Abstract
Background The circadian clock powerfully regulates inflammation and the clock protein REV-ERBα is known to play a key role as a repressor of the inflammatory response. Asthma is an inflammatory disease of the airways with a strong time of day rhythm. Airway hyper-responsiveness (AHR) is a dominant feature of asthma; however, it is not known if this is under clock control.
Objectives To determine if allergy-mediated AHR is gated by the clock protein REV-ERBα.
Methods After exposure to the intra-nasal house dust mite (HDM) allergen challenge model at either dawn or dusk, AHR to methacholine was measured invasively in mice.
Main results Wild-type (WT) mice show markedly different time of day AHR responses (maximal at dusk/start of the active phase), both in vivo and ex vivo, in precision cut lung slices. Time of day effects on AHR were abolished in mice lacking the clock gene Rev-erbα, indicating that such effects on asthma response are likely to be mediated via the circadian clock. We suggest that muscarinic receptors one (Chrm 1) and three (Chrm 3) may play a role in this pathway.
Conclusions We identify a novel circuit regulating a core process in asthma, potentially involving circadian control of muscarinic receptor expression, in a REV-ERBα dependent fashion.
Clinical implication These insights suggest the importance of considering the timing of drug administration in clinic trials and in clinical practice (chronotherapy).
Abstract
REV-ERBα gates airway hyper-responsiveness by time of day. Future asthma therapies should aim to dose anti-muscarinic agents at the most efficacious time of day (chronotherapy) and modulate the molecular clock https://bit.ly/37qY4sC
Introduction
Asthma is a chronic inflammatory disease of the airways and displays a strong relationship to circadian rhythm [1–4]. Asthma-associated mortality is strongly time of day dependent, peaking overnight between midnight and 08:00 [5]. Airway hyper-responsiveness (AHR), a cardinal feature of asthma [6, 7], involves increased sensitivity of the airways to bronchoconstrictor challenge, such as by methacholine. As such, AHR is clinically useful in diagnosing asthma; however, there is a diurnal variation in AHR in asthma, with a peak at around 04:00, the time of maximal disease expression [8–13]. Potential causes for this diurnal change in AHR in asthma remain undefined, but may be important for improved asthma treatment.
Circadian rhythms are generated by a molecular clock that is expressed in virtually all cells. A central clock in the suprachiasmatic nucleus of the brain synchronises peripheral tissue clocks via neural and humoral mediators. The cellular circadian molecular clock consists of a positive arm (CLOCK and BMAL1 heterodimers), driving transcription of two inhibitory arms (PER/CRY and REV-ERBα/REV-ERBβ), which feedback to inhibit BMAL1/CLOCK heterodimer transactivation function [14]. The circadian clock powerfully regulates inflammation [15–17] and REV-ERBα plays a key role as a repressor of the inflammatory response [18].
Here we explore the biology of REV-ERBα and address whether this protein acts as a circadian mediator, gating AHR following allergic challenge. Using the house dust mite (HDM) [19] mouse model for allergic airways disease [20], as well as an in-vitro lung slice model, we investigated the role of airway smooth muscle in the circadian gating of AHR. We found that time of day effects in AHR following allergen challenge were ablated in REV-ERBα-deficient mice, as was rhythmic expression of key muscarinic receptor subclasses, mediating cholinergic smooth-muscle responses. Thus, we have identified a pathway linking the core cellular clock, through REV-ERBα, to airway reactivity, smooth-muscle tone and airway narrowing.
Methods
Animals
All experimental procedures were carried out in accordance with the Animals (Scientific Procedures) Act, 1986. Rev-erbα−/− mice were provided by Ueli Schibler (University of Geneva, Geneva, Switzerland) [21]. Wild-type (WT) C57Bl/6J control mice and Rev-erbα−/− mice were individually housed in 12 h:12 h light:dark cycles. Zeitgeber time zero (ZT0) is when lights are turned on in the animal house and ZT12 is when lights are switched off. Female C57Bl/6J mice aged 8–12 weeks were used in all experiments.
