The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study

Bala S. C. Koritala; Panshak P. Dakup; Kenneth I. Porter; Shobhan Gaddameedhi

doi:10.12688/f1000research.136998.2

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Research Article

Revised

The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study

[version 2; peer review: 2 approved]

Bala S. C. Koritala^1-3^*, Panshak P. Dakup^3,4^*, Kenneth I. Porter³, Shobhan Gaddameedhi ^4,5

^* Equal contributors

PUBLISHED 02 Aug 2023

Author details Author details

¹ Department of Otolaryngology-Head and Neck Surgery, University of Cincinnati, Cincinnati, Ohio, USA
² Division of Pediatric Otolaryngology-Head and Neck Surgery, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA
³ Department of Pharmaceutical Sciences, Washington State University, Spokane, Washington, USA
⁴ Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, USA
⁵ Center for Human Health and the Environment, North Carolina State University, Raleigh, North Carolina, USA

Bala S. C. Koritala
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – Original Draft Preparation, Writing – Review & Editing

Panshak P. Dakup
Roles: Conceptualization, Investigation, Methodology, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Kenneth I. Porter
Roles: Investigation, Methodology, Resources, Validation, Writing – Review & Editing

Shobhan Gaddameedhi
Roles: Conceptualization, Data Curation, Funding Acquisition, Methodology, Project Administration, Resources, Supervision, Validation, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

This article is included in the Cell & Molecular Biology gateway.

This article is included in the Circadian Clocks in Health and Disease collection.

Abstract

Background: The natural day-night cycle synchronizes our circadian rhythms, but modern work practices like night shifts disrupt this pattern, leading to increased exposure to nighttime light. This exposure is linked to various health issues. While some studies have explored the effects of night shifts on human circadian rhythms, there is limited research on the consequences of long-term exposure to shift-work light conditions. Rodents can provide valuable insights into these effects. This study aimed to examine how short- or long-term exposure to rotating shifts and chronic jetlag affects the core circadian oscillators in the liver and skin of mammals.

Methods: C57BL/6J male mice were subjected to simulated shift-work light conditions, including short-term or long-term rotating shifts and chronic jet-lag conditions. Liver and skin samples were collected every four hours over a 24-hour period on the second day of constant darkness. RNA was extracted and qRT-PCR analysis was conducted to measure the circadian gene expression in liver and skin tissues. Circadian rhythm analysis using CircaCompare compared the control group to mice exposed to shift-work light conditions.

Results: The liver's circadian clock is significantly altered in mice under long-term rotating shift conditions, with a lesser but still noticeable impact in mice experiencing chronic jetlag. However, short-term rotating shift conditions do not significantly affect the liver's circadian clock. Conversely, all three simulated shift conditions affect the skin's circadian clock, indicating that the skin clock is more sensitive to shift-work light conditions than the liver clock. Compared to the liver, the skin's circadian clock is greatly affected by long-term rotating shift conditions.

Conclusions: The study findings indicate more pronounced disturbances in the canonical clock genes of the skin compared to the liver under simulated shift-work light conditions. These results suggest that the skin clock is more vulnerable to the effects of shift-work.

Keywords

Canonical clock genes, mouse, rotating shift, jet-lag, liver, skin.

Corresponding author: Shobhan Gaddameedhi

Competing interests: No competing interests were disclosed.

Grant information: This work was supported by the National Institutes of Health grant R01ES030113 (S.G.).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2023 Koritala BSC et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Koritala BSC, Dakup PP, Porter KI and Gaddameedhi S. The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study [version 2; peer review: 2 approved]. F1000Research 2023, 12:762 (https://doi.org/10.12688/f1000research.136998.2) First published: 28 Jun 2023, 12:762 (https://doi.org/10.12688/f1000research.136998.1) Latest published: 17 Aug 2023, 12:762 (https://doi.org/10.12688/f1000research.136998.3)

Revised Amendments from Version 1

We have refined the article by integrating reviewer suggestions into the methods and discussion sections. This includes the addition of details regarding the procedure for skin tissue collection, an explanation of the CircaCompare R package used for circadian analysis, and an interpretation of cry gene alterations under simulated shift conditions.

See the authors' detailed response to the review by Brian J. Altman
See the authors' detailed response to the review by Tianpeng Zhang

Introduction

The natural day-night cycle is the primary synchronizer of circadian rhythms in humans.¹ The advent of electricity has led to 24/7 work practices including night shift and rotating shift schedules, increasing nighttime light exposure in modern society. Unfortunately, these modern work habits have been associated with an elevated risk of various health conditions, including cancer, cardiovascular diseases, depression, diabetes, gastrointestinal problems, and metabolic syndrome.²^–⁵ The disruption of circadian rhythms, both at the physiological and behavioral level, contributes to these modern work habit-associated health conditions. The few studies investigating the impact of night shift on the molecular circadian rhythms in humans have revealed significant changes in the circadian transcriptome and metabolome within a one-week study duration.⁶^–⁸ However, in real-world scenarios, many shift workers experience prolonged exposure to rotating shifts that extend beyond a single week. Unfortunately, there is a lack of systematic research investigating the consequences of long-term exposure to shift-work light conditions on molecular circadian rhythms in humans. This absence may be attributed to logistical, financial, and facility constraints in setting up human sleep laboratories. Nonetheless, rodents can serve as valuable preliminary models for understanding the effects of different shift schedules or exposure to shift-work light conditions on molecular circadian rhythms, providing insights into the underlying molecular mechanisms associated with shift-work related disorders.⁹

In laboratory settings, researchers can replicate shift-work-like light environments using rotating shift and jet-lag protocols in rodents. Several studies¹⁰^–¹⁴ have employed these protocols in rodents to investigate the mechanisms underlying tumor development, metabolic disorders, and other health outcomes associated with shift work. These studies have indicated that exposure to shift-work or jet-lag light environments can promote tumor progression,¹⁰^,¹²^,¹⁵^–¹⁸ glucose intolerance,¹⁹^,²⁰ obesity,¹⁹^,²¹ genotoxic stress mediated cardiovascular toxicity,²² and radiodermatitis.²³ Although some research has shown abnormal activity/sleep rhythms in response to shift conditions,¹¹ our understanding of how short- or long-term exposure to shift-work and chronic jet-lag conditions affects the mammalian core circadian oscillator, the canonical clock genes, remains limited. Rodents serve as a convenient model for studying tissue-specific circadian gene expression of these clock genes. Therefore, in this study, we utilized a well characterized circadian mouse model, C57BL/6J,²⁴ to investigate the impact of short- or long-term exposure to rotating shifts and jet-lag conditions on the mammalian core oscillators in various tissues.

The primary focus of our study was to examine the effects of shift-work-like light conditions on the liver and skin. We specifically chose the liver because it is widely recognized as the primary organ model for studying the circadian clock in peripheral tissues.²⁵ The liver plays a crucial role in carrying out various metabolic functions regulated by the circadian clock through transcriptional and posttranslational mechanisms.²⁶^–²⁸ On the other hand, although the skin is not as metabolically active as the liver, it serves as accessible window for understanding the body’s internal clock in humans.²⁹^,³⁰ Moreover, a study has shown that restricted feeding altered the phase and amplitude of clock genes in mouse skin, subsequently affecting the skin’s response to ultraviolet radiation exposure.³¹ Given these factors, the liver and skin represent distinct metabolic tissue models with robust circadian clocks, offering valuable insights into circadian rhythm disturbances caused by shift work.

Our study employed a comprehensive design that enabled us to investigate the tissue-specific disturbances in circadian rhythms resulting from simulated short- or long-term exposure to rotating shifts and chronic jet-lag conditions. After subjecting C57BL/6J mice to simulated shift-work light conditions, we measured the circadian gene expression of canonical clock genes (Arntl, Npas2, Per1, Per2, Per3, Cry1, Cry2, and Dbp) in liver and skin samples. The measurements were taken over a 24-hour period on the second day of constant darkness (Figure 1). Our findings indicate more pronounced disturbances in the canonical clock genes of the skin compared to the liver under simulated shift-work light conditions. Notably, long-term rotating shift work significantly impacted the expression of these canonical clock genes in both tissues. Based on our observations, it is evident that the skin clock is more vulnerable to the effects of shift-work light conditions when compared to the liver clock.

Figure 1. Design of simulated shift-work light conditions for mice.

Panels from left to right represent simulated light conditions of control (left), short- and long-term rotating shifts (middle), and chronic jet-lag (right). After exposure to simulated shift conditions of light (yellow) and dark (Gray), liver and skin samples were collected for 24 hours with four-hour intervals on the second day of constant dark condition. 0^th time was defined as the onset of the light phase before the animals entered constant darkness for tissue collection.

Methods

Ethics statement

The mice utilized in this study were procured from The Jackson Laboratory and housed in the Program of Laboratory Animal Resources (PLAR) of Washington State University - Spokane. To guarantee proper animal welfare, the guidelines set by the Institutional Animal Care and Use Committee (IACUC) were followed. Our program compiles with all regulations outlined in the NIH guide for the Care and Use of Laboratory Animals, encompassing procurement, conditioning and quarantine, housing, management, veterinary care, and carcass disposal. All efforts were made to ameliorate the suffering of the mice involved. There were no adverse events during the study and no humane endpoints were established. The animal experiments conducted in this study were approved by the IACUC under the protocol number: 6202 on March 27^th, 2019.

Study design and sample collection

This investigation took place from May through September 2019. Healthy immunocompetent wild-type C57BL/6J male mice at 3 weeks of age were purchased from the Jackson Laboratory (strain #: 000664). Mice were purchased to limit variability and maintain consistency in the genetic quality of the animals. Upon arrival, these mice were acclimatized to the controlled environment of the PLAR facility at Washington State University – Spokane for at least one week. The only inclusion criterion was for animals to be at least 4 weeks of age by day 1. To investigate the impact of shift-work light conditions on circadian rhythms of canonical clock genes, a group of C57BL/6J male mice were randomly assigned and housed (3 mice per cage) in a controlled environment that simulated shift-work light conditions. The mice were subjected to different simulated conditions: either short-term (15 days) or long-term (45 days) rotating shifts, where the light conditions changed every seventh day, or a jet-lag condition lasting 21 days with an 8-hour phase advance every two days. As a comparison, a control group of mice followed the standard light-dark cycle of the facility (Figure 1). A total of 72 mice were included in this study, to cover 24 timepoints across 4 light conditions. An n = 3 was chosen per time point as the minimum number required to identify statistical differences per time-point, which translates to n = 18 per experimental condition for circadian analyses. Following exposure to simulated light conditions with an intensity of ~590 lux, the mice were housed in constant dark for up to 48 hours. On the second day, mice were sacrificed at the age of 11 to 12 weeks old, and samples of liver and skin tissues were collected from three mice at each time point over a 24-hour period, with four-hour intervals (Figure 1). Specifically, whole skin tissue was collected from dorsal lateral side of the mouse following post-cervical dislocation, placed on fixed card stock, covered with foil, snap-frozen, and stored at -80 °C for RNA extraction. To manipulate the light conditions, the mice were housed in light-tight circadian chambers provided by Phenome Technologies, Inc. The light schedules were regulated by an external timer (XT-4, Chrontrol Corporation), and the light status and intensity were monitored using HOBO data loggers (UA-002-08, Onset Computer Corporation). All mice, regardless of the light conditions or constant darkness, were given ad libitum feeding. Throughout the time-course sample collection, red light was utilized, and animals were killed per housed group, where one cage of 3 mice represented one time-point. This was done to limit variability in any time-point. Mice were anesthetized with 3-4% isoflurane and euthanized by cardiac puncture blood collection followed by cervical dislocation as a secondary method of euthanasia. The collected liver and skin tissues were snap-frozen and stored at -80 °C for subsequent RNA extraction.

