1. Immunology and Inflammation
  2. Microbiology and Infectious Disease

Loss of circadian protection against influenza infection in adult mice exposed to hyperoxia as neonates

  1. Yasmine Issah
  2. Amruta Naik
  3. Soon Y Tang
  4. Kaitlyn Forrest
  5. Thomas G Brooks
  6. Nicholas Lahens
  7. Katherine N Theken
  8. Mara Mermigos
  9. Amita Sehgal
  10. George S Worthen
  11. Garret A FitzGerald
  12. Shaon Sengupta  Is a corresponding author
  1. The Children’s Hospital of Philadelphia, United States
  2. Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, United States
  3. Systems Pharmacology University of Pennsylvania Perelman School of Medicine, United States
  4. Chronobiology and Sleep Institute, University of Pennsylvania, United States
  5. Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, United States
  6. Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, United States
https://doi.org/10.7554/eLife.61241
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Cite this article
  1. Yasmine Issah
  2. Amruta Naik
  3. Soon Y Tang
  4. Kaitlyn Forrest
  5. Thomas G Brooks
  6. Nicholas Lahens
  7. Katherine N Theken
  8. Mara Mermigos
  9. Amita Sehgal
  10. George S Worthen
  11. Garret A FitzGerald
  12. Shaon Sengupta
(2021)
Loss of circadian protection against influenza infection in adult mice exposed to hyperoxia as neonates
eLife 10:e61241.
https://doi.org/10.7554/eLife.61241
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Abstract

Adverse early-life exposures have a lasting negative impact on health. Neonatal hyperoxia that is a risk factor for bronchopulmonary dysplasia confers susceptibility to influenza A virus (IAV) infection later in life. Given our previous findings that the circadian clock protects against IAV, we asked if the long-term impact of neonatal hyperoxia vis-à-vis IAV infection includes circadian disruption. Here, we show that neonatal hyperoxia abolishes the clock-mediated time of day protection from IAV in mice, independent of viral burden through host tolerance pathways. We discovered that the lung intrinsic clock (and not the central or immune clocks) mediated this dysregulation. Loss of circadian protein, Bmal1, in alveolar type 2 (AT2) cells recapitulates the increased mortality, loss of temporal gating, and other key features of hyperoxia-exposed animals. Our data suggest a novel role for the circadian clock in AT2 cells in mediating long-term effects of early-life exposures to the lungs.

Introduction

Hyperoxia represents the single most important toxic exposure to premature neonatal lungs and is the key risk factor for chronic lung disease of prematurity or bronchopulmonary dysplasia (BPD) (Jobe and Bancalari, 2001; Peek et al., 2017). Despite remarkable improvements in the survival of premature neonates, almost 40% of infants born at <29 weeks of gestation (approximately 10,000 new cases in USA each year) suffer from BPD (Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network et al., 2010; Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network et al., 2015). In surviving adults, BPD is associated with an increased risk of respiratory infections, such as asthma (Gough et al., 2014; Yang et al., 2020) and chronic obstructive pulmonary disease (COPD) (Islam et al., 2015; McGrath-Morrow and Collaco, 2019; Savran and Ulrik, 2018). As an increasing number of prematurely born neonates survive into adulthood, these long-term morbidities have acquired greater public health importance (Jain, 2015). In a murine model, neonatal hyperoxia increased morbidity from influenza A virus (IAV) (O'Reilly et al., 2008) in a dose-dependent manner (Maduekwe et al., 2015) through pathways involving both alveolar type 2 (AT2) epithelial cells and immune pathways (Buczynski et al., 2013). Furthermore, this effect seems independent of the pathogen, since Yee et al. have recently demonstrated that the expression of the SARS-COV2 receptor, ACE2 in club cells, and AT2 cells is increased in adult mice exposed to hyperoxia as neonates (Yee et al., 2020).

We have previously demonstrated that circadian rhythms offer a protection against IAV, wherein mortality is threefold lower if the animals are infected in the morning than in the evening (Sengupta et al., 2019). This time of day-specific protection is lost upon genetic disruption of the clock via global deletion of core clock gene, Bmal1, which exacerbates immunopathology independent of viral replication. In keeping with their evolution imperative, circadian rhythms temporally segregate physiological process that allows organisms to anticipate its environment and adapt accordingly. The suprachiasmatic nucleus (SCN) is the master circadian pacemaker; however, peripheral tissues, including the lung, also have cell autonomous clocks (Spengler and Shea, 2000). Changes in oxygen tension are known to affect the clock (Walton et al., 2018; Wu et al., 2017). Low oxygen levels or hypoxia stabilize hypoxia-inducible factor (HIF). There exists a reciprocal relationship between the circadian clock and Hif1a mediated at the genomic level (Peek et al., 2017; Wu et al., 2017). More recently, even a short burst of hypoxia was shown to desynchronize the relationship between the SCN and peripheral clocks (Manella et al., 2020), which would confer further risk under conditions of stress. However, the effect of hyperoxia, especially very early in life, on circadian regulation of the recovered lung has not been investigated.

The early neonatal period represents a critical window for the development and consolidation of many important pathways, including circadian rhythms (Bartman et al., 2020; Rivkees, 2007; Yang et al., 2014). Early-life exposure to light (Coleman and Canal, 2017; Smarr et al., 2017), inflammation (Adler et al., 2014), or alcohol has disruptive effects on circadian rhythms in adulthood (Allen et al., 2005). But despite the high incidence of hyperoxia in premature neonates, how neonatal hyperoxia affects the development of circadian regulatory networks is not known. We hypothesized that early-life hyperoxia disrupts the development of circadian rhythms and that such disruption undermines recovery from lung injury. Here we test this hypothesis using an IAV infection model of adult mice exposed to neonatal hyperoxia. We find that indeed exposure to neonatal hyperoxia abrogates the time of day protection from circadian regulation of IAV infection through primarily host tolerance rather than anti-viral effects. This effect appears stage specific to the saccular stage of development that corresponds to the period during which the mice were exposed to hyperoxia in our model since adult mice exposed to hyperoxia did not lose the time of day-specific protection. To identify the location of the relevant clock, we used tissue-specific adult onset deletion of the core clock gene Bmal1. We report that disrupting Bmal1 in AT2 cells of the lung faithfully recapitulates the phenotype of animals exposed to neonatal hyperoxia, suggesting that early-life hyperoxia disrupts the circadian regulation of the pulmonary response to hyperoxia through the AT2 clock.

Results

Neonatal hyperoxia abrogates the circadian protection from influenza infection in recovered adults

We previously showed that mice infected at ZT11 (ZT11 refers to ‘Zeitgeber Time’ 11 or dusk which marks the beginning of the active phase in mice since they are nocturnal) had threefold higher mortality than mice infected at ZT23 (dawn or at the beginning of their rest phase) (Sengupta et al., 2019). Upon global disruption of the clock (Bmal1fl/fl:CAGGcreERt2/+), in adult animals, the time of day difference was lost such that the mortality was high irrespective of the time of day of infection (Sengupta et al., 2019). Here we hypothesized that neonatal hyperoxia would disrupt circadian rhythms to result in a loss of temporal difference in outcomes in recovered adult mice infected with IAV at ZT11(dusk) or ZT23 (dawn). Mice exposed to either hyperoxia or room air as neonates were recovered to adulthood and infected with IAV (H1N1 mouse-adapted strain PR8) at either ZT23 or ZT11 (Figure 1a). Mice are born at the saccular stage of lung development that corresponds to 24–28 weeks gestation for humans (Warburton et al., 2010) and thus neonatal hyperoxia provides an excellent model to study BPD (Hilgendorff et al., 2014). The room air controls maintained the time of day difference in mortality; the group infected at ZT11 had a mortality 2.6 times higher than the mice infected at ZT23 (survival 72% in ZT23 vs. 33% in ZT11, p<0.01). By contrast, the mice that had been exposed to hyperoxia as neonates lost this time of day difference: both groups had mortality comparable to the ZT11 (in RA) group (survival in hyperoxia groups: ZT23 at 37% and ZT11 at 25%; Figure 1b and c). However, when adult mice exposed to hyperoxia were infected with IAV at either ZT23 or ZT11 (Figure 1—figure supplement 1), they maintained the same difference in outcomes as seen in room air controls in Figure 2b and c. Thus, exposure to hyperoxia as adults did not appear to impair the circadian control over mortality and morbidity from IAV seen with exposure to neonatal hyperoxia. Considered together, this suggests that early life (p0–p5) accords a unique window of influencing circadian regulation and as such exposure to hyperoxia during this period disrupts circadian regulation of the lung injury response to IAV infection.