House dust mite asthma protocol
Mice were exposed intranasally to 25 µg of HDM protein (Citeq Biologics, Groningen, The Netherlands; batch no. 15J02) in 25 µL of phosphate-buffered saline (PBS) under anaesthesia 5 days·week–1 for 3 weeks [20]. Control mice received intranasal PBS. One group of mice received HDM/PBS at ZT11 (just before lights off/start of the active phase), while a second group received HDM/PBS at ZT23 (just before lights on/start of the rest phase).
Measurement of airway hyper-responsiveness
Airway resistance was measured 24 h after final HDM exposure, in response to increasing concentrations (3–100 mg·mL−1) of methacholine (Sigma-Aldrich, Gillingham, UK), using a FlexiVent small animal ventilator (SciReq, Montreal, Canada) [22] as previously described [23].
Collection of serum
Blood samples in BD Microtainers (Becton, Dickinson and Company, Franklin Lakes, NJ, USA) were placed on ice for 1 h and then centrifuged (5 min, 7000 rpm) to derive serum.
Bronchoalveolar lavage and lung digest
Bronchoalveolar lavage (BAL) was performed immediately after measurement of AHR [24]. The right inferior and post-caval lobes were taken for lung digest. Lung cells were analysed by flow cytometry [23].
Histology
Following BAL, the left lung was taken for histology. For haemoatoxylin (H) and eosin (E) stained slides a semi-quantitative scoring system graded the size of lung infiltrates [25]. Goblet cells were counted on periodic acid–Schiff (PAS) stained lung sections using an arbitrary scoring system [26].
RNA extraction and real-time quantitative polymerase chain reaction
RNA was extracted from the right middle lobe (ReliaPrep RNA Miniprep System, Promega, Madison, WI, USA, catalogue ref. Z6011) and reverse-transcribed (GoScript Reverse Transcription System, Promega, catalogue ref. A5001) before quantitative PCR analysis (KAPA SYBR FAST qPCR Master Mix (2X) Universal Kit, KAPA Biosystems, Wilmington, MA, USA, catalogue ref. KK4601). Relative gene expression was determined via normalization to Gapdh. Primers used were: Qiagen Adrb1 (QT00258692), Adrb2 (QT00253967), Chrm 1 (QT00282527), Chrm 2 (QT00290297), Chrm 3 and Gapdh (QT01658692). Primer sequences were: Nr1d1 (F GTCTCTCCGTTGGCATGTCT, R CCAAGTTCATGGCGCTCT) and Bmal1 (F CCAAGAAAGTATGGACACAGACAAA, R GCATTCTTGATCCTTCCTTGGT).
Enzyme-linked immunosorbent assay (ELISA)
Serum was analysed for anti-HDM IgE using an IgE mouse ELISA kit (Thermo Fisher Scientific, Waltham, MA, USA, catalogue ref. EMIGHE) or a mouse serum anti-HDM IgE antibody ELISA kit (Chrondrex Inc, Woodinville, WA, USA, catalogue ref. 3037) as per the manufacturer's instructions.
Bioplex
Bronchoalveolar lavage fluid (BALF) was analysed using a Bio-Plex Pro Mouse Chemokine Panel 33-Plex (Bio-Rad, Watford, UK, catalogue ref. 12002231), on a Bio-Plex 200 system (Bio-Rad).
Lung slice model
Precision-cut ectopic lung slices (175 µm) were prepared [24]. Slices placed on cell culture inserts (Millicell) were imaged using a long-term time lapse microscope (Eclipse Ti Series Inverted Microscope, Nikon Instruments Europe BV, Amsterdam, The Netherlands). Airways were imaged in response to methacholine (0–100 µM). Airway size was quantified using ImageJ software (version 1.41o). Airway contraction was measured as a percentage decrease from baseline.
Statistical analysis
Linear mixed effects modelling was used to determine how AHR changes with increasing dose of nebulised methacholine. Other data was analysed by one-way ANOVA, followed by Tukey's multiple comparison test and was represented as median±interquartile range (IQR). IgE data and change in AHR after 75 mg·mL−1 of methacholine were analysed by Mann–Whitney U-tests. Serum IgE, AHR and PCR data is represented as mean±standard error of the mean (sem). For the precision-cut lung slice model, methacholine dose–response curves were fitted to a three-parameter sigmoidal dose–response curve. An extra sum-of-squares F-test was used to test whether one curve could adequately fit the data for ZT11 and ZT23.