Gene expression analysis

Frozen liver and skin tissues were homogenized in liquid nitrogen using mortar and pestle. Next, we purified the total RNA from the homogenized tissues using a Trizol-based RNA extraction protocol. Approximately 100 mg of the ground tissue was combined with 1 ml of ice-cold TRIzol reagent (Thermo Fisher Scientific, #15596018). After thorough mixing, 0.2 ml of chloroform was added to the TRIzol tissue cocktail, mixed well, and incubated at room temperature for 3 mins. We separated the different phases of the mixture through centrifugation at 12,000 g for 15 mins. The aqueous phase (top layer) was carefully collected and transferred to a new tube. To precipitate the RNA, an equal volume of isopropanol was added to the collected aqueous phase and mixed by inverting. After a 10-minute incubation at room temperature, the samples were subjected to another round of centrifugation at 12,000 g for 10 minutes. The supernatant was discarded, and the RNA pellet was washed three times with 70% ice-cold ethanol. Subsequently, the RNA pellet was air dried for 5-10 mins and dissolved in 20 μl of ddH₂O. To assess the quantity and quality of the extracted RNA, we utilized NanoDrop^® 2000 Spectrophotometer, measuring the light absorbance at 260, 280 and 230 nm. Following the RNA purification step, we treated the RNA samples with DNase-I (New England Biolabs, #M0303S), and synthesized complementary DNA (cDNA) using TaqMan™ Reverse Transcription Reagents (Thermo Fisher Scientific, #N8080234). Real-time polymerase chain reaction (RT-PCR) was then performed using PerfeCTa^® SYBR^® Green Supermix with ROX™ (Quantabio, #95055-500) in a StepOnePlus™ Real-Time PCR System (Applied Biosystems™). The RT-PCR reaction included denaturation (3 minutes at 95 °C) and 40 PCR cycles (15 sec at 95 °C and 1 minute at 60 °C). The expression level of each clock gene was normalized to the geometric mean expression of two housekeeping genes,³² Actb and Ppib using the ΔCt method. Subsequently, the data were scaled to the sample with the highest expression level (ΔΔCt) for the time course analysis. Missing values in the raw data files resulting from technical issues with the qPCR plate were excluded from analysis. We specifically measured the expression of canonical clock genes (Arntl, Npas2, Per1, Per2, Per3, Cry1, Cry2, and Dbp) in both liver and skin tissues using validated primers. To ensure the accuracy of the PCR amplification, the primers were validated using cDNA template serial dilution, and their efficiency was calculated based on the slope value³³ (Table 1). The primer design for this study was performed using Primer3 (v.0.4.0), a widely used primer design tool.

Table 1. Primers used for measuring mRNA expression of canonical clock genes.

Gene	Forward Primer (5′ to 3′)	Reverse Primer (3′ to 5′)
Arntl	CTCAACCATCAGCGACTTCA	CCTTCCTTGGTGTTCTGCAT
Npas2	CCTAGCCCCTCCTGTAATGG	AGGTTCGTCAGCTACACACA
Per1	CCAGGATGTGGGTGTCTTCT	GACCCGAATCTTGGTCACAT
Per2	TGGTTTCTGGGAAGATCCTG	AGCTGTGGAACACACTGACG
Per3	CACCCTCCGTTTGAACACTC	GGCTCCAGGGGTTGACAAA
Cry1	CAGATCCCTTGGGACAAGAA	TGAGTCATGATGGCGTCAAT
Cry2	GGTGACCCGTTTGACCTTTG	TTCTCAGTCACCACCTCCAC
Dbp	GCAGGCTTGACATCTAGGGA	CTCATGGCCTGGAATGCTTG
Actb	CATTGCTGACAGGATGCAGAAGG	TGCTGGAAGGTGGACAGTGAGG
Ppib⁵²	GGAGATGGCACAGGAGGAAA	CCGTAGTGCTTCAGTTTGAAGTTCT

Circadian rhythm analysis

To analyze the differences in circadian rhythms of canonical clock genes in animals exposed to both control and simulated shift-work light conditions, we utilized the standard parameters of the CircaCompare R package with a 24 hour fixed period.³⁴ Circadian time, CT0 was defined as the onset of the light phase before the animals entered constant darkness for tissue collection. This alignment allowed us to effectively compare and assess the variations in circadian rhythms between control and simulated shift-work light conditions. We applied a p-value cut-off of <0.05 to determine the presence or absence of rhythms and to evaluate significant differences in phase, amplitude, and the Midline Estimating Statistic of Rhythm (MESOR). Sample resolution is a critical factor in circadian analysis as it directly affects the precision of phase estimates.³⁵ In our study, we used four-hour sample resolution, therein phase differences were only considered if they were at least four hours apart. This approach was implemented to ensure the accuracy of our results.

Results

Circadian analysis of canonical clock genes in the liver after exposure to simulated shift- work light conditions

To investigate the impact of shift-work light conditions on the liver clock, we examined the circadian rhythms of canonical clock genes (Arntl, Npas2, Per1, Per2, Per3, Cry1, Cry2, and Dbp) in the liver samples of mice exposed to simulated shift-work light conditions. Rhythmic gene expression and its significance was determined at p < 0.05 of CircaCompare. Our findings revealed significant rhythmic patterns in all analyzed clock genes, both in the control group and in the mice exposed to the simulated shift-work light conditions. However, Cry1 did not show significant rhythmicity in the long-term rotating shift scenario and Cry2 did not exhibit significant rhythmicity in the chronic jet-lag scenario (Figure 2, Extended Data Table 1⁵⁴). This suggests that these genes may be more sensitive to prolonged disruption of light-dark cycles. Furthermore, we examined various circadian properties such as phase, amplitude, and MESOR and compared differences between conditions (Figures 2 and 4A, Extended Data Table 1⁵⁴). In the short-term rotating shift and chronic jet-lag scenarios, we did not observe any discernible phase differences compared to the control condition. However, in the long-term rotating shift scenario, significant phase advance of at least four hours were detected in five out of eight clock genes: Npas2, Per1, Per2, Per3, and Cry2. Regarding amplitude, we did not find significant differences in the rotating shift conditions. However, we did observe a significant decrease in amplitude of Per1 and Dbp among mice exposed to chronic jet-lag compared to the control group. This indicates that chronic disruption of light-dark cycles may affect the robustness of circadian rhythms in these genes. We did not find any significant changes in MESOR with short-term rotating shift. However, we observed a significant increase in MESOR with the genes Arntl, Per2, Per3, and Cry2 in the long-term rotating shift condition. Conversely, we found a significant decrease in MESOR with the genes Per1 and Dbp in the chronic jet-lag scenario. Overall, these results suggest that the circadian clock in the liver is highly impacted in mice exposed to the long-term rotating shift condition with a clear but less dramatic impact in mice exposed to chronic jet-lag. In contrast, we found no significant impact on the liver’s circadian clock in mice exposed to a short-term rotating shift condition.

Figure 2. Circadian rhythms of canonical clock genes in the liver following exposure to simulated shift-work light conditions.

The graphs display 24-hour expression (Mean ± SE) of Arntl, Npas2, Per1, Per2, Per3, Cry1, Cry2, and Dbp in the liver under constant dark after exposure to simulated shift-work light conditions. The figure allows for a comparison between the control group and three experimental conditions: short-term rotating shift (left), long-term rotating shift (middle), and control vs chronic jet-lag (right) were represented in the figure. To ensure accurate analysis, the mRNA expression throughout the time course was normalized against the geometric mean expression of housekeeping genes Actb and Ppib. The statistical significance of the circadian rhythms and the differences in circadian characteristics between the control group and the simulated shift-work conditions were assessed using CircaCompare, with a significance level set at p < 0.05. Genes that exhibit a significant rhythmic pattern are represented by continuous lines, while arrhythmic genes are represented by dotted lines.

Circadian analysis of canonical clock gene expression in the skin after exposure to simulated shift-work light conditions

In addition to studying the liver, we also examined the expression of canonical clock genes in the dorsal skin of mice (Figure 3, Extended Data Table 1⁵⁴) collected under constant darkness after being exposed to simulated shift-work light conditions. We analyzed the circadian rhythms and determined their significance using CircaCompare with a p < 0.05. Our analysis revealed that majority of the analyzed clock genes in the skin exhibited rhythmic patterns. However, we observed a loss of rhythmicity in Cry1 after exposure to short-term rotating shift and chronic jet-lag conditions. Additionally, Cry2 became arrhythmic when subjected to long-term rotating shift and chronic jet-lag conditions. Furthermore, we compared the circadian rhythms between the control group and the simulated shift-work groups, focusing on differences in phase (at least four hours), amplitude, and MESOR (Figure 4B, Extended Data Table 1⁵⁴). Out of the eight genes analyzed in the skin, significant phase differences were observed in two genes (Arntl and Cry2) following the short-term rotating shift condition. Four genes (Arntl, Per2, Per3, and Dbp) exhibited significant phase differences following the long-term rotating shift condition, and one gene (Arntl) showed a significant phase difference following chronic jet-lag. Notably, most of these genes displayed a phase advance following simulated shift-work conditions compared to the control group. Arntl consistently exhibited dysregulation across all simulated shift conditions, particularly showing a phase delay in the long-term rotating shift scenario. Moreover, we observed alterations in amplitude: Cry2 and Arntl exhibited reduced amplitude following short-term and long-term rotating shift conditions, respectively. Per2 displayed reduced amplitude in both rotating shift conditions, while no significant differences in amplitude were noted with chronic jet-lag. Regarding MESOR, two out of eight genes analyzed in each shift condition exhibited MESOR differences compared to the control group. Arntl displayed a significant increase in MESOR following exposure to short-term rotating shift and chronic jet-lag conditions, while Per1 showed a significant increase following long-term rotating shift and chronic jet-lag. Additionally, Cry2 and Per2 exhibited a significant decrease in MESOR following exposure to the short-term and long-term rotating shift conditions, respectively. Overall, these results indicate that the circadian clock in the skin is impacted by all three simulated shift conditions and suggest that the skin clock is more sensitive to shift-work light conditions compared to the liver clock. Similar to our observations in the liver, the circadian clock in the skin is highly impacted in mice exposed to long-term rotating shift conditions.