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Overall experimental design and effects of neonatal hyperoxia on circadian regulation of IAV infection adulthood.

(A) Experimental model for neonatal hyperoxia followed by IAV infection: C57Bl6 pups aged <12 hr were exposed to either hyperoxia (>95% O2) or room air (21% O2) from PN0–5. Thereafter, the pups were recovered in room air to adulthood (8–12 weeks). As adults, the mice were place in reverse 12 hr light–dark cycles for 2 weeks before being infected with the influenza A virus (PR8). Experimental design: Adult mice were placed in 12 hr light–dark reverse cycles and infected with 25–40 PFU of PR8 at either ZT23 (dawn or just before the onset of rest phase) or at ZT11 (dusk or just before the onset of activity, since mice are nocturnal animals). (B) Survival (n = 17–18 per group, **p=0.0027 log-rank test test from three independent experiments) and (C) Percentage of body weight lost (n = 10–15 per group, *p<0.001 ANOVA for repeated measures) following IAV infection (25–40 PFU PR8) at either ZT23 (dawn) or at ZT11(dusk). (D) Survival of mice exposed to hyperoxia as adults and infected with IAV after 3–4 weeks of recovery (n = 8–16 per group, *p=0.0417 log-rank test from two independent experiments). (E) Percentage of body weight lost (n = 17–18 per group, *p=0.0091 for time of infection by REML mixed effects model for repeated measures) following IAV infection (25–40 PFU PR8) at either ZT23 (dawn or just before the onset of rest phase) or at ZT11 (dusk or just before the onset of activity, since mice are nocturnal animals).

Figure 1—source data 1

Source data for Figure 1.

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Figure 2
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Loss of temporal gating of IAV infection in adults exposed to hyperoxia as neonates is not mediated through central circadian clock.

Mice pups <12 hr old were exposed to either hyperoxia or room air for 5 days and then recovered in RA into adulthood. As adults, effect on the central (locomotor activity) and peripheral (gene expression from lung and spleen, flow cytometry of lung resident immune cells, and bioluminescence of period two gene) clocks was measured. (A) Central effects were assessed by actigraphy measurements of rest and activity in constant darkness. Period, amplitude, activity counts, and phase of this locomotor activity in adult mice exposed to neonatal hyperoxia or room air (n = 6–15 per group). (B) Representative actigraph images taken from adult mice exposed to either neonatal hyperoxia or room air. This graph depicts the rest–activity behavior from a representative mouse where consecutive days are plotted on the y-axis, and time (in hours) is shown on the x-axis. The black bars represent the number of turns of the running wheel/movement sensed by the infrared motion sensors and indicates a time when the mouse of active. (C) Period length across days to acclimatize from constant darkness (DD) to 12 hr LD conditions adult mice exposed to neonatal hyperoxia or room air (n = 5–6 per group).

Figure 2—source data 1

Source data for Figure 2.

https://cdn.elifesciences.org/articles/61241/elife-61241-fig2-data1-v1.xlsx

Neonatal hyperoxia has only subtle effects on the central clock in adulthood

To determine the effect of neonatal hyperoxia on central circadian rhythms in adulthood, we evaluated the locomotor activity patterns of adult mice (8–12 weeks old of both genders) exposed to 5 days of neonatal hyperoxia (≥95% O2 starting <12 hr of age to 5 days post-natal). A similar duration of hyperoxia is known to cause alveolar oversimplification, as seen in BPD (Yee et al., 2011). Immediately after exposure, the pups exposed to hyperoxia weigh less (Figure 1—figure supplement 2). However, these pups are indistinguishable from the room air controls in weight or overall activity by 8–12 weeks of age (Figure 1—figure supplement 2). To exclude differences in exercise tolerance, we measured locomotor activity using both infrared sensors and running wheels and found that the two methods yielded similar results. Interestingly, while phase, period length, amplitude, and total activity patterns were comparable between the two groups, the hyperoxia group displayed significantly more variation in their period lengths (Figure 2a).

Infection with IAV disrupts circadian locomotor rhythms under in a mouse model of COPD (Sundar et al., 2015), raising the possibility that further stress may unmask a central phenotype. To address the hypothesis that neonatal hyperoxia caused instability of circadian regulation, we examined the ability of the animals to re-entrain to 12 hr light-dark cycles after several weeks in constant darkness. Entrainment refers to the re-synchronization of the internal or endogenous circadian rhythms to external cues (Golombek and Rosenstein, 2010), such as the change in lighting schedule here, and is a way to assess the function of the central clock (Tahara and Shibata, 2018). Normoxia and hyperoxia groups did not entrain differently to this small change (Figure 2b and c). Thus, considered together, these data are consistent with the hypothesis that effects of neonatal hyperoxia on IAV infection are not mediated via lasting changes in the central clock.

Effect of neonatal hyperoxia on resident immune cells in the lung

We next addressed the possibility that loss of circadian gating of IAV responses in mice exposed to neonatal hyperoxia was secondary to circadian dysregulation of the immune response. We harvested lungs from adult animals exposed to either room air or hyperoxia as neonates and separated different populations of immune cells by flow cytometry at either the beginning of the rest phase (ZT23) or the beginning of the active phase (ZT11). While the total CD45+ population did not differ at these time points in the normoxia group, mice at ZT23 had higher numbers of CD45+ cells than at ZT11 in the hyperoxia group (Figure 3a). The percentage of natural killer (NK) was significantly lower in the hyperoxia-exposed mice at both time points. And the phase of the monocytes seems to reverse upon exposure to hyperoxia. Interestingly, in our previous work, more NK cells and lesser inflammatory monocytes were present in the group infected at ZT23 relative to the ZT11 group and thus associated with better outcomes (Sengupta et al., 2019). Since these changes in the immune population were noted at baseline, we delved further into the circadian control of immune response to IAV as a mechanism to explain the lack of circadian protection in adults exposed to hyperoxia as neonates.

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Exposure to hyperoxia as neonates has subtle effects of the circadian regulation of the immune response to influenza infection.

(A) Flow cytometric enumeration of the CD45+ cells from lungs of adult mice exposed to neonatal hyperoxia or room air (n = 5–7/group from three independent experiments). (B) Viral burden measure by hemagglutination inhibition assay (n = 5–7/group) by two-way ANOVA, p<0.001 for time post-infection, p=0.8855 for treatment group and interaction. (C) Left: Representative micrographs of H and E stained lung sections 8 days after IAV (40 PFU) treatment of adults exposed to neonatal hyperoxia or room air (photomicrograph bar = 100 µm). Right: Severity of lung injury quantified using an objective histopathological scoring system by a researcher blinded to study group (n = 4–8 mice/group; data as median, IQR; Wilcoxon rank sum test; **p<0.01; pooled data from two independent experiments). (D) Bronchoalveolar lavage (BAL) from animals infected at either ZT11 or ZT23 on day 1 and 5 p.i. (n = 5–6/group, p=0.0001 for time at infection, p<0.0001 time after infection, and p=0.0023 for interaction by two-way ANOVA).

Figure 3—source data 1

Criteria for scoring lung injury on histology.

https://cdn.elifesciences.org/articles/61241/elife-61241-fig3-data1-v1.xlsx
Figure 3—source data 2

Source data for Figure 3.

https://cdn.elifesciences.org/articles/61241/elife-61241-fig3-data2-v1.xlsx

Immune mechanisms underlying the circadian dysregulation of IAV-induced lung injury in adults exposed to neonatal hyperoxia: We showed previously that circadian control of IAV-induced lung injury and outcomes is not mediated by viral burden, but rather by the control of inflammation, with the group infected at ZT11 revealing evidence of exaggerated inflammation (Sengupta et al., 2019). Coupled with our findings above of impaired immune cell regulation in hyperoxia-treated animals, we hypothesized that the loss of time-of-day protection in these animals would be manifest as an exaggerated inflammatory response irrespective of the time of infection.

