 night of sleep deprivation decreased both NK-cell and T helper cell numbers. However, these same subjects continued to be sleep deprived and after 2 nights without sleep, the number of NK cells increased (14). Similarly, 24 hours of sleep loss increased CD8+ and CD4+ T cells, whereas 36 hours of sleep loss decreased these parameters in the same subjects (2). It is plausible that salivary AMPs could be altered with longer periods without sleep, but this has yet to be examined and further research is warranted. In addition, chronic poor sleep quality before exposure to a virus leads to increased infection risk (4).

Most employees of occupations that require exercise on limited sleep, as well as athletes traveling for competition, will undergo recovery sleep before performing additional exercise. In the absence of an exercise stressor, immune indices (NK activity (14,29); monocytes (14)) have been shown to return to normal after 1 night of recovery sleep. However, it was not previously understood if exercise after sleep loss exacerbated the decline of immune function or if immune variables returned to normal. For example, if exercise after acute sleep loss further depresses immune parameters, an environment that is more susceptible to invading pathogens or dysregulation in inflammation at the mucosal surface could be created. Nevertheless, the current data suggest that mucosal immunity is resistant to a night without sleep.

Our data demonstrated an increase in the concentration and secretion rate of each of the 4 AMPs quantified after subjects completed a 45-minute treadmill run at 75% of

. These findings agree with our previous work and that of others, which have shown a postexercise increase in salivary AMPs, including lactoferrin (1,21), lysozyme (1,21), LL-37 (10,38), and HNP1-3 (10). The postexercise increase in concentration and secretion rate of AMPs could arise from the exercise-induced neutrophilia that occurs in mucosal secretions (31) potentially due to airway inflammation or damage to the airway epithelial cells. In addition, neutrophilia of the blood can increase α-defensins in saliva (37). Neutrophils contain Lys and Lac (15), in addition to HNP1-3 (22), whereas LL-37 is stored in neutrophils, monocytes, epithelial cells, NK cells, and lymphocytes (12). Exercise has been shown to activate neutrophils potentially causing the release of their contents into the saliva (35), and this is likely the cause of increased AMPs after exercise.

Saliva flow rate did not change between conditions. This is congruent with previous findings of 24 (8), 30 (7), and 48 (8) hours of sleep deprivation not affecting the salivary flow rate. Saliva flow rate is thought to be regulated by parasympathetic activity (34). Since flow rate was unaffected with sleep deprivation, it seems likely that a night without sleep had a limited effect on autonomic activity. Indeed, previous work has reported sympathetic nervous system activity to be unaltered in response to acute sleep deprivation (14). Additionally, stress hormones are typically not affected by sleep loss in humans. Cortisol has not been shown to be affected by 24, 30, or 48 hours of sleep loss (7,8,25,28). Furthermore, cortisol has not been shown to impact AMP in an exercise model (1). Thus, because of a limited effect of acute sleep loss on sympathetic and parasympathetic activity, saliva flow rate, either before or after exercise was unaffected by acute sleep loss.

A limitation to this study is the small sample size that is mixed with both men and women. This likely contributed to the large variability we reported with salivary AMPs. Men and women have been shown to differently secrete AMPs (21). Although the small sample size is a potential limitation, the same number of participants were used in another study detailing the effect of exercise and sleep loss on mucosal parameters (11 participants were enrolled but only 8 were used for the salivary analyses) (7). In addition, most studies performed in this field use between 8 and 12 participants (1,6,8,9,10). Larger studies outside the field of exercise science have been conducted. In the studies that enrolled larger participants, the coefficient of variation for resting salivary analytes were similar to this study (42) (18). Thus, although 8 participants do not provide a complete picture of the AMP response to exercise after acute sleep loss, it does seem to be in line with previous work.

In conclusion, acute sleep loss did not affect salivary AMP expression, and sleep loss did not alter the AMP response to running. The concentration and secretion rate of each AMP increased after exercise. The current data, along with evidence demonstrating exercise after limited sleep does not affect salivary IgA (7), suggest that the major constituents of the mucosal immune system are unaffected by acute sleep loss and by exercise after acute sleep loss.

Practical Applications

Military personnel, law enforcement, and athletes traveling across time zones are often required to perform physical activity with limited sleep. The results of this study suggest that 1 night without sleep does not compromise important constituents of the mucosal immune system and thus does not increase the risk of illness. Thus, athletes and the various occupations that require acute sleep loss need not be concerned with an increased risk of illness after arduous exercise with acute sleep loss. Because poor chronic sleep increases the risk of infection, it may be wise for coaches and supervisors to monitor sleep patterns of their athletes or employees.


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alpha-defensins; cathelicidin; lactoferrin; lysozyme; sleep deprivation; mucosal immunity; running

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