Results
Airway hyper-responsiveness varies by time of day that house dust mite allergen challenge occurs
The time of day at which WT mice are challenged with HDM significantly impacts the resultant AHR (figure 1a). WT mice were challenged with HDM at either ZT11 (just before lights off and at the start of the active phase for mice) or at ZT23 (just before lights on and at the start of the rest phase in mice). WT mice challenged with HDM at ZT11, in which maximal airway resistance was recorded 24 h later at ZT11, showed a significant increase in the slope of the methacholine dose–response curve compared to mice challenged at ZT23 (figure 1a) (p=0.005). This indicates a significant time of challenge effect and suggests increased sensitivity of the airways to the effects of methacholine after HDM challenge at ZT11 compared to ZT23. This was also the case when airway resistance was measured as area under the curve (supplementary figure S1a) (p=0.005).
WT mice challenged with HDM exhibited increased airway resistance after 75 mg·mL−1 of methacholine at both ZT11 and ZT23 compared to control mice treated with PBS (p=0.007 for ZT11 and p=0.055 for ZT23). Maximal airway resistance was significantly higher after 75 mg·mL−1 of methacholine in WT mice challenged with HDM at ZT11 compared to challenge at ZT23 (figure 1a) (p=0.05). This was also the case for mean resistance (Rrs) (figure 1b) (p=0.03). There were no differences in lung compliance between groups (figure 1c).
Airway and lung inflammation reveal no time of challenge differences
Next, we examined BAL to determine whether time of day differences in AHR were associated with airway inflammatory changes. There was a significant increase in total cells from BAL for mice treated with HDM at ZT11, as compared to controls, but not at ZT23. There was no difference by time of challenge (table 1). BAL eosinophils significantly increased following HDM challenge at both ZT11 and at ZT23, compared to controls. No time of challenge differences were seen for differential BAL cell types. BAL macrophages were significantly reduced at ZT23 after HDM challenge. HDM-specific IgE significantly increased after HDM challenge in WT mice; however, there was no time of challenge difference, indicating similar sensitisation and acquisition of adaptive immunity (supplementary figure S1b).
Next we analysed inflammatory cells present in lung digests. There was an increase in total immune cell content after HDM challenge, but this only reached significance at ZT23 and there was no time of HDM challenge difference (figure 2a). There was also a significant increase in lung eosinophils after HDM challenge, but again no time of challenge difference (figure 2b).
Histology revealed a significant increase in eosinophil infiltration around the bronchioles and blood vessels within the lung following HDM challenge, as compared to control mice. However, there was no time of challenge difference (figure 2c). There was increased mucus in PAS stained lung sections after HDM challenge compared to controls, but no time of challenge difference in PAS scores (figure 2d).
REV-ERBα is a negative repressor of airway hyper-responsiveness
The functions of two components of the molecular clock within the lungs of WT mice were investigated. We focussed on BMAL1, the only non-redundant clock component and the major element of the positive arm of the clock. BMAL1 has been implicated in the circadian control of inflammation [27–30]. We also studied REV-ERBα, a component of the negative arm of the clock and a known regulator of inflammation [16, 18], itself repressed by inflammation. Bmal1 expression is in antiphase to Rev-erbα expression in PBS-treated mice (figures 3a and 3b). There was a significant time of day difference in Rev-erbα expression at baseline, with high levels of Rev-erbα expression at ZT11, close to the predicted circadian peak of expression and low levels of expression at ZT23 (figure 3a). After HDM challenge there is reduced expression of both Rev-erbα and Bmal1, with a loss of time of day of expression within the lung (figures 3a and 3b).
The change in Rev-erbα expression seen after HDM challenge, taken with the previous work showing a role for REV-ERBα in lung inflammation, prompted us to investigate HDM responses in Rev-erbα−/− mice. There is an increase in AHR to 75 mg·mL−1 of methacholine after HDM challenge in Rev-erbα−/− mice, as compared to controls (p<0.03 at ZT23 and p=0.09 at ZT11), but no time of challenge effect (in contrast to WT mice) (figure 3c and supplementary figure S2a). There was no difference in the slope of the methacholine dose–response curves between Rev-erbα−/− mice challenged with HDM at either ZT11 or ZT23, in contrast to WT mice. We also noted higher baseline AHR at ZT23 compared to ZT11 in PBS-treated Rev-erbα −/− mice (figure 3c) and, although this was not significant, this trend was in anti-phase to the effect seen in WT mice (figure 1).