Consistent with our previous work, we found that the viral burden was comparable between the groups infected at ZT11 or ZT23; this held true in both neonatal hyperoxia- and room-air-exposed groups (Figure 3b and Figure 3—figure supplement 1). Next, we quantified lung injury on histological analyses using a previously validated scoring system (Sengupta et al., 2019). The scores were based on peri-bronchial inflammation, peri-vascular inflammation, alveolar inflammatory exudates, and epithelial necrosis/sloughing. (Scoring system detailed in Figure 3—source data 2.) On histological analyses, animals infected in the hyperoxia group scored worse for lung injury and the time of day difference in severity was absent (Figure 3c). To address the hypothesis that an exaggerated inflammatory response abrogated circadian variability in the innate immune response of animals exposed to neonatal hyperoxia, we performed bronchoalveolar lavage on days 1 and 5 following infection with IAV. Concordant with our previous work, among control animals exposed to room air as neonates, the room air group showed a higher total BAL count at ZT11 than at ZT23 by day 5 p.i. (Figure 3d) among control animals exposed to room air as neonates. Contrary to our hypothesis, this was not influenced by neonatal exposure to hyperoxia, since even among the hyperoxia-exposed pups, the total BAL count was higher in the ZT11 than in the ZT23 group. Thus, impaired circadian regulation of the response to IAV does not appear to arise directly from deficits in the circadian regulation of innate immunity.

Effect of neonatal hyperoxia on the pulmonary circadian system

We next investigated the effect of hyperoxia on the intrinsic clock in the lung by whole lung gene expression assays as well as with the use of a circadian reporter. On visual inspection, subtle differences in the phase of the oscillation of core clock genes Bmal1, Per2, and Nr1d2 were noted as a consequence of neonatal hyperoxia, but none of these changes were statistically significant (Figure 4a). However, since bulk gene expression may conceal functionally relevant changes in cell-specific circadian oscillation, we next used Per2luc mice, exposed them to hyperoxia as neonates and then recorded their bioluminescence ex vivo at 10–11 weeks of age. The hyperoxia-exposed animals showed rhythmic expression of the Period2 gene with comparable periodicity and phase to the animals exposed to room air. However, the amplitude of these oscillations was significantly dampened in the hyperoxia group (Figure 4b). These data are consistent with the hypothesis that the perturbation induced by IAV infection unmasks a dysregulation of circadian function intrinsic to the lung in animals exposed to neonatal hyperoxia.

Figure 4
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Exposure to hyperoxia as neonates reduce the amplitude of circadian oscillations in lung explants from adult animals.

(A) Gene expression of clock genes from whole lungs harvested at 6 hr intervals determined by qPCR (n = 4–6 per time point from three different experiments). (B) Representative bioluminescence tracings, period, amplitude, and phase from lung explants from adult Per2luc mice exposed to neonatal hyperoxia or room air (n = 4 from two independent experiments).

Figure 4—source data 1

Source data for Figure 4.

https://cdn.elifesciences.org/articles/61241/elife-61241-fig4-data1-v1.xlsx
Figure 4—source data 2

qPCR primers used to generate data for Figure 4.

https://cdn.elifesciences.org/articles/61241/elife-61241-fig4-data2-v1.xlsx

Disrupting the circadian clock in AT2 cells in adulthood recapitulates the loss of time of day protection seen in adults exposed to neonatal hyperoxia

Neonatal hyperoxia disrupts the development of the respiratory epithelium, at least in part due to the depletion of AT2 cells after recovery (Yee et al., 2014). During hyperoxia, the AT2 cell number expands as a source of AT1 cells; upon return to room air for recovery, there is a progressive depletion of AT2 cells, with approximately 70% surviving at 8 weeks of age (Yee et al., 2014; Yee et al., 2016). Thus, given the role of the type two airway epithelial cells in hyperoxic injury and repair, we asked if clock disruption in AT2 cells would be sufficient to re-capitulate the effects of neonatal hyperoxia in terms of loss of circadian gating in response to IAV. An effect localized to AT2 cells would also be consistent with the relatively intact circadian gene expression in hyperoxia-treated mice, given that AT2 contribute only a small percentage of the cells in the total lung (Figure 4a).

To test the relevance of the clock in AT2 cells, we generated mice in which the core clock gene, Bmal1 was deleted in these cells (SftpcCreERt2/+::Bmal1fl/fl). In the tamoxifen-treated SftpcCreERt2/+::Bmal1fl/fl mice, Bmal1 expression was selectively absent in AT2 cells but not elsewhere such as the airway epithelium (Figure 5—figure supplement 1). While the cre− mice infected in the morning had better survival than cre− mice infected in the evening (Figure 5a; 72% survival in CT23 group versus 20% survival is CT11 group; p<0.01 by Mental–Cox test), this time of day difference was lost in mice lacking Bmal1 in their AT2 cells (Figure 5a; 25% survival in CT23 group versus 38% in the CT11 group of SftpcCreERt2/+::Bmal1fl/fl). CT11 and CT23 refer to the time corresponding to ZT11 and ZT23, respectively, in constant darkness. In models of Bmal1 deletion, we and others have used constant darkness conditions to avoid any differential effects of light on relevant peripheral clocks (Gibbs et al., 2014; Sengupta et al., 2019; Yang et al., 2016). A pattern similar to the mortality was also noted in the weight loss trajectory from SftpcCreERt2/+::Bmal1fl/fl and cre−littermates (Figure 5b). Thus, post-natal deletion of Bmal1 specifically in AT2 epithelial cells thus recapitulated the impact of neonatal hyperoxia on IAV-induced mortality and morbidity.

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Disrupting the circadian clock in AT2 cells in adults recapitulates the phenotype seen in adult animals exposed to hyperoxia as neonates.

Experimental design: SftpcCreERt2/+::Bmal1fl/fl mice (mice lacking Bmal1 in AT2 cells of the lung epithelium) and their creneg littermates were treated with tamoxifen at 6–8 weeks of age and acclimatized to reverse cycles of 12 hr LD for 2 weeks. Thereafter, they were maintained in constant darkness for 2–4 days prior to administering IAV (PR8) at CT23 and CT11 and acclimatized to reverse cycles of 12 hr LD for 2 weeks. Thereafter, they were maintained in constant darkness for 2–3 days prior to administering IAV (PR8) at CT23 and CT11. CT23 and CT11 refer to the time corresponding to ZT23 and ZT11, respectively, when animals are maintained under constant darkness conditions. (A) Survival curves (n = 16–18 in SftpcCreERt2/+::Bmal1fl/fl groups and n = 20–21 in creneg, *p=0.0014 Mantel–Cox test; pooled data from four independent experiments). (B) Percentage of body weight lost (n = 16–18 in SftpcCreERt2/+::Bmal1fl/fl groups and n = 18–20 in creneg group from three independent experiments *p<0.01 ANOVA for repeated measures). (C) Viral burden measure by hemagglutination inhibition assay (n = 5–13/group) by two-way ANOVA, p<0.0001 for time post-infection, p=0.9981 for treatment group and interaction. (D) Left: Representative micrographs of H and E stained lung sections 8 days after IAV (40 PFU) treatment of SftpcCreERt2/+::Bmal1fl/fl mice and their cre− littermates (photomicrograph bar = 100 µm). Right: Severity of lung injury quantified using an objective histopathological scoring system by a researcher blinded to study group (n = 4–8 mice/group; data as median, IQR; Wilcoxon rank sum test; **p=0.0014, CT23 vs. CT11 for Cre+ refers to SftpcCreERt2/+::Bmal1fl/fl mice vs. Cre− which refers to SftpcCreERt2neg::Bmal1fl/fl; pooled data from three independent experiments).

Figure 5—source data 1

Source data for Figure 5.

https://cdn.elifesciences.org/articles/61241/elife-61241-fig5-data1-v1.xlsx

Bmal1 deletion in AT2 cells reiterates the phenotype of circadian dysregulation seen in adult animals exposed to hyperoxia as neonates

As loss of circadian protection may be caused by different mechanisms, we sought to determine whether this loss in the SftpcCreERt2/+::Bmal1fl/fl animals was associated with similar underlying mechanisms as those one seen in hyperoxia-exposed animals. Specifically, we determined whether the loss of circadian protection was mediated through anti-viral or host tolerance pathways.