Figure 3. Circadian rhythms of canonical clock genes in the skin following exposure to simulated shift-work light conditions.

The graphs in the figure illustrate the 24-hour expression (Mean ± SE) of Arntl, Npas2, Per1, Per2, Per3, Cry1, Cry2, and Dbp in the skin under constant darkness following exposure to simulated shift-work light conditions. The figure enables a comparison between the control group and three experimental conditions: short-term rotating shift (left), long-term rotating shift (middle), and control vs chronic jet-lag (right) were represented in the figure. To ensure precise analysis, the mRNA expression throughout the entire time course was normalized against the geometric mean expression of housekeeping genes Actb and Ppib. The statistical significance of the circadian rhythms and the variations in circadian characteristics between the control group and the simulated shift-work conditions were evaluated using CircaCompare, with a significance level set at p < 0.05. In the figure, genes that exhibit a significant rhythmic pattern are depicted by continuous lines, while genes lack a rhythmic pattern are represented by dotted lines.

Figure 4. Differential circadian properties of canonical clock genes in the liver and skin following exposure to simulated shift-work light conditions.

The figure represents differences in phase (left), amplitude (middle), and MESOR (right) of canonical clock genes in the liver (top) and skin (bottom) of mice subjected to short-term, long-term rotating shift, and chronic jet-lag conditions, in comparison to a control condition. Significance testing was performed using CircaCompare with a threshold of p < 0.05, and the corresponding p-values can be found in Extended Data Table 1.⁵⁴

Discussion

Our study aimed to fill a significant knowledge gap regarding the effects of different durations and types of shift conditions on the circadian system. Shift-work has been hypothesized to disrupt the synchronization between the central and peripheral circadian machinery.³⁶ Previous studies in humans have only examined the impact of mistimed sleep on molecular rhythms for about a week,⁶^–⁸ limiting our understanding of the long-term consequences. We conducted a study using a well-established C57BL/6J mouse model to investigate the consequences of various durations and types of shift-work light conditions on the circadian system. By simulating shift-work light conditions, we were able to observe changes in the circadian expression of canonical clock genes in both the liver and the skin.

Light is widely recognized as the primary synchronizer for maintaining the mammalian circadian system. Two photoreceptors, melanopsin (OPN4) and neuropsin (OPN5), have been identified as mediators of light entrainment from the retinal ganglion cells to the suprachiasmatic nucleus (SCN),³⁷^,³⁸ which serves as the central pacemaker of the circadian system. Interestingly, recent studies have shown that OPN5 in murine melanocytes is involved in circadian photoentrainment and the expression of clock genes, a phenomenon not observed in the liver.³⁹ On the other hand, the liver, being a metabolically active organ, can directly entrain its clock through feeding-fasting cycles.⁴⁰^–⁴² Prior research has demonstrated this ability, indicating that the liver is more influenced by metabolic cues compared to the skin. Therefore, in the current study, we examined the impact of simulated shift-work light conditions on the circadian gene expression of canonical clock genes in two different tissues: the liver and the skin.

Unlike the skin, which directly senses external light stimuli,³⁹ the entrainment of liver clocks by light serves as a secondary event. In addition to synchronization from the central clock, feeding has been well demonstrated as a mechanism to reset liver clocks.⁴⁰^–⁴² In our study, we provided mice with unrestricted access to food, allowing us to primarily observe changes arising from shift-work light conditions. The data from our study indicated that short-term exposure to rotating shift-light conditions did not significantly affect the circadian rhythms of liver clock genes. However, long-term exposure to rotating shifts resulted in circadian dysregulation, as evidence by loss of rhythmicity or significant differences in phase, amplitude, or MESOR in 7 out of 8 tested clock genes, and the jet-lag condition affected 3 out of 8 of the genes tested. These results suggest that liver clocks exhibit adaptability under less aggressive shift-work light conditions, possibly due to input from multiple environmental cues. Moreover, recent research has demonstrated that restricted feeding not only entrains liver clocks but also influences skin clocks in a distinct manner, highlighting an interesting interplay wherein a single stimulus can impact multiple systems.³¹

In our investigation, we observed significant disturbances in the circadian rhythm of canonical clock genes in the skin under various shift-work light conditions. Short-term exposure to rotating shift schedules and chronic jet-lag led to the disruption of circadian rhythmicity in 4 out of 8 tested canonical clock genes, while long-term exposure to rotating shifts affected 6 out of 8 of the genes, with most of these changes attributed to phase differences. Notably, unlike the liver, the circadian clock in the skin exhibited significant dysregulation across all shift-work light conditions examined in our study. This suggests that the skin’s circadian clock is more susceptible to the impact of shift-work light conditions compared to the clock in the liver. One potential explanation for this susceptibility is the involvement of opsins-mediated signaling. Opsins are a class of light sensing G protein-coupled receptors that trigger signaling cascades upon photosensation. Previous studies have identified the expression of various opsins in different models, including murine melanocytes,³⁹ human melanocytes, keratinocytes, and dermal fibroblasts, and hair follicle stem cells.⁴³ The presence of opsins within the skin cells indicates the possibility of light-sensing capabilities in the skin tissue and the potential influence of environmental light cues on core clock regulation. However, experimental verification of this hypothesis is still required.

At the level of independent clock genes, we found that the circadian rhythms of cryptochrome genes (Cry1 and/or Cry2), which are the primary repressors of the molecular clock and also involved in maintaining genome integrity of cells,⁴⁴^,⁴⁵ were significantly disrupted under simulated shift conditions in both tissues. However, in the case of short-term rotating shift specifically affecting the liver, the rhythmicity of these genes remained intact. Cryptochromes (CRYs), found across various species from plants to animals, conserved evolutionarily, function in photoreception and signal transduction.⁴⁶ Their precise roles in mammalian circadian rhythm and light perception are complex, yet evidence suggests that CRYs may act as circadian photopigments, a possibility supported by experiments involving vitamin A depletion and mutations.⁴⁷^,⁴⁸ Our findings align with this research, indicating that Cry genes could be more sensitive to altered light shifts than other clock genes. Consequently, their rhythms may be uniquely susceptible to disruption under simulated shift conditions.

Moreover, our findings are consistent with existing literature in humans, which has associated disrupted rhythms of Cry1 and Cry2 with circadian dysregulation of DNA repair and increased DNA damage following exposure to simulated night shift conditions.⁴⁹ Additionally, we observed consistent dysregulation of the circadian transcription factor Arntl, which is involved in protecting skin cells and regulating UVB associated DNA repair response and melanin pigmentation.²³^,⁵⁰^,⁵¹ This dysregulation occurred following exposure to all different types of simulated shift-work light conditions utilized in this study.

Our study has few limitations that should be considered when interpreting the findings. First, the use of a mouse model may limit the generalizability of the results to humans. Second, the simulation of shift-work light conditions may not fully capture the complexity of real-world shift schedules. Third, the sample size was relatively small, potentially affecting the statistical power. Fourth, the duration of exposure in our study may not fully reflect the long-term consequences of shift-work in humans.

Despite these limitations, our study emphasizes the importance of recognizing the varying impacts of different shift conditions on the circadian system. We highlight the heightened susceptibility of the skin to circadian misalignment under shift-work light conditions, in comparison to the liver. Furthermore, we emphasize the significance of tissue-specific responses and the role of light regulating circadian rhythms, specifically focusing on canonical clock genes during shift-work. These findings offer valuable insights that can guide future research, potentially leading to the discovery of novel mechanisms and more effective treatment strategies for shift-work associated diseases.

Author contributions

Bala S. C. Koritala: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Software, Validation, Visualization, Writing – original draft preparation, Writing – review & editing. Panshak P. Dakup: Conceptualization, Investigation, Methodology, Resources, Validation, Writing – original draft preparation, Writing – review & editing. Kenneth I. Porter: Investigation, Methodology, Resources, Validation, Writing – review & editing. Shobhan Gaddameedhi: Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing.

Data availability

Underlying data

figshare: Raw data files with replicates titled as “Cycle threshold values of qPCR data for genes in the liver and skin of animals that were exposed to both control and simulated shift conditions”. https://doi.org/10.6084/m9.figshare.23269757.v1.⁵³

Extended data

figshare: Extended Data Table 1. CircaCompare analysis of canonical clock genes in the mouse liver and skin following exposure to simulated shift-work light conditions. https://doi.org/10.6084/m9.figshare.23512155.v1.⁵⁴

Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0).

Reporting guidelines

figshare: ARRIVE checklist for ‘The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study’. https://doi.org/10.6084/m9.figshare.23519379.v1.⁵⁵