Furthermore, there was an increase in maximal effect of methacholine in Rev-erbα−/− mice compared to WT mice for both PBS-challenged mice (supplementary figure S2b) and HDM-challenged mice (figure 3d). This suggests that loss of REV-ERBα causes exaggerated and clock-time independent AHR in response to methacholine challenge.
Airway and lung inflammation reveal no time of challenge differences in Rev-erbα−/− mice
There was a significant increase in the total number of cells in BAL and in the percentage of eosinophils following HDM challenge in Rev-erbα−/− mice, but with no time of challenge effect in either case, as previously seen in WT mice (figures 3e and 3f). There was a significant increase in total cells in the lung digest following HDM challenge in Rev-erbα−/− mice at ZT23, as compared to control mice, but no time of challenge difference (figure 4a). Lung eosinophils also increased after HDM challenge (only reaching significance at ZT11) and there was no time of challenge difference (figure 4b).
Histological analysis showed increased H and E staining around the bronchioles and blood vessels, and within the interstitial spaces (as well as increased PAS staining), at both challenge times after HDM challenge, with no time of day effect in the Rev-erbα−/− mice (figures 4c and 4d). Following HDM challenge in Rev-erbα−/− mice, HDM-specific IgE was increased but no time of day difference was seen (supplementary figure S2c).
Genotype comparison of wild-type versus Rev-erbα−/− mice
Individual cell counts in BAL, measured as a percentage of the total cell count, revealed no significant genotype differences (supplementary figure S3a). In addition, cytokine and chemokine analysis revealed no time of challenge differences (data not shown) and only CXCL13 showed a genotype difference (table 2).
REV-ERBα action is through airway smooth muscle muscarinic receptor regulation
Since we did not find a convincing correlation between inflammatory parameters and AHR in our models, we next investigated bronchiolar smooth muscle function. Using precision cut lung sections in organotypic culture we quantified airway contraction in response to methacholine.
We found a significant increase in the maximal effect to methacholine at ZT11 compared to ZT23 (p=0.03) and a reduction in the EC50 value for methacholine in HDM-challenged lung slices at ZT11 (3.2 µM) compared to ZT23 (6.2 µM) (figures 5a and 5b). We repeated these experiments in lung slices from HDM-challenged Rev-erbα−/− mice and found no time of day differences to methacholine challenge, as well as similar EC50 values (ZT11: EC50 9.3 µM and ZT23: EC50 8.5 µM) (figure 5c). There were no changes by time of day in PBS-treated lung slices.
We then investigated muscarinic receptor expression in the lungs. After saline challenge, we found Chrm 1 was more highly expressed at ZT11 rather than at ZT23, perhaps accounting for the physiological differences in AHR at baseline by time of day in WT mice (figure 5d). We also found Chrm 3 expression was higher after HDM challenge at ZT11, but not at ZT23, potentially explaining the time of challenge difference in AHR. These time of day effects were lost in Rev-erbα−/− mice (figure 5f). Chrm 2 expression showed no time of day or genotype differences after PBS or HDM challenge (figure 5e).
We also measured the expression of the muscle contractile apparatus genes smooth muscle actin (Acta), myosin light chain kinase (mylk1) and smooth muscle myosin (sm-mhc). None of these demonstrated a time of day response (supplementary figures S4a–S4c). Similarly, the beta adrenoceptors Adrb1 and Adrb2, although reduced in response to HDM challenge, importantly also showed no time of day effects (supplementary figures S4d and S4e).