We found that the viral loads at days 1 and 5 and day 8 were comparable across genotypes in animals infected at CT11 or CT23, both via hemagglutination inhibition assay (Figure 5c) and viral nucleic acid expression (Figure 5—figure supplement 1). This result is identical to that seen in hyperoxia-treated animals exposed to IAV (Figure 3b). We next compared the histology of the cre+ and the cre− animals infected with IAV and found, again, that it was reminiscent of the hyperoxia-treated animals. While the lung pathology was worse in cre− group infected at CT11 than at CT23, this time of day protection was lost in the cre+ animals, where the histology was worse at both CT11 and CT23 (Figure 5d). Furthermore, we found that many of the gene expression signatures were comparable between the hyperoxia-treated animals and those with Bmal1 deleted in AT2 cells. This included a reduction in Il1b and Il10 in both hyperoxia-exposed animals and cre+ mice, while the pattern of change was comparable for ccl2 (all on day 5 p.i. in Figure 6a). Finally, even with the loss of Bmal1 in AT2 cells (SftpcCreERt2/+::Bmal1fl/fl), the BAL cell count varied by time of day (Figure 6b), being higher in CT11 than at CT23 in both cre+ and cre− animals on day 5 p.i. – again similar to the BAL count patterns seen in adults exposed to hyperoxia. Considered together, these results support the possibility that early-life hyperoxia disrupts the circadian rhythm-mediated protection in IAV-induced lung injury through AT2-clock-mediated effects.

Figure 6
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Disrupting the circadian clock in AT2 cells in adults recapitulates the gene expression pattern and BAL expression in adult animals exposed to hyperoxia.

(A) Whole lung gene expression measured by qPCR on day 5 post-infection in adults exposed to neonatal hyperoxia or room air (left panel) and SftpcCreERt2/+::Bmal1fl/fl mice (mice lacking Bmal1 in AT2 cells of the lung epithelium referred to in the figures as SPC-cre+) and their cre− littermates referred to as SPC-cre− (right panel). (B) Bronchoalveolar lavage (BAL) from animals infected at either CT11 or CT23 on day 5 p.i. (n = 4–6/group, p=0.0063 for time of day by two-way ANOVA).

Figure 6—source data 1

Source data for Figure 6.

https://cdn.elifesciences.org/articles/61241/elife-61241-fig6-data1-v1.xlsx

Discussion

In the current study, we systematically studied the effect of an early-life hyperoxia exposure on the function of circadian rhythms in adulthood. A hallmark of circadian regulation is a difference in outcomes based on time of day at which the insult is sustained. We found that this time of day-specific protection from IAV is lost in adult animals exposed to hyperoxia as neonates, reminiscent of the effect of global genetic disruption of core clock gene Bmal1 from our previous work (Sengupta et al., 2019). Hyperoxia is known to cause significant damage to the lung and one speculation might be that the loss of the time of day difference in outcomes in reflective of a generalized lack of well-being rather than a loss of circadian control. However, our data clearly refutes that possibility, given that the hyperoxia-exposed groups only ever have mortality comparable to the control group infected in the evening; not worse. We have also seen the loss of this circadian protection without worsening beyond the ZT11 group at lower doses of the virus (data not shown).

Consistent with our previous observations on clock disruption, the viral burden after challenge was similar across all the groups. Thus, the loss of protection from IAV in mice exposed to hyperoxia as neonates is not due differences in viral replication. Therefore, we addressed the possibility that this loss of central gating reflected dysregulation of central clock function (measured as locomotor activity rhythms), the immunological response to infection or peripheral clock function in pulmonary epithelial cells.

We found that mice exposure to neonatal hyperoxia did not have a significant effect on the central clock by adulthood. This is not surprising – while other adverse effects early in life are known to disrupt local or central circadian rhythmicity (Coleman and Canal, 2017; Smarr et al., 2017), the SCN clock is well known to be resistant to non-photic stimuli (Damiola et al., 2000; Stokkan et al., 2001). At baseline, we also saw that neonatal hyperoxia could disrupt the immune clock, which would account for abrogated time of day protection from IAV. Since these cell populations were implicated in the exaggerated inflammation in the groups infected in the evening (Sengupta et al., 2019), we initially hypothesized that neonatal hyperoxia disrupts the immune clock which in turn abrogates the circadian protection from IAV. However, following IAV infection total BAL cell counts were higher in the group infected at ZT11 than in those infected at ZT23 in both the room air and neonatal hyperoxia-exposed animals. This is in contrast with the work of O’Reilly et al. who have shown that adults exposed to hyperoxia as neonates had a hyper-inflammatory response, with higher BAL counts in comparison to the room air controls. We speculate that this difference from the work by O'Reilly et al., 2008 results from our circadian experimental design since we infected mice at dawn and dusk. Furthermore, we found that exposure to hyperoxia did not change the viral burden at either time points, which is consistent with previous literature. Overall, given that even in our previous work, the myeloid clock did not completely control the phenotype seen in animals with a disrupted clock, we focused on the lung epithelium.

The lung consists of anatomically distinct regions (tracheas, bronchioles, and alveoli) each populated by structurally and functionally distinct epithelial cell types. Tracheas and proximal airways are lined by multi-ciliated cells, secretory cells (Scgba1a1+), goblet cells, and basal stem/progenitor (BSC) cells. The small airways terminate in the alveolar sacs, which are mainly composed of alveolar type1 (AT1) or AT2 cells (Zepp and Morrisey, 2019). Although all epithelial cells are susceptible to IAV infection, AT2 cells are primarily affected by neonatal hyperoxia. Even though there were only subtle differences in gene expression rhythms assayed in the entire lung, the possibility that the AT2 clock is disproportionately affected cannot be ruled out. We suspect that since AT2 cells contribute only a small portion of the total RNA extracted from the lung, the disruptive effect on the AT2 clock was underestimated. In fact, in our lung explant model, while pulmonary rhythmicity was maintained, the amplitude was definitely blunted in the hyperoxia-treated group. Thus, a role for the AT2 clock is supported by our Bmal1−/− data.

We and others (Gibbs et al., 2014; Sengupta et al., 2019; Zhang et al., 2019) have demonstrated a role for the Scgb1a1 (or CCSP) clock in mediating lung injury, however, this is the first report of a cell intrinsic clock in AT2 cells. Although many clock genes participate in the generation and maintenance of circadian rhythms, Bmal1 is the only circadian gene whose sole deletion is sufficient to cause arrhythmicity of locomotor activity – the hallmark of circadian disruption. Embryonic deletion of Bmal1 results in a severe accelerated aging phenotype, in which the circadian phenotype is confounded by potentially off target developmental effects of Bmal1 deletion (Yang et al., 2016). We avoid any confounding by non-circadian effects from Bmal1 by targeting gene deletion in adulthood. The time of day difference in IAV induced mortality in cre− littermates was abrogated amongst SftpcCreERt2/+::Bmal1fl/fl mice, treated with tamoxifen at 8 weeks of age. It is intriguing that the both hyperoxia and AT2 clock disruption not only abolish the circadian directed time of day protection from IAV, but also share many similarities in the mechanisms underlying this dysregulation. In both conditions, the loss of circadian regulation of the host response to IAV is not mediated through control of viral burden, but rather through worse injury. Overall, our data strongly support the possibility that hyperoxia disrupts the circadian regulation of lung injury in IAV through the AT2 clock. Since many of the Scgb1a1-cre models affect AT2 cells as well (Rawlins et al., 2009), it is possible that the Scgb1a1-cre described previously overestimates the effect of Bmal1 deletion. Thus, neonatal hyperoxia impairs the circadian regulation of host response to IAV in adult mice.