References

1. Wright KP Jr, McHill AW, Birks BR, et al.: Entrainment of the human circadian clock to the natural light-dark cycle. Curr. Biol. 2013 Aug 19; 23(16): 1554–1558. PubMed Abstract | Publisher Full Text | Free Full Text
2. Roenneberg T, Merrow M: The Circadian Clock and Human Health. Curr. Biol. 2016 May 23; 26(10): R432–R443. PubMed Abstract | Publisher Full Text
3. Costa G: Shift work and health: current problems and preventive actions. Saf. Health Work. 2010 Dec; 1(2): 112–123. PubMed Abstract | Publisher Full Text | Free Full Text
4. Lunn RM, Blask DE, Coogan AN, et al.: Health consequences of electric lighting practices in the modern world: A report on the National Toxicology Program’s workshop on shift work at night, artificial light at night, and circadian disruption. Sci. Total Environ. 2017 Dec 31; 607-608: 1073–1084. PubMed Abstract | Publisher Full Text | Free Full Text
5. James SM, Honn KA, Gaddameedhi S, et al.: Shift Work: Disrupted Circadian Rhythms and Sleep-Implications for Health and Well-Being. Curr. Sleep Med. Rep. 2017 Jun; 3(2): 104–112. PubMed Abstract | Publisher Full Text | Free Full Text
6. Kervezee L, Cuesta M, Cermakian N, et al.: Simulated night shift work induces circadian misalignment of the human peripheral blood mononuclear cell transcriptome. Proc. Natl. Acad. Sci. U. S. A. 2018 May 22; 115(21): 5540–5545. PubMed Abstract | Publisher Full Text | Free Full Text
7. Kervezee L, Cermakian N, Boivin DB: Individual metabolomic signatures of circadian misalignment during simulated night shifts in humans. PLoS Biol. 2019 Jun; 17(6): e3000303. Epub 2019/06/19. PubMed Abstract | Publisher Full Text | Free Full Text
8. Skene DJ, Skornyakov E, Chowdhury NR, et al.: Separation of circadian- and behavior-driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism. Proc. Natl. Acad. Sci. U. S. A. 2018 Jul 24; 115(30): 7825–7830. PubMed Abstract | Publisher Full Text | Free Full Text
9. Adams KL, Castanon-Cervantes O, Evans JA, et al.: Environmental circadian disruption elevates the IL-6 response to lipopolysaccharide in blood. J. Biol. Rhythm. 2013 Aug; 28(4): 272–277. PubMed Abstract | Publisher Full Text | Free Full Text
10. Lee Y, Lahens NF, Zhang S, et al.: G1/S cell cycle regulators mediate effects of circadian dysregulation on tumor growth and provide targets for timed anticancer treatment. PLoS Biol. 2019 Apr; 17(4): e3000228. Epub 2019/05/01. PubMed Abstract | Publisher Full Text | Free Full Text
11. McGowan NM, Coogan AN: Circadian and behavioural responses to shift work-like schedules of light/dark in the mouse. J. Mol. Psychiatry. 2013; 1(1): 7. Epub 2013/01/01. PubMed Abstract | Publisher Full Text | Free Full Text
12. Van Dycke KC, Rodenburg W, van Oostrom CT , et al.: Chronically Alternating Light Cycles Increase Breast Cancer Risk in Mice. Curr. Biol. 2015 Jul 20; 25(14): 1932–1937. PubMed Abstract | Publisher Full Text
13. Davidson AJ, Castanon-Cervantes O, Leise TL, et al.: Visualizing jet lag in the mouse suprachiasmatic nucleus and peripheral circadian timing system. Eur. J. Neurosci. 2009 Jan; 29(1): 171–180. PubMed Abstract | Publisher Full Text
14. Figueiro MG, Goo YH, Hogan R, et al.: Light-Dark Patterns Mirroring Shift Work Accelerate Atherosclerosis and Promote Vulnerable Lesion Phenotypes. J. Am. Heart Assoc. 2021 Jan 19; 10(2): e018151. Epub 2021/01/07. PubMed Abstract | Publisher Full Text | Free Full Text
15. Papagiannakopoulos T, Bauer MR, Davidson SM, et al.: Circadian Rhythm Disruption Promotes Lung Tumorigenesis. Cell Metab. 2016 Aug 9; 24(2): 324–331. PubMed Abstract | Publisher Full Text | Free Full Text
16. Lee S, Donehower LA, Herron AJ, et al.: Disrupting circadian homeostasis of sympathetic signaling promotes tumor development in mice. PLoS One. 2010 Jun 7; 5(6): e10995. Epub 2010/06/12. PubMed Abstract | Publisher Full Text | Free Full Text
17. Kettner NM, Voicu H, Finegold MJ, et al.: Circadian Homeostasis of Liver Metabolism Suppresses Hepatocarcinogenesis. Cancer Cell. 2016 Dec 12; 30(6): 909–924. PubMed Abstract | Publisher Full Text | Free Full Text
18. Aiello I, Fedele MLM, Roman F, et al.: Circadian disruption promotes tumor-immune microenvironment remodeling favoring tumor cell proliferation. Sci. Adv. 2020 Oct; 6(42). Epub 2020/10/16. PubMed Abstract | Publisher Full Text | Free Full Text
19. Thaiss CA, Zeevi D, Levy M, et al.: Transkingdom control of microbiota diurnal oscillations promotes metabolic homeostasis. Cell. 2014 Oct 23; 159(3): 514–529. PubMed Abstract | Publisher Full Text
20. Figueiro MG, Radetsky L, Plitnick B, et al.: Glucose tolerance in mice exposed to light-dark stimulus patterns mirroring dayshift and rotating shift schedules. Sci. Rep. 2017 Jan 12; 7: 40661. Epub 2017/01/13. PubMed Abstract | Publisher Full Text | Free Full Text
21. Christie S, Vincent AD, Li H, et al.: A rotating light cycle promotes weight gain and hepatic lipid storage in mice. Am. J. Physiol. Gastrointest. Liver Physiol. 2018 Dec 1; 315(6): G932–G942. PubMed Abstract | Publisher Full Text
22. Dakup PP, Porter KI, Gajula RP, et al.: The circadian clock protects against ionizing radiation-induced cardiotoxicity. FASEB J. 2020 Feb; 34(2): 3347–3358. PubMed Abstract | Publisher Full Text | Free Full Text
23. Dakup PP, Porter KI, Gaddameedhi S: The circadian clock protects against acute radiation-induced dermatitis. Toxicol. Appl. Pharmacol. 2020 Jul 15; 399: 115040. Epub 20200515. PubMed Abstract | Publisher Full Text
24. Bae K, Jin X, Maywood ES, et al.: Differential functions of mPer1, mPer2, and mPer3 in the SCN circadian clock. Neuron. 2001 May; 30(2): 525–536. PubMed Abstract | Publisher Full Text
25. Zwighaft Z, Reinke H, Asher G: The Liver in the Eyes of a Chronobiologist. J. Biol. Rhythm. 2016 Apr; 31(2): 115–124. PubMed Abstract | Publisher Full Text
26. Koike N, Yoo SH, Huang HC, et al.: Transcriptional architecture and chromatin landscape of the core circadian clock in mammals. Science. 2012 Oct 19; 338(6105): 349–354. PubMed Abstract | Publisher Full Text | Free Full Text
27. Rey G, Cesbron F, Rougemont J, et al.: Genome-wide and phase-specific DNA-binding rhythms of BMAL1 control circadian output functions in mouse liver. PLoS Biol. 2011 Feb; 9(2): e1000595. Epub 2011/03/03. PubMed Abstract | Publisher Full Text | Free Full Text
28. Reinke H, Asher G: Crosstalk between metabolism and circadian clocks. Nat. Rev. Mol. Cell Biol. 2019 Apr; 20(4): 227–241. PubMed Abstract | Publisher Full Text
29. Wu G, Ruben MD, Schmidt RE, et al.: Population-level rhythms in human skin with implications for circadian medicine. Proc. Natl. Acad. Sci. U. S. A. 2018 Nov 27; 115(48): 12313–12318. PubMed Abstract | Publisher Full Text | Free Full Text
30. Plikus MV, Andersen B: Skin as a window to body-clock time. Proc. Natl. Acad. Sci. U. S. A. 2018 Nov 27; 115(48): 12095–12097. PubMed Abstract | Publisher Full Text | Free Full Text
31. Wang H, van Spyk E , Liu Q, et al.: Time-Restricted Feeding Shifts the Skin Circadian Clock and Alters UVB-Induced DNA Damage. Cell Rep. 2017 Aug 1; 20(5): 1061–1072. PubMed Abstract | Publisher Full Text | Free Full Text
32. Vandesompele J, De Preter K, Pattyn F, et al.: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002 Jun 18; 3(7): RESEARCH0034. Epub 2002/08/20. PubMed Abstract | Publisher Full Text | Free Full Text
33. Svec D, Tichopad A, Novosadova V, et al.: How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments. Biomol. Detect Quantif. 2015 Mar; 3: 9–16. PubMed Abstract | Publisher Full Text | Free Full Text
34. Parsons R, Parsons R, Garner N, et al.: CircaCompare: a method to estimate and statistically support differences in mesor, amplitude and phase, between circadian rhythms. Bioinformatics. 2020 Feb 15; 36(4): 1208–1212. PubMed Abstract | Publisher Full Text
35. Hughes ME, Abruzzi KC, Allada R, et al.: Guidelines for Genome-Scale Analysis of Biological Rhythms. J. Biol. Rhythm. 2017 Oct; 32(5): 380–393. PubMed Abstract | Publisher Full Text | Free Full Text
36. Fritschi L, Glass DC, Heyworth JS, et al.: Hypotheses for mechanisms linking shiftwork and cancer. Med. Hypotheses. 2011 Sep; 77(3): 430–436. PubMed Abstract | Publisher Full Text
37. Panda S, Sato TK, Castrucci AM, et al.: Melanopsin (Opn4) requirement for normal light-induced circadian phase shifting. Science. 2002 Dec 13; 298(5601): 2213–2216. PubMed Abstract | Publisher Full Text
38. Buhr ED, Yue WW, Ren X, et al.: Neuropsin (OPN5)-mediated photoentrainment of local circadian oscillators in mammalian retina and cornea. Proc. Natl. Acad. Sci. U. S. A. 2015 Oct 20; 112(42): 13093–13098. PubMed Abstract | Publisher Full Text | Free Full Text
39. Buhr ED, Vemaraju S, Diaz N, et al.: Neuropsin (OPN5) Mediates Local Light-Dependent Induction of Circadian Clock Genes and Circadian Photoentrainment in Exposed Murine Skin. Curr. Biol. 2019 Oct 21; 29(20): 3478–3487.e4. PubMed Abstract | Publisher Full Text | Free Full Text
40. Damiola F, Le Minh N, Preitner N, et al.: Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes Dev. 2000 Dec 1; 14(23): 2950–2961. PubMed Abstract | Publisher Full Text | Free Full Text
41. Stokkan KA, Yamazaki S, Tei H, et al.: Entrainment of the circadian clock in the liver by feeding. Science. 2001 Jan 19; 291(5503): 490–493. PubMed Abstract | Publisher Full Text
42. Koronowski KB, Kinouchi K, Welz PS, et al.: Defining the Independence of the Liver Circadian Clock. Cell. 2019 May 30; 177(6): 1448–1462.e14. PubMed Abstract | Publisher Full Text | Free Full Text
43. Suh S, Choi EH, Atanaskova MN: The expression of opsins in the human skin and its implications for photobiomodulation: A Systematic Review. Photodermatol. Photoimmunol. Photomed. 2020 Sep; 36(5): 329–338. PubMed Abstract | Publisher Full Text | Free Full Text
44. Papp SJ, Huber AL, Jordan SD, et al.: DNA damage shifts circadian clock time via Hausp-dependent Cry1 stabilization. elife. 2015 Mar 10; 4. Epub 20150310. PubMed Abstract | Publisher Full Text | Free Full Text
45. Ye R, Selby CP, Chiou YY, et al.: Dual modes of CLOCK:BMAL1 inhibition mediated by Cryptochrome and Period proteins in the mammalian circadian clock. Genes Dev. 2014 Sep 15; 28(18): 1989–1998. PubMed Abstract | Publisher Full Text | Free Full Text
46. Sancar A: Regulation of the mammalian circadian clock by cryptochrome. J. Biol. Chem. 2004 Aug 13; 279(33): 34079–34082. PubMed Abstract | Publisher Full Text
47. Thompson CL, Blaner WS, Van Gelder RN, et al.: Preservation of light signaling to the suprachiasmatic nucleus in vitamin A-deficient mice. Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 11708–11713. PubMed Abstract | Publisher Full Text | Free Full Text
48. Thompson CL, Selby CP, Van Gelder RN, et al.: Effect of vitamin A depletion on nonvisual phototransduction pathways in cryptochromeless mice. J. Biol. Rhythms. 2004; 19: 504–517. PubMed Abstract | Publisher Full Text
49. Koritala BSC, Porter KI, Arshad OA, et al.: Night shift schedule causes circadian dysregulation of DNA repair genes and elevated DNA damage in humans. J. Pineal Res. 2021 Apr; 70(3): e12726. Epub 20210314. PubMed Abstract | Publisher Full Text | Free Full Text
50. Geyfman M, Kumar V, Liu Q, et al.: Brain and muscle Arnt-like protein-1 (BMAL1) controls circadian cell proliferation and susceptibility to UVB-induced DNA damage in the epidermis. Proc. Natl. Acad. Sci. U. S. A. 2012 Jul 17; 109(29): 11758–11763. PubMed Abstract | Publisher Full Text | Free Full Text
51. Sarkar S, Porter KI, Dakup PP, et al.: Circadian clock protein BMAL1 regulates melanogenesis through MITF in melanoma cells. Pigment Cell Melanoma Res. 2021 Sep; 34(5): 955–965. PubMed Abstract | Publisher Full Text | Free Full Text
52. Kosir R, Acimovic J, Golicnik M, et al.: Determination of reference genes for circadian studies in different tissues and mouse strains. BMC Mol. Biol. 2010 Aug 16; 11: 60. PubMed Abstract | Publisher Full Text | Free Full Text
53. Koritala BSC, Dakup PP, Porter KI, et al.: Cycle threshold values of qPCR data for genes in the liver and skin of animals that were exposed to both control and simulated shift conditions. [Dataset]. figshare. 2023. Publisher Full Text
54. Koritala B, Dakup PP, Porter KI, et al.: CircaCompare analysis of canonical clock genes in the mouse liver and skin following exposure to simulated shift-work light conditions. [Dataset]. figshare. 2023. Publisher Full Text
55. Koritala B, Dakup PP, Porter KI, et al.: Author Checklist - F1000 Research.pdf. figshare. 2023. Publisher Full Text