Discussion
We show that AHR is determined by time of day, an effect regulated through REV-ERBα. Allergen challenge at ZT11 (just before lights off/beginning of the active phase in mice and equivalent to early morning in humans) significantly increases the magnitude of AHR compared to allergen challenge at ZT23 (just before lights on/beginning of the rest phase in mice and equivalent to late afternoon/early evening in humans). This effect is abolished in Rev-erbα−/− mice, suggesting that AHR is regulated, or gated, by REV-ERBα. Despite the marked changes in AHR, only modest changes in inflammatory mediators and cells were seen in the lungs, suggesting dissociation between inflammatory response and airway constriction. Even ex-vivo the airways retain a time of day signature in response to methacholine, an effect which was lost in Rev-erbα−/− mice and which prompted our analysis of the muscarinic receptor types. This revealed both time of day and also REV-ERBα dependent changes in expression, especially of the M3 receptor in whole lung.
Nocturnal exacerbations of asthma, hospital admissions and deaths remain an unmet medical need. The immune system lies under strong circadian control [23, 24] and lung inflammatory responses are strongly regulated by the circadian clock, specifically by REV-ERBα [16, 18]. Since human asthma symptoms peak in the early morning, at around 6am, we focussed on this time point (ZT11) and its anti-phasic time point ZT23 in our mouse studies. These time points have also been shown to be important for lung innate immune response and in food allergy [31, 32], as well as in our own work on human asthma [1]. Using direct FlexiVent measurement of AHR and a physiologically relevant allergen, HDM, we found higher AHR at ZT11. In nocturnal mice, this time-point is equivalent to the transition from the rest phase to activity and is biologically comparable to early morning in humans.
The allergic inflammatory process recruits many specialised cells to the lung, resulting in a changed immune environment. We characterised the immune cell repertoire, both in BAL and in lung digests, and also measured inflammatory and immune mediators. Overall, the effects of time of day were dissociated from the consistent and marked changes in AHR, suggesting possible non-immune cell involvement. We acknowledge that there could have been time of day differences at other time points. Our sampling was undertaken at 24 h after the final allergen challenge, when AHR was predicted to be greatest [20].
The orphan nuclear receptor REV-ERBα has recently emerged as a major regulator of the lung immune response, mediating time of day changes to acute inflammatory challenges [16, 18]. Moreover, REV-ERBα plays important roles in non-immune cells, regulating energy metabolism and in muscle function [33, 34]. For these reasons we repeated the HDM challenges in Rev-erbα−/− mice and showed that the time of day AHR effect was abolished. Interestingly, we also found that HDM challenge in WT mice had a major inhibitory effect on Rev-erbα expression, identifying inflammation acting through both transcriptional and post-translational mechanisms to repress Rev-erbα expression [18]. Again, we saw no differences in immune cells infiltrating into the lungs between WT and Rev-erbα−/− mice, despite the loss of temporal control of AHR. This again suggests a non-immune cell and non-inflammatory effector mechanism.
To examine airway response directly, we removed the lungs of HDM-sensitised animals, prepared precision cut lung slices for organotypic culture and measured airway responses to methacholine. Here, we saw an increase in the maximal effect to methacholine at ZT11, indicating greater methacholine sensitivity. Furthermore, when we repeated these experiments in Rev-erbα−/− mice, the time of day difference was abolished. This correlates with the in-vivo measurements and indicates a lung-intrinsic mechanism of action. Methacholine acts on muscarinic receptors, with little effect on nicotinic receptors [35]. Therefore, we examined the expression of muscarinic receptors and identified major changes in both Type M1 and Type M3 muscarinic receptors. Importantly, we found no changes in the expression of genes involved in the contractile apparatus of airway muscle, or in adrenoceptors, suggesting that the changes in muscarinic receptors in the lung by time of day were specific. The increase in M1 receptor expression at ZT11 in the PBS-treated group suggests that this receptor is important for conferring time of day constrictor tone to the airway under basal conditions. Furthermore, Chrm1 contains transcription factor binding sites for the clock proteins BMAL:CLOCK and RORβ [36]; suggesting that muscarinic receptor one (Chrm 1) is under direct clock control. In contrast muscarinic receptor three (Chrm 3) only acquires a time of day effect after HDM-inflammation, with peak expression at ZT11. Strikingly, this time of day change in Chrm 3 expression is completely lost in the Rev-erba−/− mouse, providing an attractive explanation for the loss of temporal gating in AHR that we observed. However, according to the Circadian Database [37] of rhythmic gene expression, the expression of Chrm 3 oscillates in healthy mouse lung with maximal expression at 6 pm (ZT11) and nadir of expression at 6 am (ZT23). In our study, we identified similar time of day differences in Chrm 3 expression; however, in our case, these differences were only apparent following stimulation with HDM and were not observed under baseline conditions. One potential explanation may be that our assay was insufficiently sensitive for the detection of low level changes in gene transcription under unstimulated conditions. Bioinformatic analysis revealed no evidence of clock transcription factor binding sites in Chrm 3 [36] and we therefore postulate that Chrm 3 transcription may be under indirect clock control.