Our work further strengthens the observation in the field that oxygen tension modulates the circadian clock. While we focused on long-term effects of neonatal hyperoxia on circadian networks, Lagishetty et al. has suggested that hyperoxia exposure in adult mice changes the circadian gene expression, although only a single time point was assessed (Lagishetty et al., 2014). Most evidence for the connection between the changes in oxygen tension and circadian clock comes from hypoxia. Interestingly, both clock and HIF belong to the same basic helix-loop-helix PER-ARNT-SIM (bHLH-PAS) transcription factor super family. In the skeletal muscle, a reciprocal relationship was noted between the hypoxia-sensing HIF1 pathways and the circadian clock – the response to hypoxia is gated by the circadian clock and HIF1α binds to clock targets to modulate the clock output under hypoxic conditions (Peek et al., 2017). Furthermore, HIF1α is shown to accelerate adaptation to jetlag, suggesting an interaction between the two at a central level (Adamovich et al., 2017). More recently, hypoxia was shown to desynchronize the relationship between peripheral tissue clocks (Manella et al., 2020). Our work here suggests that a unique window exists in the lung in the early neonatal period that might affect circadian regulation throughout later life. Since this period, (around p4) affects the development of AT2 population, it was not surprising that AT2-specific disruption of the circadian clock, via Bmal1 deletion, recapitulated the results from the neonatal hyperoxia cohort. Many developmental pathways such as the Wnt-βcatenin pathways have recently been demonstrated to be central to the pathogenesis of BPD following neonatal hyperoxia (Sucre et al., 2020). Thus, one possibility would be that the developmental reprogramming that is triggered by noxious stimuli like neonatal hyperoxia also disrupts the development of the circadian networks within the epithelium. Neonatal hyperoxia affects multiple transcription factors such as Nfe212, Cdnk1a, Fos, Trp53, Rela, Stat3, and Cebpa (Wright and Dennery, 2009). Many of these transcription factors and pathways are known to be under circadian control. Thus, one possibility is that a reciprocal relationship between one or more of these pathways and the circadian clock may underlie the life course effects of hyperoxia on circadian regulation, akin to the Hif1a and Bmal1 connection discussed above. However, since there is not a single regulatory node for hyperoxia unlike the hypoxia–Hif1a axis, it is hard to speculate which specific pathway would play this role.

In conclusion, children born prematurely and suffering from even mild BPD have persistent adverse effects on their lung function into adulthood. This may result in part from long-lasting damage to circadian mechanisms residing in AT2 cells that influence the response to injury after viral infection. The current study provides a circadian paradigm for the long-term consequences of early-life insults in this vulnerable population, paving the way for novel therapeutics and chronobiological strategies.

Materials and methods

Key resources table
Reagent type
(species) or resource		DesignationSource or referenceIdentifiersAdditional information
AntibodyAnti-Bmal1 (Rabbit monoclonal)Abcamab230822IF(1:1000)
Antibodyanti-Pro-SPC (Rabbit polyclonal)EMD Milliporeab3786IF(1:2000)
AntibodyNk1.1 (Mouse monoclonal)Biolegend108716Flow cytometry (1:100)
AntibodyLy6C (Mouse monoclonal)Biolegend128024Flow cytometry (1:100)
AntibodyCD45 (Rat monoclonal)Biolegend103114Flow cytometry (1:100)
AntibodyCD11c (Hamster monoclonal)Biolegend117324Flow cytometry (1:100)
AntibodyCD11b (Mouse monoclonal)EBiosciences11-0112-41, 47-0112-82Flow cytometry (1:100)
AntibodyCD3 (Rat monoclonal)EBiosciences11-0032-82Flow cytometry (1:50)
AntibodyLy6G (Rat monoclonal)Biolegend127606, 127608,Flow cytometry (1:100)
AntibodySiglec F (Rat monoclonal)BD Pharmingen552126Flow cytometry (1:100)
Software AlgorithmClocklabActimetricsRest-activity analyses
OtherDAPI stainD1306(1 µg/mL)
Chemicals strain, strain background (include species and sex here)TamoxifenSigmaT5648-1G
Strain, strain background (include species and sex here)C57BL/6JJaxStock No: 000664 | B6Both genders and age at infection > 8 weeks

Animal models, hyperoxia exposure, and influenza infection

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For neonatal hyperoxia, newborn C57BL/6J mice (<12 hr old) were exposed to either 21% oxygen (room air) or ≥95% oxygen (O2) between post-natal days 0 and 5. Mice are born in the saccular phase of lung development and thus exposure to hyperoxia shortly after birth simulates the effects of hyperoxia on preterm lungs. This model of BPD is well established. Similar models have resulted in mild alveolar oversimplification and airway hyper-reactivity at 8 weeks of life (Yee et al., 2011). To minimize oxygen toxicity, nursing dams were switched out every 24 hr. Following exposure, the hyperoxia-exposed pups were recovered in room air with/alongside their littermates under 12 hr LD conditions until 8–10 weeks of age. For adult hyperoxia exposure, 8 week old C57BL/6J (RRID:IMSR_JAX:000664) mice were exposed to or ≥95% oxygen for 48 hr. Thereafter, the mice were recovered in room air for a period of 3–4 weeks and acclimatized to reverse light cycling to split up the group into two for further influenza infection.

For influenza infections, mice were acclimatized to reverse cycles in specially designed circadian chambers for 2 weeks. Thereafter, they were infected at ZT23 or Z11 with 30 PFU of IAV (PR8) i.n. under light isoflurane anesthesia. This method has been used and validated in our previous work and is used by many circadian labs to remove confounding from infecting animals at different times of the conventional day (Sengupta et al., 2019).

Mouse strains and tamoxifen administration

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A mouse line with AT2 cell-specific knockout of Bmal1 was generated by crossing SftpcCre-ERT2/+, a tamoxifen-inducible Cre, with Bmal1fl/fl mice. The SftpcCreERT2/+ mice (on mixed Balbc/C567 background) were a kind gift from E.E. Morrissey (University of Pennsylvania; originally made in Dr. H. Chapman’s group [Chapman et al., 2011] and has been used widely in the field to target AT2 cells). The animals were back crossed for four to five generations onto a C57 background. Tamoxifen (Sigma–Aldrich) was dissolved/reconstituted in corn oil and ethanol to create a 100 mg/mL stock solution. Bmal1 deletion was induced by administration of tamoxifen (5 mg dissolved in corn oil/ethanol) via oral gavage for five consecutive days. Following tamoxifen treatment, mice were acclimatized to reverse light–dark cycles for 2 weeks, then placed in constant darkness 2 days before being infected with PR8 (25–35 PFU). Weights were monitored before, during, and post-tamoxifen administration, and no significant weight loss was noted. They were acclimatized to reverse light–dark cycles for 2 weeks and exposed/placed in constant darkness 24–48 days before being infected with PR8 at (CT/ZT23 and 11).

Flow cytometry

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Lungs were harvested after perfusion with 10 mL of phosphate-buffered saline (PBS) through the right ventricle. The lungs were digested using DNAse II (Roche) and Liberase (Roche) at 37°C for 30 min. Dissociated lung tissue was passed through a 70 µm cell strainer, followed by centrifugation and red blood cell (RBC) lysis. Cells were washed and re-suspended in PBS with 2% fetal bovine serum. (Details of the antibodies in Figure 3–Source data 1.) 2–3 × 106 cells were blocked with 1 µg of anti-CD16/32 (Fc Block) antibody and were stained with indicated antibodies on ice for 20 min. No fixatives were used. Flow cytometric data was acquired using FACS Canto flow cytometer and analyzed using FlowJo software (Tree Star, Inc). All cells were pre-gated on size as singlet live cells. All subsequent gating was on CD45+ in lung only. Neutrophils were identified as live, CD45+, and Ly6G+ cells. Ly6Chi monocytes were identified as live, CD45+Ly6G−Ly6ChiCD11b+ cells. NK cells were identified as CD45+Ly6G−LysC-NK1.1+CD3+ cells.