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Version 3

VERSION 3 PUBLISHED 28 Jun 2023

Author details Author details

Panshak P. Dakup
Roles: Conceptualization, Investigation, Methodology, Resources, Validation, Writing – Original Draft Preparation, Writing – Review & Editing

Kenneth I. Porter
Roles: Investigation, Methodology, Resources, Validation, Writing – Review & Editing

Shobhan Gaddameedhi
Roles: Conceptualization, Data Curation, Funding Acquisition, Methodology, Project Administration, Resources, Supervision, Validation, Writing – Review & Editing

Competing interests

No competing interests were disclosed.

Grant information

This work was supported by the National Institutes of Health grant R01ES030113 (S.G.).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Koritala BSC, Dakup PP, Porter KI and Gaddameedhi S. The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study [version 2; peer review: 2 approved]. F1000Research 2023, 12:762 (https://doi.org/10.12688/f1000research.136998.2)

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Reviewer Report 09 Aug 2023

Tianpeng Zhang, Guangzhou University, Guangzhou, Guangdong, China

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https://doi.org/10.5256/f1000research.153932.r193308

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Reviewer Report 11 Aug 2023

Brian J. Altman, Department of Biomedical Genetics, Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY, USA

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https://doi.org/10.5256/f1000research.150145.r184831

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the outcome of short- and long-term exposure to rotating shift work compared to normal conditions and jet lag in circadian rhythms of the skin and liver in mice. This aims to fill a knowledge gap where only short-term shift work experiments have been conducted on humans in laboratory settings, whereas human shift workers tend to engage in rotating shift work for many years. The Authors find that, in general, short-term shift work has a subtle effect on rhythmicity of molecular clock gene expression, particularly in the liver. In longer-term shift work and jet lag, the Cry genes were the most sensitive to disruption; however, long-term shift work and jet lag both dramatically affected the oscillatory characteristics of many circadian genes, often in a disparate fashion. The Authors conclude that different rotating work and sleep schedules can have outsize impacts on molecular clock oscillation that may vary between tissues.

Overall, this is a well-designed and executed study with clear outcomes and interpretable results. I have several minor suggestions and comments that I believe will enhance the quality of the final manuscript.

This study was only carried out in male mice, which goes against the NIH policy “Consideration of Sex as a Biological Variable in NIH-funded Research” (NOT-OD-15-102). The Authors should discuss this in their Limitations section, and how the outcomes may be different in females.
In Figure 4, it is difficult to assess which oscillation characteristics are significantly different from control just by looking at the figure. I am aware that full statistics are available in Extended Data Table 1, but it would be best if the Authors also figured out a way to represent, perhaps with a different shape (a star instead of a circle?) which datapoints were significantly different in Figure 4.
In the Discussion, the Authors mainly focus on the observed differences between short-term and long-term rotating shift work, which is indeed important. Equally important is the fact that many papers and groups use the jet lag protocol as a proxy for shift work, and the Authors demonstrate here that the outcomes of jet lag can be quite different from either short-term or long-term rotating shift work. This is a very important finding that should be addressed in the Discussion.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: Molecular cancer biology, lung biology, immunology, circadian rhythms, metabolism

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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Report a concern

Author Response 29 Aug 2023

SHOBHAN GADDAMEEDHI, Center for Human Health and the Environment, North Carolina State University, Raleigh, USA

29 Aug 2023

Author Response

Reviewer Comments

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the ... Continue reading Reviewer Comments

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the outcome of short- and long-term exposure to rotating shift work compared to normal conditions and jet lag in circadian rhythms of the skin and liver in mice. This aims to fill a knowledge gap where only short-term shift work experiments have been conducted on humans in laboratory settings, whereas human shift workers tend to engage in rotating shift work for many years. The Authors find that, in general, short-term shift work has a subtle effect on rhythmicity of molecular clock gene expression, particularly in the liver. In longer-term shift work and jet lag, the Cry genes were the most sensitive to disruption; however, long-term shift work and jet lag both dramatically affected the oscillatory characteristics of many circadian genes, often in a disparate fashion. The Authors conclude that different rotating work and sleep schedules can have outsize impacts on molecular clock oscillation that may vary between tissues.

Overall, this is a well-designed and executed study with clear outcomes and interpretable results. I have several minor suggestions and comments that I believe will enhance the quality of the final manuscript.

Authors' response: We appreciate the reviewer’s constructive and positive feedback on our manuscript.

1. This study was only carried out in male mice, which goes against the NIH policy “Consideration of Sex as a Biological Variable in NIH-funded Research” (NOT-OD-15-102). The Authors should discuss this in their Limitations section, and how the outcomes may be different in females.

Authors' response: We thank the reviewer for highlighting this. We concur and have addressed the exclusive use of male mice in the limitations section, including potential differences in female outcomes.

2. In Figure 4, it is difficult to assess which oscillation characteristics are significantly different from control just by looking at the figure. I am aware that full statistics are available in Extended Data Table 1, but it would be best if the Authors also figured out a way to represent, perhaps with a different shape (a star instead of a circle?) which datapoints were significantly different in Figure 4.

Authors' response: Great suggestion. We revised Figure 4 to visually highlight the significantly different datapoints.

3. In the Discussion, the Authors mainly focus on the observed differences between short-term and long-term rotating shift work, which is indeed important. Equally important is the fact that many papers and groups use the jet lag protocol as a proxy for shift work, and the Authors demonstrate here that the outcomes of jet lag can be quite different from either short-term or long-term rotating shift work. This is a very important finding that should be addressed in the Discussion.

Authors' response: Thank you for highlighting this. We've updated our Discussion section to emphasize the differences between jet lag outcomes and the effects of both short-term and long-term rotating shift work.
Reviewer Comments

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the outcome of short- and long-term exposure to rotating shift work compared to normal conditions and jet lag in circadian rhythms of the skin and liver in mice. This aims to fill a knowledge gap where only short-term shift work experiments have been conducted on humans in laboratory settings, whereas human shift workers tend to engage in rotating shift work for many years. The Authors find that, in general, short-term shift work has a subtle effect on rhythmicity of molecular clock gene expression, particularly in the liver. In longer-term shift work and jet lag, the Cry genes were the most sensitive to disruption; however, long-term shift work and jet lag both dramatically affected the oscillatory characteristics of many circadian genes, often in a disparate fashion. The Authors conclude that different rotating work and sleep schedules can have outsize impacts on molecular clock oscillation that may vary between tissues.

Overall, this is a well-designed and executed study with clear outcomes and interpretable results. I have several minor suggestions and comments that I believe will enhance the quality of the final manuscript.

Authors' response: We appreciate the reviewer’s constructive and positive feedback on our manuscript.

1. This study was only carried out in male mice, which goes against the NIH policy “Consideration of Sex as a Biological Variable in NIH-funded Research” (NOT-OD-15-102). The Authors should discuss this in their Limitations section, and how the outcomes may be different in females.

Authors' response: We thank the reviewer for highlighting this. We concur and have addressed the exclusive use of male mice in the limitations section, including potential differences in female outcomes.

2. In Figure 4, it is difficult to assess which oscillation characteristics are significantly different from control just by looking at the figure. I am aware that full statistics are available in Extended Data Table 1, but it would be best if the Authors also figured out a way to represent, perhaps with a different shape (a star instead of a circle?) which datapoints were significantly different in Figure 4.

Authors' response: Great suggestion. We revised Figure 4 to visually highlight the significantly different datapoints.

3. In the Discussion, the Authors mainly focus on the observed differences between short-term and long-term rotating shift work, which is indeed important. Equally important is the fact that many papers and groups use the jet lag protocol as a proxy for shift work, and the Authors demonstrate here that the outcomes of jet lag can be quite different from either short-term or long-term rotating shift work. This is a very important finding that should be addressed in the Discussion.

Authors' response: Thank you for highlighting this. We've updated our Discussion section to emphasize the differences between jet lag outcomes and the effects of both short-term and long-term rotating shift work.
Competing Interests: No conflicts of Interests Close
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COMMENTS ON THIS REPORT

Author Response 29 Aug 2023

SHOBHAN GADDAMEEDHI, Center for Human Health and the Environment, North Carolina State University, Raleigh, USA

29 Aug 2023

Author Response

Reviewer Comments

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the ... Continue reading Reviewer Comments

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the outcome of short- and long-term exposure to rotating shift work compared to normal conditions and jet lag in circadian rhythms of the skin and liver in mice. This aims to fill a knowledge gap where only short-term shift work experiments have been conducted on humans in laboratory settings, whereas human shift workers tend to engage in rotating shift work for many years. The Authors find that, in general, short-term shift work has a subtle effect on rhythmicity of molecular clock gene expression, particularly in the liver. In longer-term shift work and jet lag, the Cry genes were the most sensitive to disruption; however, long-term shift work and jet lag both dramatically affected the oscillatory characteristics of many circadian genes, often in a disparate fashion. The Authors conclude that different rotating work and sleep schedules can have outsize impacts on molecular clock oscillation that may vary between tissues.

Overall, this is a well-designed and executed study with clear outcomes and interpretable results. I have several minor suggestions and comments that I believe will enhance the quality of the final manuscript.

Authors' response: We appreciate the reviewer’s constructive and positive feedback on our manuscript.