We acknowledge that the M3 receptor is not only expressed by airway smooth muscle cells but by multiple other cell types [38], including endothelial cells and inflammatory cells. However, given the immediate and directly visualised contraction of the airway to methacholine during the lung slice experiments, the likely mechanism of action of methacholine is through the muscarinic receptors present in the airway smooth muscle. Although we have focussed on time of day changes in muscarinic receptors, it should be noted that the parasympathetic nervous system as a whole displays marked circadian rhythmicity [39]. It is therefore likely that in vivo the diurnal variation in AHR would be affected by both neural and humoral circadian rhythms, as well as by rhythmic changes in receptor expression.
To our knowledge this is the first time that the molecular clock has been shown to be important in gating AHR. Furthermore, the discovery that muscarinic receptors might play a role is important for the treatment of asthma [40]. The cholinergic system is functionally linked to the circadian system [39]. Tiotropium bromide, a long-lasting M3 muscarinic-receptor antagonist, is licensed for asthma [41]. In the future, a short-acting drug antagonising both M1 and M3 might prevent AHR in asthma and its administration at the peak of receptor expression could significantly increase its efficacy, leading to novel chronotherapeutic approaches.
Supplementary material
Supplementary Material
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Supplementary figure S1. Time of HDM challenge effects AHR to methacholine, measured as airway resistance (area under the curve, AUC, rather than maximum resistance as in figure 2) in wild type (WT) mice. a) Airway resistance to increasing doses of methacholine was measured by area under the curve, AUC, in mice challenged with either HDM or PBS at ZT11 or ZT23. There was a significant time of day difference in airway resistance in mice challenged with HDM (p=0.005), mixed linear modelling (n=8-9, per treatment group). Mice challenged with HDM at ZT11 showed increased airway resistance compared to those challenged at ZT23. b) HDM specific IgE was measured in serum from WT mice. There were significantly increased levels of HDM specific IgE in WT mice treated with intranasal HDM compared to PBS treated control mice (* p<0.05 at ZT23 and *** p<0.001 at ZT11). There were no time of challenge differences in control or HDM treated groups (mean±SEM, (n=5-8, per treatment group) Mann Whitney U). ERJ-02407-2019.Figure_S1
Supplementary figure S2. REV-ERBα acts as a repressor of AHR. a) Effect of time of HDM challenge on AHR in Rev-erbα-/- mice. Airway resistance measured as area under the curve, AUC, rather than as maximum airway resistance as in figure 4. There was a significant increase in airway resistance (AUC) after HDM challenge at ZT11 (*** p<0.001) and ZT23 (*** p<0.001), compared to control, PBS challenged mice. There was no time of challenge difference in airway resistance (AUC) after PBS challenge or after HDM challenge, mixed linear modelling, (n=7-9 per treatment group). b) Maximum airway resistance (cmH20·s/mL) was measured in PBS challenged WT and Rev-erbα-/- mice to increasing doses of nebulised methacholine. All measurements of maximum airway resistance were increased in the Rev-erbα-/- mice compared to WT mice. c) HDM specific IgE was measured in serum from Rev-erbα-/- mice. HDM specific serum IgE was significantly increased following HDM challenge, compared to control mice (** p<0.01 at ZT23 and ** p<0.01 at ZT11). There were no time of challenge differences in control or HDM treated groups (mean±SEM (n=4-7 per treatment group), Mann Whitney U). ERJ-02407-2019.Figure_S2
Supplementary figure S3. Genotype differences in airway and lung inflammatory cells. a) BAL inflammatory cell counts measured as a percentage of the total cell count, were analysed in WT and Rev-erbα-/- mice to determine genotype differences. There were no significant differences between the groups. Mean±SEM (n=8-12 per treatment group), one-way ANOVA, followed by Tukey multiple comparison test. ERJ-02407-2019.Figure_S3