Histology and staining

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Lungs from the mice were inflated and fixed with 10% neutral buffered formalin (Sigma–Aldrich), embedded in paraffin, and sectioned. Lung sections were stained with hematoxylin–eosin. Stained slides were digitally scanned at 40× magnification using Aperio CS-O slide scanner (Leica Biosystems, Chicago, IL). Representative images were taken from the scanned slides using Aperio ImageScope v 12.4. Soring was performed blindly using previously validated scoring method (Sengupta et al., 2019). Briefly, the eight lung fields selected at random at 20× magnification were scored based on a scale of 0–3 for the following (1) peri-bronchial infiltrates, (2) per-vascular infiltrates, (3) alveolar exudates, and (4) epithelial damage of medium-sized airways. For immunofluorescence staining, paraffin sections of SftpcCreERt2/+::Bmal1fl/fl+ and SftpcCreERt2neg::Bmal1fl/fl were obtained. Slides were stained with anti-BMAL1 antibody (Abcam, ab230822, 1:1000, RRID:AB_2889035) followed by secondary antibody staining with alexa 488 Straptavdin (A21370, Life Technologies, Eugene, OR, 1:200). Slides were then incubated with anti Pro Surfactant protein (EMD Millipore ab3786, RRID:AB_91588, 1:2000) followed by alexa 594 anti-rabbit (Invitrogen A21207). Slides were then rinsed, counterstained with DAPI, and rinsed again before cover slipping with Prolong Gold (P36930, Life Technologies, Eugene, OR). At least five randomly selected regions were imaged for three samples/genotype on Leica DM 4000 B at 20× and 63×.

Quantitative PCR

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RNA was isolated/extracted from the inferior lobe of the mouse lung using TRIzol (Life Technologies). RNA was further purified using the RNeasy Mini Elute Clean Up Kit (Qiagen). The quantity and quality of RNA were assessed using the NanoDrop ND- 1000 spectrophotometer (NanoDrop Technologies Inc) and cDNA prepared with TaqMan. SYBR Green gene-expression assays were used to measure mRNA levels for genes of interest. Eukaryotic 18S rRNA (Life Technologies) and 28S (Sigma) were used as an internal control for TaqMan and SYBR Green assays, respectively. The samples were run on a Viia7 real-time PCR thermal cycler (Roche), and the relative ratio of the expression of each gene was calculated using the 2ΔΔCt method. Gene expression values for each of Bmal1, Cry1, Per2, Nr1d1, and Nr1d2 were fit by least squares to cosinor curves with a fixed period of 24 hr. Gene expression data was plotted in MATLAB (MATLAB R2020a; The MathWorks Inc) using the curve-fitting function that generates a best-fit line for the given data. A cosinor linear model was fit to the data for each gene (Cornelissen, 2014). An F-test comparing the full model allowing for differences in amplitude, phase, and mesor between the hyperoxia and room air conditions to the restricted model allowing only differences in mesor between conditions yielded no significant results at the p=0.05 level.

Primers: All primers were procured from Thermofisher life sciences. Catalog numbers are provided in source data file.

Viral titration

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As described before (Sengupta et al., 2019), we harvested lungs at different time points following infection, as indicated in the specific experiment. Following homogenization in PBS–gelatin (0.1%), these lungs were frozen for preservation. The presence of influenza virus was evaluated using MCDK (RRID:CVCL_0422) cells with 1:10 dilutions of the lung homogenates at 37°C. After 1 hr of infections, 175 µL of media containing 2 µg/mL trypsin was added and the cells were further incubated for 72 hr at 37°C. A total of 50 µL of medium was then removed from the plate and tested by hemagglutination of chicken RBCs for the presence of virus particles. The hemagglutination of RBCs indicated the presence of the virus.

Rest–activity measurements

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Mice were singly housed in circadian light control boxes (Actimetrics) to measure their locomotor or rest–activity rhythms using either running wheels or Infrared Motion Sensors (Actimetrics). After the mice were acclimatized to circadian chambers, their activity was measured in 12 hr LD conditions for 2 weeks, constant dark (DD) conditions for 2–4 weeks, and again in 12 hr LD conditions. Period, amplitude, phase, and total activity counts were calculated. In the second shift from constant darkness to 12 hr LD conditions, the rate of entrainment to the new lighting system was also analyzed. We used the period length averaged over days 1–4, 3–7, 4–8, 7–11, and 8–12 was determined for each group. Data was analyzed using Clocklab software.

Ex vivo bioluminescence recording from lung explants

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Lungs from Per2luc mice were harvested following perfusion to flush out blood cells. Thereafter, peripheral sections were obtained, and explants were placed in media containing luciferin. Bioluminescence recording was initiated, and data was recorded for 5–6 days. Data was analyzed using Clocklab software.

Statistical analyses

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Sample size analyses was performed using PS Sample size calculator. For survival experiments, sample size of 15 was calculated for median survival times (5 in ZT11 and 28 in ZT23, although the experiments were often plotted for 14 days) and an alpha of 0.05 with 90% power, matching 1:1 for control to case. Data was platted and analyzed using Graphpad Prism Software. Graphs represent data as means ± SEM or median ± IQR as applicable. Based on the distribution of data, either parametric (Student’s t-test or two-way ANOVA based on number or type of comparison groups) or non-parametric (Mann–Whitney or Kruskal–Wallis test) was used. Mortality data was analyzed using Mantel–Cox test. Tukey corrections were used for multiple comparisons.

Statement on rigor and reproducibility

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All studies were performed using animals from either Jackson Labs and animals from in-house breeding. The background strain of each genetically modified animal has been specified, and controls were cre− littermates on that same background. Reported findings are summarized results from 3 to 6 independent experiments.

Approval

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All studies involving IAV infection were carried out in biosafety level 2 (BSL2 and ABSL2) conditions and approved facility. Animals were provided with food and water ad libitum. All procedures and studies were performed by experienced personnel with appropriate supervision from veterinary support staff. All animal studies were approved by the University of Pennsylvania animal care and use Committee (protocol ID # 805645) and met the stipulations of the Guidelines for the Care and Use of Laboratory Animals.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for all figures.

References

    1. Jobe AH
    2. Bancalari E
    (2001) Bronchopulmonary dysplasia
    American Journal of Respiratory and Critical Care Medicine 163:1723–1729.
    https://doi.org/10.1164/ajrccm.163.7.2011060

Decision letter

  1. Miles P Davenport
    Senior Editor; University of New South Wales, Australia
  2. Jane A McKeating
    Reviewing Editor

In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.

Acceptance summary:

Your study shows a clear role for neonatal hyperoxia to perturb circadian pathways that regulate respiratory responses to influenza infection that is likely to have wide-ranging effects for other respiratory pathogens.

Decision letter after peer review:

Thank you for submitting your article "Loss of circadian Protection against Influenza Infection in Adults Exposed to Hyperoxia as neonates" for consideration by eLife. Your article has been reviewed by two peer reviewers, one of whom is a member of our Board of Reviewing Editors, and the evaluation has been overseen by Miles Davenport as the Senior Editor. The reviewers have opted to remain anonymous.

The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, when editors judge that a submitted work as a whole belongs in eLife but that some conclusions require a modest amount of additional new data, as they do with your paper, we are asking that the manuscript be revised to either limit claims to those supported by data in hand, or to explicitly state that the relevant conclusions require additional supporting data.

Essential revisions:

1) Edit paper to address reviewer #1 points 1-3 and 5-8 listed below to increase the readability of the for a broad readership.

2) To edit the paper to suggest a mechanism for the proposed effects of hyperoxia on circadian signalling pathways in the lung and impact of other respiratory pathogens. The authors should cite a recent BioRixv pre-print: Yee et al., 2020.

3) To provide the following additional data sets to strengthen their overall conclusions:

– Provide additional viral replication parameters beyond PCR enumeration of influenza viral RNA such as measuring viral infectivity or viral antigen immunostaining in the lung

– Include data to validate Bmal1 gene KO in AT2 cells – such as protein staining in the KO cells.

– Address stage specificity of hyperoxia on circadian gene expression

Reviewer #1:

Issah and colleagues show that neonatal hyperoxia perturbs circadian protection from influenza infection in a mouse model that is phenocopied by a genetic deletion of Bmal1 in alveolar type 2 (AT2) epithelial cells. These elegant experiments provide a mechanism for why neonatal hyperoxia associates with increased susceptibility to influenza associated disease in adult life. The manuscript is well written and overall the experimental data support the stated conclusions, however, both the text and figure legends are brief and further information would increase the readability of the paper. Encourage the authors to discuss the translational impact of their results for treating IAV infection and other viruses that infect the respiratory tract such as SARS-CoV-2.