1. This study was only carried out in male mice, which goes against the NIH policy “Consideration of Sex as a Biological Variable in NIH-funded Research” (NOT-OD-15-102). The Authors should discuss this in their Limitations section, and how the outcomes may be different in females.

Authors' response: We thank the reviewer for highlighting this. We concur and have addressed the exclusive use of male mice in the limitations section, including potential differences in female outcomes.

2. In Figure 4, it is difficult to assess which oscillation characteristics are significantly different from control just by looking at the figure. I am aware that full statistics are available in Extended Data Table 1, but it would be best if the Authors also figured out a way to represent, perhaps with a different shape (a star instead of a circle?) which datapoints were significantly different in Figure 4.

Authors' response: Great suggestion. We revised Figure 4 to visually highlight the significantly different datapoints.

3. In the Discussion, the Authors mainly focus on the observed differences between short-term and long-term rotating shift work, which is indeed important. Equally important is the fact that many papers and groups use the jet lag protocol as a proxy for shift work, and the Authors demonstrate here that the outcomes of jet lag can be quite different from either short-term or long-term rotating shift work. This is a very important finding that should be addressed in the Discussion.

Authors' response: Thank you for highlighting this. We've updated our Discussion section to emphasize the differences between jet lag outcomes and the effects of both short-term and long-term rotating shift work.
Reviewer Comments

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the outcome of short- and long-term exposure to rotating shift work compared to normal conditions and jet lag in circadian rhythms of the skin and liver in mice. This aims to fill a knowledge gap where only short-term shift work experiments have been conducted on humans in laboratory settings, whereas human shift workers tend to engage in rotating shift work for many years. The Authors find that, in general, short-term shift work has a subtle effect on rhythmicity of molecular clock gene expression, particularly in the liver. In longer-term shift work and jet lag, the Cry genes were the most sensitive to disruption; however, long-term shift work and jet lag both dramatically affected the oscillatory characteristics of many circadian genes, often in a disparate fashion. The Authors conclude that different rotating work and sleep schedules can have outsize impacts on molecular clock oscillation that may vary between tissues.

Overall, this is a well-designed and executed study with clear outcomes and interpretable results. I have several minor suggestions and comments that I believe will enhance the quality of the final manuscript.

Authors' response: We appreciate the reviewer’s constructive and positive feedback on our manuscript.

1. This study was only carried out in male mice, which goes against the NIH policy “Consideration of Sex as a Biological Variable in NIH-funded Research” (NOT-OD-15-102). The Authors should discuss this in their Limitations section, and how the outcomes may be different in females.

Authors' response: We thank the reviewer for highlighting this. We concur and have addressed the exclusive use of male mice in the limitations section, including potential differences in female outcomes.

2. In Figure 4, it is difficult to assess which oscillation characteristics are significantly different from control just by looking at the figure. I am aware that full statistics are available in Extended Data Table 1, but it would be best if the Authors also figured out a way to represent, perhaps with a different shape (a star instead of a circle?) which datapoints were significantly different in Figure 4.

Authors' response: Great suggestion. We revised Figure 4 to visually highlight the significantly different datapoints.

3. In the Discussion, the Authors mainly focus on the observed differences between short-term and long-term rotating shift work, which is indeed important. Equally important is the fact that many papers and groups use the jet lag protocol as a proxy for shift work, and the Authors demonstrate here that the outcomes of jet lag can be quite different from either short-term or long-term rotating shift work. This is a very important finding that should be addressed in the Discussion.

Authors' response: Thank you for highlighting this. We've updated our Discussion section to emphasize the differences between jet lag outcomes and the effects of both short-term and long-term rotating shift work.
Competing Interests: No conflicts of Interests Close
Report a concern

Views

Reviewer Report 13 Jul 2023

Tianpeng Zhang, Guangzhou University, Guangzhou, Guangdong, China

Approved with Reservations

https://doi.org/10.5256/f1000research.150145.r184816

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the authors have utilized multiple approaches to test their hypothesis, there remain areas where ... Continue reading

Describe in detail the process for collecting skin, which part of the skin tissue was collected?
Is the selection of light intensity reasonable in the experiment? Multiple studies have shown that bright light can affect the circadian rhythm of activity, metabolism and clock gene expression (Bano-Otalora et al., 2021¹; Alves-Simoes et al., 2016²; Fan et al., 2022³). Meanwhile, the light intensity also affects the impact of chronic jet-lag.
More information should be provided on Circadian rhythm analysis, especially the setting of parameters.
Why use two housekeeping genes in the same tissue for clock gene relative quantification?
The author should discuss why Cry genes are preferentially altered under three light conditions.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

References

1. Bano-Otalora B, Martial F, Harding C, Bechtold DA, et al.: Bright daytime light enhances circadian amplitude in a diurnal mammal.Proc Natl Acad Sci U S A. 2021; 118 (22). PubMed Abstract | Publisher Full Text
2. Alves-Simoes M, Coleman G, Canal MM: Effects of type of light on mouse circadian behaviour and stress levels.Lab Anim. 2016; 50 (1): 21-9 PubMed Abstract | Publisher Full Text
3. Fan X, Chen D, Wang Y, Tan Y, et al.: Light intensity alters the effects of light-induced circadian disruption on glucose and lipid metabolism in mice.Am J Physiol Endocrinol Metab. 2022; 322 (1): E1-E9 PubMed Abstract | Publisher Full Text

Competing Interests: No competing interests were disclosed.

Reviewer Expertise: circadian clock and metabolism

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.

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Author Response 29 Aug 2023

SHOBHAN GADDAMEEDHI, Center for Human Health and the Environment, North Carolina State University, Raleigh, USA

29 Aug 2023

Author Response

Reviewer Comments

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the ... Continue reading Reviewer Comments

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the authors have utilized multiple approaches to test their hypothesis, there remain areas where the methods section should also provide detailed information. Please refer to the following comments for more details.

1. Describe in detail the process for collecting skin, which part of the skin tissue was collected?
Authors' response: As per the suggestion of the reviewer, we have elaborated on the procedure of skin tissue collection within the 'Study Design and Sample Collection' section in our methods.

2. Is the selection of light intensity reasonable in the experiment? Multiple studies have shown that bright light can affect the circadian rhythm of activity, metabolism and clock gene expression (Bano-Otalora et al., 20211; Alves-Simoes et al., 20162; Fan et al., 20223). Meanwhile, the light intensity also affects the impact of chronic jet-lag.
Authors' response: Our study maintained similar light intensities across control and shift simulation groups to focus on shift impacts, thereby reducing potential variation from light intensity differences. However, recognizing the significance of light intensity on chronic jet-lag, we will consider incorporating this factor into future experimental designs, perhaps by comparing the effects of different light intensities on chronic jet-lag.

3. More information should be provided on Circadian rhythm analysis, especially the setting of parameters.
Authors' response: In response to the reviewer’s suggestion, we have clarified our use of the standard parameters of the CircaCompare R package (as per Parsons et al., Bioinformatics, 2020, PMID: 31588519). This approach includes a fixed period of 24 hours.

4. Why use two housekeeping genes in the same tissue for clock gene relative quantification?
Authors' response: Vandesompele et al. (Genome Biol. 2002, PMID: 12184808) showed that normalizing with the geometric mean of carefully chosen control genes improves qPCR accuracy. Using a single universal control gene is less effective due to variations across different cells or tissues. Moreover, fluctuations within standard housekeeping genes depending on the time of day have been recognized in studies (Kosir et al., BMC Mol Biol. 2010; PMID: 20712867). Thus, the utilization of more than one housekeeping gene minimizes this variability.

5.The author should discuss why Cry genes are preferentially altered under three light conditions.
Authors' response: In the discussion section of the revised manuscript, we covered the response of Cry genes to simulated shift conditions.
Reviewer Comments

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the authors have utilized multiple approaches to test their hypothesis, there remain areas where the methods section should also provide detailed information. Please refer to the following comments for more details.

1. Describe in detail the process for collecting skin, which part of the skin tissue was collected?
Authors' response: As per the suggestion of the reviewer, we have elaborated on the procedure of skin tissue collection within the 'Study Design and Sample Collection' section in our methods.

2. Is the selection of light intensity reasonable in the experiment? Multiple studies have shown that bright light can affect the circadian rhythm of activity, metabolism and clock gene expression (Bano-Otalora et al., 20211; Alves-Simoes et al., 20162; Fan et al., 20223). Meanwhile, the light intensity also affects the impact of chronic jet-lag.
Authors' response: Our study maintained similar light intensities across control and shift simulation groups to focus on shift impacts, thereby reducing potential variation from light intensity differences. However, recognizing the significance of light intensity on chronic jet-lag, we will consider incorporating this factor into future experimental designs, perhaps by comparing the effects of different light intensities on chronic jet-lag.

3. More information should be provided on Circadian rhythm analysis, especially the setting of parameters.
Authors' response: In response to the reviewer’s suggestion, we have clarified our use of the standard parameters of the CircaCompare R package (as per Parsons et al., Bioinformatics, 2020, PMID: 31588519). This approach includes a fixed period of 24 hours.

4. Why use two housekeeping genes in the same tissue for clock gene relative quantification?
Authors' response: Vandesompele et al. (Genome Biol. 2002, PMID: 12184808) showed that normalizing with the geometric mean of carefully chosen control genes improves qPCR accuracy. Using a single universal control gene is less effective due to variations across different cells or tissues. Moreover, fluctuations within standard housekeeping genes depending on the time of day have been recognized in studies (Kosir et al., BMC Mol Biol. 2010; PMID: 20712867). Thus, the utilization of more than one housekeeping gene minimizes this variability.

5.The author should discuss why Cry genes are preferentially altered under three light conditions.
Authors' response: In the discussion section of the revised manuscript, we covered the response of Cry genes to simulated shift conditions.
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Author Response 29 Aug 2023

SHOBHAN GADDAMEEDHI, Center for Human Health and the Environment, North Carolina State University, Raleigh, USA

29 Aug 2023

Author Response

Reviewer Comments

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the ... Continue reading Reviewer Comments

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the authors have utilized multiple approaches to test their hypothesis, there remain areas where the methods section should also provide detailed information. Please refer to the following comments for more details.

1. Describe in detail the process for collecting skin, which part of the skin tissue was collected?
Authors' response: As per the suggestion of the reviewer, we have elaborated on the procedure of skin tissue collection within the 'Study Design and Sample Collection' section in our methods.

2. Is the selection of light intensity reasonable in the experiment? Multiple studies have shown that bright light can affect the circadian rhythm of activity, metabolism and clock gene expression (Bano-Otalora et al., 20211; Alves-Simoes et al., 20162; Fan et al., 20223). Meanwhile, the light intensity also affects the impact of chronic jet-lag.
Authors' response: Our study maintained similar light intensities across control and shift simulation groups to focus on shift impacts, thereby reducing potential variation from light intensity differences. However, recognizing the significance of light intensity on chronic jet-lag, we will consider incorporating this factor into future experimental designs, perhaps by comparing the effects of different light intensities on chronic jet-lag.