Supplementary figure S4. Expression of beta adrenoceptors in murine lung. a) Quantitative PCR for myosin light chain kinase 1 (mlck1) in mouse lung. There were no time of day or genotype differences in expression between groups. b) Quantitative PCR for smooth muscle myosin (sm-mhc) in mouse lung. There were no time of day or genotype differences in expression between groups. c) Quantitative PCR for smooth muscle actin (acta) in mouse lung. There were no time of day or genotype differences in expression between groups. d) Quantitative PCR for Adrenoceptor Beta 1 (Adrb1) in mouse lung tissue. There were no time of day or genotype differences in expression of Adrb1. e) Quantitative PCR for Adrenocpetor Beta 2 (Adrb2) in mouse lung tissue. There was no time of day or genotype differences in expression of Adrb2. All data presented as mean±SEM (n=5-9 per treatment group, in duplicate) and analysed by one-way ANOVA, followed by Tukey’s multiple comparison test. All QPCR data is compared to expression of the housekeeping gene Gapdh in WT PBS challenged mice at ZT23. Black bars indicate challenge at ZT11 and grey bars indicate challenge at ZT23. ERJ-02407-2019.Figure_S4
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Author contributions: H.J. Durrington conceived of the study, secured the funding, ran the study, analysed the results and prepared the manuscript. K. Krakowiak performed Bioplex, PCR, histology, cell counts and lung slice experiments. P. Meijer performed lung slice experiments. N. Begley and L. Goosey performed FlexiVent measurements and collected samples. L.G. Gregory and C.M. Lloyd advised on the house dust mite model and FlexiVent measurements, and helped to prepare the manuscript. R. Maidstone ran statistical analysis and advised on the statistics used and prepared the manuscript. A.S.I. Loudon, J.E. Gibbs and J.F. Blaikley prepared the manuscript. J.F. Blaikley also advised on lung slice experiments. D.W. Ray conceived the study, analysed the results and prepared the manuscript.
Conflict of interest: K. Krakowiak has nothing to disclose.
Conflict of interest: P. Meijer has nothing to disclose.
Conflict of interest: N. Begley has nothing to disclose.
Conflict of interest: R. Maidstone has nothing to disclose.
Conflict of interest: L. Goosey has nothing to disclose.
Conflict of interest: J.E. Gibbs has nothing to disclose.
Conflict of interest: J.F. Blaikley has nothing to disclose.
Conflict of interest: L.G. Gregory has nothing to disclose.
Conflict of interest: C.M. Lloyd has nothing to disclose.
Conflict of interest: A.S.I. Loudon has nothing to disclose.
Conflict of interest: D.W. Ray has nothing to disclose.
Conflict of interest: H.J. Durrington has nothing to disclose.
Support statement: H.J. Durrington is supported by an Asthma UK Senior Clinical Academic Development Award (AUK-SCAD-2013–229), the JP Moulton Charitable Foundation, a North West Lung Centre charity project grant (R 121399) and the University of Manchester's Dean's Prize for Clinicians. K. Krakowiak is supported by the JP Moulton Charitable Foundation. P. Meijer is supported by Medical Research Council Doctoral Training Partnership funding (AA07 P117413). R. Maidstone is funded by a Wellcome Trust grant (107849/Z/15/Z) and a Medical Research Council grant (MR/P023576/1). J.E. Gibbs is a Career Development Fellow versus Arthritis (20629) and holds a Medical Research Council grant (MR/S002715/1). C.M. Lloyd is a Wellcome Senior Fellow in Basic Biomedical Sciences (107059/Z/15/Z). A.S.I. Loudon is a Wellcome Investigator (Wellcome Trust 107849/Z/15/Z). D.W. Ray is a Wellcome Investigator (Wellcome Trust 107849/Z/15/Z) and holds a Medical Research Council grant (MR/P023576/1). J.F. Blaikley is funded by a Medical Research Council grant (MR/L006499/1). Funding information for this article has been deposited with the Crossref Funder Registry.
- Received December 16, 2019.
- Accepted June 6, 2020.
- Copyright ©ERS 2020