1) The brevity of the manuscript text may reflect the authors drafting of the paper for a general audience, resulting in text that could be read as “superficial” by chronobiologists or viral immunologists. For example: “The mechanism involves both the pulmonary epithelium and the immune system.” “Changes in oxygen tension are known to affect the clock as well as the interplay between the SCN and peripheral clocks.” I would encourage the authors to expand and provide mechanistic data for some these statements.

2) Current Figure 1 and Figure 2 could be combined into a single figure.

3) Figure 3B – can the authors provide more details on what this figure shows bearing in the mind the general readership of the journal.

4) Figure 4B. The authors should provide more detail on how they measure viral burden and why these time points were selected. Have they evaluated infectious virus levels rather than simple PCR quantification of IAV RNA. This is the one area of the study that I felt was over-interpreted and further data could substantiate their conclusions. The colors used for the bar charts in this figure are not easy to discern – similar criticism of Figure 4D. Suggest the authors recolor the figures and provide an overlay of all data points.

5) Figure 4C – it is not clear what the data points in the histological scoring represent and why they differ between ZT11 and ZT23.

6) Figure 5A was poorly described with limited stat analysis and very low resolution figures. The accompanying text states: “the cycling of Cry1 and Clock was slightly increased” is not appropriate and the authors should address this figure.

7) Figure 6 – revise choice of colors and symbols to help clarify these figures.

8) Figure 7A – provide an overlay of data symbols for all bar charts.

Reviewer #3:

This well-written manuscript by Issah et al. identifies a new potential mechanism by which injury in early life may contribute to lung disease in adulthood. Using a previously established influenza infection model and AT2-cell specific CRE knockout of clock gene Bmal1, the authors show evidence that saccular stage hyperoxia injury disrupts the lung cellular clocks, resulting in a loss of the protective mechanism from influenza injury later in life. While the manuscript is clearly written and the proposed mechanism is novel, there are a few additional experiments necessary to strengthen the findings of this paper:

1) All of the data shown for Bmal expression after injury is at the level of RNA by qPCR. If possible, showing AT2-specific loss of Bmal by RNA in situ hybridization or at the protein level by immunofluorescence (with AT2 co-localization) would be very helpful.

2) Is the effect of hyperoxia on clock gene expression stage specific? Data are shown for neonatal/saccular stage injury--what happens to the lung cellular clocks of mice exposed to hyperoxia after P5 or in adulthood? These are important controls to consider.

3) It would be helpful for the authors to propose a mechanism in the Discussion whereby hyperoxia leads to cellular clock disruption and to link this proposed mechanism to other relevant papers discussing aspects of the molecular mechanisms of saccular stage hyperoxia injury.

https://doi.org/10.7554/eLife.61241.sa1

Author response

Essential revisions:

1) Edit paper to address reviewer# 1 points 1-3 and 5-8 listed below to increase the readability of the for a broad readership.

We have addressed the points below.

2) To edit the paper to suggest a mechanism for the proposed effects of hyperoxia on circadian signalling pathways in the lung and impact of other respiratory pathogens. The authors should cite a recent BioRixv pre-print: Yee et al., 2020.

Thank you for drawing our attention to this report. The preprint is now published in Scientific reports and we have included this reference in our manuscript.

3) To provide the following additional data sets to strengthen their overall conclusions:

– Provide additional viral replication parameters beyond PCR enumeration of influenza viral RNA such as measuring viral infectivity or viral antigen immunostaining in the lung

We have processed the samples for hemagglutination inhibition assay for both the hyperoxia cohort as well as the AT2 Bmal1KO animals.

– Include data to validate Bmal1 gene KO in AT2 cells – such as protein staining in the KO cells.

We have included IF-staining with Bmal1 and AT2 marker, Pro-SPC in lung sections (in Figure 5—figure supplement 1).

– Address stage specificity of hyperoxia on circadian gene expression

We have included data for adults exposed to hyperoxia and infected with influenza virus, after a period of recovery. (Figure 1D and E).

Reviewer #1:

Issah and colleagues show that neonatal hyperoxia perturbs circadian protection from influenza infection in a mouse model that is phenocopied by a genetic deletion of Bmal1 in alveolar type 2 (AT2) epithelial cells. These elegant experiments provide a mechanism for why neonatal hyperoxia associates with increased susceptibility to influenza associated disease in adult life. The manuscript is well written and overall the experimental data support the stated conclusions, however, both the text and figure legends are brief and further information would increase the readability of the paper. Encourage the authors to discuss the translational impact of their results for treating IAV infection and other viruses that infect the respiratory tract such as SARS-CoV-2.

1) The brevity of the manuscript text may reflect the authors drafting of the paper for a general audience, resulting in text that could be read as “superficial” by chronobiologists or viral immunologists. For example: “The mechanism involves both the pulmonary epithelium and the immune system.” “Changes in oxygen tension are known to affect the clock as well as the interplay between the SCN and peripheral clocks.” I would encourage the authors to expand and provide mechanistic data for some these statements.

We thank the reviewer for this insight and have accordingly expanded the sections as recommended in not only the above two instances but others where the critique would be relevant.

Upon further review, the comment on epithelium and immune cells did not seem to be pertinent here, so have deleted that reference altogether.

Revised as below:

“Changes in oxygen tension are known to affect the clock (Walton et al., 2018; Wu et al., 2017). […] More recently, even a short burst of hypoxia was shown to desynchronize the relationship between the SCN and peripheral clocks (Manella et al., 2020), which would confer further risk under conditions of stress.”

2) Current Figure 1 and Figure 2 could be combined into a single figure.

Done.

3) Figure 3B – can the authors provide more details on what this figure shows bearing in the mind the general readership of the journal.

We have clarified the same in both the Materials and methods section and the legends that accompany the figure. Revised section as below:

Main text: “To address the hypothesis that neonatal hyperoxia caused instability of circadian regulation, we examined the ability of the animals to re-entrain to 12hr light-dark cycles after several weeks in constant darkness. […] Normoxia and hyperoxia groups did not entrain differently to this small change [Figure 2B and C]”.

Materials and methods: “Mice were singly housed in circadian light control boxes (Actimetrics) to measure their locomotor or rest-activity rhythms using either running wheels or Infrared Motion Sensors (Actimetrics). […] Data was analyzed using Clocklab software.”

Legends for new “Figure 2B” (was earlier Figure 3B): “Representative actigraph images taken from adult mice exposed to either neonatal hyperoxia and room air. […] The black bars represent the number of turns of the running wheel/movement sensed by the infrared motion sensors and indicates a time when the mouse of active.”

4) Figure 4B. The authors should provide more detail on how they measure viral burden and why these time points were selected. Have they evaluated infectious virus levels rather than simple PCR quantification of IAV RNA. This is the one area of the study that I felt was over-interpreted and further data could substantiate their conclusions. The colors used for the bar charts in this figure are not easy to discern – similar criticism of Figure 4D. Suggest the authors recolor the figures and provide an overlay of all data points.

We thank the reviewer for this comment. We have expanded our dataset for both eth hyperoxia and the Sftpc cohorts. For hyperoxia animals we now have days 1, 3, 5 and 8 and for the Sftpc-cre we have days 1, 5 and 8. Our aims was to capture the early replication and clearance trajectory following IAV infection. Further, we have expanded our viral burden determination from qPCR to include the hemagglutination inhibition assay. We have included the results from Hemagglutination inhibition assay for the hyperoxia and the SPC-cre animals. We are glad to note that overall, the conclusion of the two methods of viral burden determination are the same. Time of day at infection doesn’t impact viral replication/burden in room air or neonatal hyperoxia exposed animals or for the Sftpc status.

Figure 4D: We have also changed the color scheme of the figure and overlaid the individual data points on top of the summary stats.

5) Figure 4C – it is not clear what the data points in the histological scoring represent and why they differ between ZT11 and ZT23.

To clarify this response we have included the scoring scheme as a table in the source data (Figure 3—source data 2) and expanded on the same in the text. The data points in the histological scoring is the summary from these measurements. Revised as:

“Next, we quantified lung injury on histological analyses using a previously validated scoring system(Sengupta et al., 2019). […] On histological analyses, animals infected in the hyperoxia group scored worse for lung injury and the time of day difference in severity was absent [Figure 3C].”