3. More information should be provided on Circadian rhythm analysis, especially the setting of parameters.
Authors' response: In response to the reviewer’s suggestion, we have clarified our use of the standard parameters of the CircaCompare R package (as per Parsons et al., Bioinformatics, 2020, PMID: 31588519). This approach includes a fixed period of 24 hours.

4. Why use two housekeeping genes in the same tissue for clock gene relative quantification?
Authors' response: Vandesompele et al. (Genome Biol. 2002, PMID: 12184808) showed that normalizing with the geometric mean of carefully chosen control genes improves qPCR accuracy. Using a single universal control gene is less effective due to variations across different cells or tissues. Moreover, fluctuations within standard housekeeping genes depending on the time of day have been recognized in studies (Kosir et al., BMC Mol Biol. 2010; PMID: 20712867). Thus, the utilization of more than one housekeeping gene minimizes this variability.

5.The author should discuss why Cry genes are preferentially altered under three light conditions.
Authors' response: In the discussion section of the revised manuscript, we covered the response of Cry genes to simulated shift conditions.
Reviewer Comments

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the authors have utilized multiple approaches to test their hypothesis, there remain areas where the methods section should also provide detailed information. Please refer to the following comments for more details.

1. Describe in detail the process for collecting skin, which part of the skin tissue was collected?
Authors' response: As per the suggestion of the reviewer, we have elaborated on the procedure of skin tissue collection within the 'Study Design and Sample Collection' section in our methods.

2. Is the selection of light intensity reasonable in the experiment? Multiple studies have shown that bright light can affect the circadian rhythm of activity, metabolism and clock gene expression (Bano-Otalora et al., 20211; Alves-Simoes et al., 20162; Fan et al., 20223). Meanwhile, the light intensity also affects the impact of chronic jet-lag.
Authors' response: Our study maintained similar light intensities across control and shift simulation groups to focus on shift impacts, thereby reducing potential variation from light intensity differences. However, recognizing the significance of light intensity on chronic jet-lag, we will consider incorporating this factor into future experimental designs, perhaps by comparing the effects of different light intensities on chronic jet-lag.

3. More information should be provided on Circadian rhythm analysis, especially the setting of parameters.
Authors' response: In response to the reviewer’s suggestion, we have clarified our use of the standard parameters of the CircaCompare R package (as per Parsons et al., Bioinformatics, 2020, PMID: 31588519). This approach includes a fixed period of 24 hours.

4. Why use two housekeeping genes in the same tissue for clock gene relative quantification?
Authors' response: Vandesompele et al. (Genome Biol. 2002, PMID: 12184808) showed that normalizing with the geometric mean of carefully chosen control genes improves qPCR accuracy. Using a single universal control gene is less effective due to variations across different cells or tissues. Moreover, fluctuations within standard housekeeping genes depending on the time of day have been recognized in studies (Kosir et al., BMC Mol Biol. 2010; PMID: 20712867). Thus, the utilization of more than one housekeeping gene minimizes this variability.

5.The author should discuss why Cry genes are preferentially altered under three light conditions.
Authors' response: In the discussion section of the revised manuscript, we covered the response of Cry genes to simulated shift conditions.
Competing Interests: No conflicts of Interests Close
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Version 3

VERSION 3 PUBLISHED 28 Jun 2023

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Version 3 (revision) 17 Aug 23		read
Version 2 (revision) 02 Aug 23	read
Version 1 28 Jun 23	read	read

Tianpeng Zhang, Guangzhou University, Guangzhou, China
Brian J. Altman, University of Rochester Medical Center, Rochester, USA

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9 Views

22 Aug 2023 | for Version 3

Brian J. Altman, Department of Biomedical Genetics, Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY, USA

9 Views Cite this report Responses(0)

Approved

I approve of all changes made to the revised manuscript.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

circadian rhythms, cancer

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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14 Views

09 Aug 2023 | for Version 2

Tianpeng Zhang, Guangzhou University, Guangzhou, Guangdong, China

14 Views Cite this report Responses(0)

Approved

Authors have responded my comments.

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Circadian clock and metabolism

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

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18 Views

11 Aug 2023 | for Version 1

Brian J. Altman, Department of Biomedical Genetics, Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, NY, USA

18 Views Cite this report Responses(1)

Approved

This study was only carried out in male mice, which goes against the NIH policy “Consideration of Sex as a Biological Variable in NIH-funded Research” (NOT-OD-15-102). The Authors should discuss this in their Limitations section, and how the outcomes may be different in females.
In Figure 4, it is difficult to assess which oscillation characteristics are significantly different from control just by looking at the figure. I am aware that full statistics are available in Extended Data Table 1, but it would be best if the Authors also figured out a way to represent, perhaps with a different shape (a star instead of a circle?) which datapoints were significantly different in Figure 4.
In the Discussion, the Authors mainly focus on the observed differences between short-term and long-term rotating shift work, which is indeed important. Equally important is the fact that many papers and groups use the jet lag protocol as a proxy for shift work, and the Authors demonstrate here that the outcomes of jet lag can be quite different from either short-term or long-term rotating shift work. This is a very important finding that should be addressed in the Discussion.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Partly
Are sufficient details of methods and analysis provided to allow replication by others?

Yes
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

Molecular cancer biology, lung biology, immunology, circadian rhythms, metabolism

I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Respond to this report

Responses (1)

Author Response

29 Aug 2023

SHOBHAN GADDAMEEDHI, Center for Human Health and the Environment, North Carolina State University, Raleigh, USA

Reviewer Comments

In “The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study”, Koritala, Dakup, and colleagues explore the outcome of short- and long-term exposure to rotating shift work compared to normal conditions and jet lag in circadian rhythms of the skin and liver in mice. This aims to fill a knowledge gap where only short-term shift work experiments have been conducted on humans in laboratory settings, whereas human shift workers tend to engage in rotating shift work for many years. The Authors find that, in general, short-term shift work has a subtle effect on rhythmicity of molecular clock gene expression, particularly in the liver. In longer-term shift work and jet lag, the Cry genes were the most sensitive to disruption; however, long-term shift work and jet lag both dramatically affected the oscillatory characteristics of many circadian genes, often in a disparate fashion. The Authors conclude that different rotating work and sleep schedules can have outsize impacts on molecular clock oscillation that may vary between tissues.

Overall, this is a well-designed and executed study with clear outcomes and interpretable results. I have several minor suggestions and comments that I believe will enhance the quality of the final manuscript.

Authors' response: We appreciate the reviewer’s constructive and positive feedback on our manuscript.

1. This study was only carried out in male mice, which goes against the NIH policy “Consideration of Sex as a Biological Variable in NIH-funded Research” (NOT-OD-15-102). The Authors should discuss this in their Limitations section, and how the outcomes may be different in females.

Authors' response: We thank the reviewer for highlighting this. We concur and have addressed the exclusive use of male mice in the limitations section, including potential differences in female outcomes.

2. In Figure 4, it is difficult to assess which oscillation characteristics are significantly different from control just by looking at the figure. I am aware that full statistics are available in Extended Data Table 1, but it would be best if the Authors also figured out a way to represent, perhaps with a different shape (a star instead of a circle?) which datapoints were significantly different in Figure 4.

Authors' response: Great suggestion. We revised Figure 4 to visually highlight the significantly different datapoints.

3. In the Discussion, the Authors mainly focus on the observed differences between short-term and long-term rotating shift work, which is indeed important. Equally important is the fact that many papers and groups use the jet lag protocol as a proxy for shift work, and the Authors demonstrate here that the outcomes of jet lag can be quite different from either short-term or long-term rotating shift work. This is a very important finding that should be addressed in the Discussion.

Authors' response: Thank you for highlighting this. We've updated our Discussion section to emphasize the differences between jet lag outcomes and the effects of both short-term and long-term rotating shift work.

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Competing Interests

No conflicts of Interests

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Reviewer Report

32 Views

13 Jul 2023 | for Version 1

Tianpeng Zhang, Guangzhou University, Guangzhou, Guangdong, China

32 Views Cite this report Responses(1)

Approved With Reservations

Describe in detail the process for collecting skin, which part of the skin tissue was collected?
Is the selection of light intensity reasonable in the experiment? Multiple studies have shown that bright light can affect the circadian rhythm of activity, metabolism and clock gene expression (Bano-Otalora et al., 2021¹; Alves-Simoes et al., 2016²; Fan et al., 2022³). Meanwhile, the light intensity also affects the impact of chronic jet-lag.
More information should be provided on Circadian rhythm analysis, especially the setting of parameters.
Why use two housekeeping genes in the same tissue for clock gene relative quantification?
The author should discuss why Cry genes are preferentially altered under three light conditions.

Is the work clearly and accurately presented and does it cite the current literature?

Yes
Is the study design appropriate and is the work technically sound?

Yes
Are sufficient details of methods and analysis provided to allow replication by others?

Partly
If applicable, is the statistical analysis and its interpretation appropriate?

Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results?

Yes

References

Competing Interests

No competing interests were disclosed.

Reviewer Expertise

circadian clock and metabolism

Respond to this report

Responses (1)

Author Response

29 Aug 2023

SHOBHAN GADDAMEEDHI, Center for Human Health and the Environment, North Carolina State University, Raleigh, USA

Reviewer Comments

In this manuscript, Koritala et al. report that shift-work light affects the circadian rhythms of canonical clock genes in the liver and skin of mice. Although the authors have utilized multiple approaches to test their hypothesis, there remain areas where the methods section should also provide detailed information. Please refer to the following comments for more details.

1. Describe in detail the process for collecting skin, which part of the skin tissue was collected?
Authors' response: As per the suggestion of the reviewer, we have elaborated on the procedure of skin tissue collection within the 'Study Design and Sample Collection' section in our methods.

2. Is the selection of light intensity reasonable in the experiment? Multiple studies have shown that bright light can affect the circadian rhythm of activity, metabolism and clock gene expression (Bano-Otalora et al., 20211; Alves-Simoes et al., 20162; Fan et al., 20223). Meanwhile, the light intensity also affects the impact of chronic jet-lag.
Authors' response: Our study maintained similar light intensities across control and shift simulation groups to focus on shift impacts, thereby reducing potential variation from light intensity differences. However, recognizing the significance of light intensity on chronic jet-lag, we will consider incorporating this factor into future experimental designs, perhaps by comparing the effects of different light intensities on chronic jet-lag.

3. More information should be provided on Circadian rhythm analysis, especially the setting of parameters.
Authors' response: In response to the reviewer’s suggestion, we have clarified our use of the standard parameters of the CircaCompare R package (as per Parsons et al., Bioinformatics, 2020, PMID: 31588519). This approach includes a fixed period of 24 hours.