6) Figure 5A was poorly described with limited stat analysis and very low resolution figures. The accompanying text states: “the cycling of Cry1 and Clock was slightly increased” is not appropriate and the authors should address this figure.

We have revised the Materials and methods and the Results section pertaining to this experiment, as recommended by the reviewer. Further, we have also revised the figures with better resolution and overall clarity. Revised text as:

“On visual inspection, subtle differences in the phase of the oscillation of core clock genes Bmal1, Per2 and Nr1d2 were noted as a consequence of neonatal hyperoxia, but none of these changes were statistically significant [Figure 4A].”

7) Figure 6 – revise choice of colors and symbols to help clarify these figures.

We have updated the colors and legends.

8) Figure 7A – provide an overlay of data symbols for all bar charts.

Done.

Reviewer #3:

This well-written manuscript by Issah et al. identifies a new potential mechanism by which injury in early life may contribute to lung disease in adulthood. Using a previously established influenza infection model and AT2-cell specific CRE knockout of clock gene Bmal1, the authors show evidence that saccular stage hyperoxia injury disrupts the lung cellular clocks, resulting in a loss of the protective mechanism from influenza injury later in life. While the manuscript is clearly written and the proposed mechanism is novel, there are a few additional experiments necessary to strengthen the findings of this paper:

1) All of the data shown for Bmal expression after injury is at the level of RNA by qPCR. If possible, showing AT2-specific loss of Bmal by RNA in situ hybridization or at the protein level by immunofluorescence (with AT2 co-localization) would be very helpful.

We have performed immunofluorescence with Bmal1 and Pro-SPC on lung sections from Sftpc-cre+Bmal1fl/fl as well as Sfptc-cre+Bmal1+/+ littermates--results confirming an AT2 specific Bmal1 deletion in the former and are included as Figure 5—figure supplement 1.

2) Is the effect of hyperoxia on clock gene expression stage specific? Data are shown for neonatal/saccular stage injury--what happens to the lung cellular clocks of mice exposed to hyperoxia after P5 or in adulthood? These are important controls to consider.

We thank the reviewer for this fascinating line of inquiry. We have likewise repeated the hyperoxia exposure in adults followed by IAV infection after a recovery period of 3-4 weeks. It appears that the effect of hyperoxia on the circadian control of IAV induced outcomes is specific to the saccular stage. The experimental scheme is detailed in Figure 1—figure supplement 1 and the results in Figure 1D and E.

3) It would be helpful for the authors to propose a mechanism in the Discussion whereby hyperoxia leads to cellular clock disruption and to link this proposed mechanism to other relevant papers discussing aspects of the molecular mechanisms of saccular stage hyperoxia injury.

We have included an entire section discussing the possible interconnections as proposed by the reviewers. Revised section as below:

“Our work further strengthens the observation in the field that oxygen tension modulates the circadian clock. […] However, since there is not a single regulatory node for hyperoxia unlike the hypoxia-HIF1α axis, it is hard to speculate which specific pathway would play this role.”

https://doi.org/10.7554/eLife.61241.sa2

Article and author information

Author details

  1. Yasmine Issah

    The Children’s Hospital of Philadelphia, Philadelphia, United States
    Contribution
    Formal analysis, Investigation, Methodology, Writing - original draft
    Contributed equally with
    Amruta Naik
    Competing interests
    No competing interests declared

  2. Amruta Naik

    The Children’s Hospital of Philadelphia, Philadelphia, United States
    Contribution
    Investigation, Methodology, Project administration, Writing - review and editing
    Contributed equally with
    Yasmine Issah
    Competing interests
    No competing interests declared

  3. Soon Y Tang

    Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, Philadelphia, United States
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  4. Kaitlyn Forrest

    The Children’s Hospital of Philadelphia, Philadelphia, United States
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  5. Thomas G Brooks

    Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, Philadelphia, United States
    Contribution
    Formal analysis, Writing - review and editing
    Competing interests
    No competing interests declared

  6. Nicholas Lahens

    Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, Philadelphia, United States
    Contribution
    Formal analysis, Visualization
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3965-5624

  7. Katherine N Theken

    1. Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, Philadelphia, United States
    2. Systems Pharmacology University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
    Contribution
    Conceptualization, Writing - review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9918-9170

  8. Mara Mermigos

    The Children’s Hospital of Philadelphia, Philadelphia, United States
    Contribution
    Investigation, Methodology
    Competing interests
    No competing interests declared

  9. Amita Sehgal

    1. Chronobiology and Sleep Institute, University of Pennsylvania, Philadelphia, United States
    2. Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
    Contribution
    Conceptualization, Resources, Visualization, Writing - review and editing
    Competing interests
    Reviewing editor, eLife

  10. George S Worthen

    1. The Children’s Hospital of Philadelphia, Philadelphia, United States
    2. Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
    Contribution
    Conceptualization, Visualization, Writing - review and editing
    Competing interests
    No competing interests declared

  11. Garret A FitzGerald

    1. Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, Philadelphia, United States
    2. Systems Pharmacology University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
    3. Chronobiology and Sleep Institute, University of Pennsylvania, Philadelphia, United States
    Contribution
    Conceptualization, Resources, Software, Funding acquisition, Writing - review and editing
    Competing interests
    No competing interests declared

  12. Shaon Sengupta

    1. The Children’s Hospital of Philadelphia, Philadelphia, United States
    2. Institute of Translational Medicine and Therapeutics (ITMAT), University of Pennsylvania, Philadelphia, United States
    3. Chronobiology and Sleep Institute, University of Pennsylvania, Philadelphia, United States
    4. Department of Pediatrics, University of Pennsylvania Perelman School of Medicine, Philadelphia, United States
    Contribution
    Conceptualization, Resources, Data curation, Supervision, Funding acquisition, Validation, Investigation, Visualization, Methodology, Project administration, Writing - review and editing
    For correspondence
    SenguptaS@email.chop.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5237-3835

Funding

National Heart, Lung, and Blood Institute (K08HL132053)

  • Shaon Sengupta

National Institute of Child Health and Human Development (K12HD043245)

  • Shaon Sengupta

National Center for Research Resources (RR023567)

  • Garret A FitzGerald

Howard Hughes Medical Institute

  • Amita Sehgal

National Center for Advancing Translational Sciences (5T32MH106442-04)

  • Thomas G Brooks

National Center for Advancing Translational Sciences (NCATS-5UL1TR000003)

  • Thomas G Brooks

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We are thankful to members of the FitzGerald lab – Dr. S Teegarden for help with animal breeding and general lab management; Dr. G Grant for his comments and discussions at lab meetings. This work was supported by the NHLBI-K08HL132053 (SS), NICHD-K12HD043245 (SS), a Maturational Human Biology grant from the Institute of Translational Medicine and Therapeutics, University of Pennsylvania (SS), and NIH/NCRR RR023567 (GAF). Dr. FitzGerald is the McNeil Professor of Translational Medicine and Therapeutics and a senior advisor to Calico Laboratories. We are also thankful to Dr. Carolina B Lopez for her advice regarding viral stock generation and viral titration.

Ethics

Animal experimentation: All animal studies were approved by the University of Pennsylvania Animal Care and Use Committee and adhered strictly of the Guide for the care and Use of Laboratory animals. No survival surgeries were involved. Any potential pain and suffering was minimized by using a priori generated and validated guidelines (protocol ID # 805645).

Senior Editor

  1. Miles P Davenport, University of New South Wales, Australia

Reviewing Editor

  1. Jane A McKeating

Version history

  1. Received: July 20, 2020
  2. Accepted: February 14, 2021
  3. Version of Record published: March 2, 2021 (version 1)

Copyright

© 2021, Issah et al.

This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

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  1. Yasmine Issah
  2. Amruta Naik
  3. Soon Y Tang
  4. Kaitlyn Forrest
  5. Thomas G Brooks
  6. Nicholas Lahens
  7. Katherine N Theken
  8. Mara Mermigos
  9. Amita Sehgal
  10. George S Worthen
  11. Garret A FitzGerald
  12. Shaon Sengupta
(2021)
Loss of circadian protection against influenza infection in adult mice exposed to hyperoxia as neonates
eLife 10:e61241.
https://doi.org/10.7554/eLife.61241

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