4. Why use two housekeeping genes in the same tissue for clock gene relative quantification?
Authors' response: Vandesompele et al. (Genome Biol. 2002, PMID: 12184808) showed that normalizing with the geometric mean of carefully chosen control genes improves qPCR accuracy. Using a single universal control gene is less effective due to variations across different cells or tissues. Moreover, fluctuations within standard housekeeping genes depending on the time of day have been recognized in studies (Kosir et al., BMC Mol Biol. 2010; PMID: 20712867). Thus, the utilization of more than one housekeeping gene minimizes this variability.

5.The author should discuss why Cry genes are preferentially altered under three light conditions.
Authors' response: In the discussion section of the revised manuscript, we covered the response of Cry genes to simulated shift conditions.

View more View less

Competing Interests

No conflicts of Interests

Alongside their report, reviewers assign a status to the article:

Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested

Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.

Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions

[1] 1. Wright KP Jr, McHill AW, Birks BR, et al.: Entrainment of the human circadian clock to the natural light-dark cycle. Curr. Biol. 2013 Aug 19; 23(16): 1554–1558. PubMed Abstract | Publisher Full Text | Free Full Text

[2] 2. Roenneberg T, Merrow M: The Circadian Clock and Human Health. Curr. Biol. 2016 May 23; 26(10): R432–R443. PubMed Abstract | Publisher Full Text

[3] 3. Costa G: Shift work and health: current problems and preventive actions. Saf. Health Work. 2010 Dec; 1(2): 112–123. PubMed Abstract | Publisher Full Text | Free Full Text

[4] 4. Lunn RM, Blask DE, Coogan AN, et al.: Health consequences of electric lighting practices in the modern world: A report on the National Toxicology Program’s workshop on shift work at night, artificial light at night, and circadian disruption. Sci. Total Environ. 2017 Dec 31; 607-608: 1073–1084. PubMed Abstract | Publisher Full Text | Free Full Text

[5] 5. James SM, Honn KA, Gaddameedhi S, et al.: Shift Work: Disrupted Circadian Rhythms and Sleep-Implications for Health and Well-Being. Curr. Sleep Med. Rep. 2017 Jun; 3(2): 104–112. PubMed Abstract | Publisher Full Text | Free Full Text

[6] 6. Kervezee L, Cuesta M, Cermakian N, et al.: Simulated night shift work induces circadian misalignment of the human peripheral blood mononuclear cell transcriptome. Proc. Natl. Acad. Sci. U. S. A. 2018 May 22; 115(21): 5540–5545. PubMed Abstract | Publisher Full Text | Free Full Text

[7] 7. Kervezee L, Cermakian N, Boivin DB: Individual metabolomic signatures of circadian misalignment during simulated night shifts in humans. PLoS Biol. 2019 Jun; 17(6): e3000303. Epub 2019/06/19. PubMed Abstract | Publisher Full Text | Free Full Text

[8] 8. Skene DJ, Skornyakov E, Chowdhury NR, et al.: Separation of circadian- and behavior-driven metabolite rhythms in humans provides a window on peripheral oscillators and metabolism. Proc. Natl. Acad. Sci. U. S. A. 2018 Jul 24; 115(30): 7825–7830. PubMed Abstract | Publisher Full Text | Free Full Text

[9] 9. Adams KL, Castanon-Cervantes O, Evans JA, et al.: Environmental circadian disruption elevates the IL-6 response to lipopolysaccharide in blood. J. Biol. Rhythm. 2013 Aug; 28(4): 272–277. PubMed Abstract | Publisher Full Text | Free Full Text

[10] 10. Lee Y, Lahens NF, Zhang S, et al.: G1/S cell cycle regulators mediate effects of circadian dysregulation on tumor growth and provide targets for timed anticancer treatment. PLoS Biol. 2019 Apr; 17(4): e3000228. Epub 2019/05/01. PubMed Abstract | Publisher Full Text | Free Full Text

[11] 11. McGowan NM, Coogan AN: Circadian and behavioural responses to shift work-like schedules of light/dark in the mouse. J. Mol. Psychiatry. 2013; 1(1): 7. Epub 2013/01/01. PubMed Abstract | Publisher Full Text | Free Full Text

[12] 12. Van Dycke KC, Rodenburg W, van Oostrom CT , et al.: Chronically Alternating Light Cycles Increase Breast Cancer Risk in Mice. Curr. Biol. 2015 Jul 20; 25(14): 1932–1937. PubMed Abstract | Publisher Full Text

[13] 13. Davidson AJ, Castanon-Cervantes O, Leise TL, et al.: Visualizing jet lag in the mouse suprachiasmatic nucleus and peripheral circadian timing system. Eur. J. Neurosci. 2009 Jan; 29(1): 171–180. PubMed Abstract | Publisher Full Text

[14] 14. Figueiro MG, Goo YH, Hogan R, et al.: Light-Dark Patterns Mirroring Shift Work Accelerate Atherosclerosis and Promote Vulnerable Lesion Phenotypes. J. Am. Heart Assoc. 2021 Jan 19; 10(2): e018151. Epub 2021/01/07. PubMed Abstract | Publisher Full Text | Free Full Text

[15] 15. Papagiannakopoulos T, Bauer MR, Davidson SM, et al.: Circadian Rhythm Disruption Promotes Lung Tumorigenesis. Cell Metab. 2016 Aug 9; 24(2): 324–331. PubMed Abstract | Publisher Full Text | Free Full Text

[16] 16. Lee S, Donehower LA, Herron AJ, et al.: Disrupting circadian homeostasis of sympathetic signaling promotes tumor development in mice. PLoS One. 2010 Jun 7; 5(6): e10995. Epub 2010/06/12. PubMed Abstract | Publisher Full Text | Free Full Text

[17] 17. Kettner NM, Voicu H, Finegold MJ, et al.: Circadian Homeostasis of Liver Metabolism Suppresses Hepatocarcinogenesis. Cancer Cell. 2016 Dec 12; 30(6): 909–924. PubMed Abstract | Publisher Full Text | Free Full Text

[18] 18. Aiello I, Fedele MLM, Roman F, et al.: Circadian disruption promotes tumor-immune microenvironment remodeling favoring tumor cell proliferation. Sci. Adv. 2020 Oct; 6(42). Epub 2020/10/16. PubMed Abstract | Publisher Full Text | Free Full Text

[19] 19. Thaiss CA, Zeevi D, Levy M, et al.: Transkingdom control of microbiota diurnal oscillations promotes metabolic homeostasis. Cell. 2014 Oct 23; 159(3): 514–529. PubMed Abstract | Publisher Full Text

[20] 20. Figueiro MG, Radetsky L, Plitnick B, et al.: Glucose tolerance in mice exposed to light-dark stimulus patterns mirroring dayshift and rotating shift schedules. Sci. Rep. 2017 Jan 12; 7: 40661. Epub 2017/01/13. PubMed Abstract | Publisher Full Text | Free Full Text

[21] 21. Christie S, Vincent AD, Li H, et al.: A rotating light cycle promotes weight gain and hepatic lipid storage in mice. Am. J. Physiol. Gastrointest. Liver Physiol. 2018 Dec 1; 315(6): G932–G942. PubMed Abstract | Publisher Full Text

[22] 22. Dakup PP, Porter KI, Gajula RP, et al.: The circadian clock protects against ionizing radiation-induced cardiotoxicity. FASEB J. 2020 Feb; 34(2): 3347–3358. PubMed Abstract | Publisher Full Text | Free Full Text

[23] 23. Dakup PP, Porter KI, Gaddameedhi S: The circadian clock protects against acute radiation-induced dermatitis. Toxicol. Appl. Pharmacol. 2020 Jul 15; 399: 115040. Epub 20200515. PubMed Abstract | Publisher Full Text

[24] 24. Bae K, Jin X, Maywood ES, et al.: Differential functions of mPer1, mPer2, and mPer3 in the SCN circadian clock. Neuron. 2001 May; 30(2): 525–536. PubMed Abstract | Publisher Full Text

[25] 25. Zwighaft Z, Reinke H, Asher G: The Liver in the Eyes of a Chronobiologist. J. Biol. Rhythm. 2016 Apr; 31(2): 115–124. PubMed Abstract | Publisher Full Text

[26] 26. Koike N, Yoo SH, Huang HC, et al.: Transcriptional architecture and chromatin landscape of the core circadian clock in mammals. Science. 2012 Oct 19; 338(6105): 349–354. PubMed Abstract | Publisher Full Text | Free Full Text

[27] 27. Rey G, Cesbron F, Rougemont J, et al.: Genome-wide and phase-specific DNA-binding rhythms of BMAL1 control circadian output functions in mouse liver. PLoS Biol. 2011 Feb; 9(2): e1000595. Epub 2011/03/03. PubMed Abstract | Publisher Full Text | Free Full Text

[28] 28. Reinke H, Asher G: Crosstalk between metabolism and circadian clocks. Nat. Rev. Mol. Cell Biol. 2019 Apr; 20(4): 227–241. PubMed Abstract | Publisher Full Text

[29] 29. Wu G, Ruben MD, Schmidt RE, et al.: Population-level rhythms in human skin with implications for circadian medicine. Proc. Natl. Acad. Sci. U. S. A. 2018 Nov 27; 115(48): 12313–12318. PubMed Abstract | Publisher Full Text | Free Full Text

[30] 30. Plikus MV, Andersen B: Skin as a window to body-clock time. Proc. Natl. Acad. Sci. U. S. A. 2018 Nov 27; 115(48): 12095–12097. PubMed Abstract | Publisher Full Text | Free Full Text

[31] 31. Wang H, van Spyk E , Liu Q, et al.: Time-Restricted Feeding Shifts the Skin Circadian Clock and Alters UVB-Induced DNA Damage. Cell Rep. 2017 Aug 1; 20(5): 1061–1072. PubMed Abstract | Publisher Full Text | Free Full Text

[32] 32. Vandesompele J, De Preter K, Pattyn F, et al.: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002 Jun 18; 3(7): RESEARCH0034. Epub 2002/08/20. PubMed Abstract | Publisher Full Text | Free Full Text

[33] 33. Svec D, Tichopad A, Novosadova V, et al.: How good is a PCR efficiency estimate: Recommendations for precise and robust qPCR efficiency assessments. Biomol. Detect Quantif. 2015 Mar; 3: 9–16. PubMed Abstract | Publisher Full Text | Free Full Text

[34] 34. Parsons R, Parsons R, Garner N, et al.: CircaCompare: a method to estimate and statistically support differences in mesor, amplitude and phase, between circadian rhythms. Bioinformatics. 2020 Feb 15; 36(4): 1208–1212. PubMed Abstract | Publisher Full Text

[35] 35. Hughes ME, Abruzzi KC, Allada R, et al.: Guidelines for Genome-Scale Analysis of Biological Rhythms. J. Biol. Rhythm. 2017 Oct; 32(5): 380–393. PubMed Abstract | Publisher Full Text | Free Full Text

[36] 36. Fritschi L, Glass DC, Heyworth JS, et al.: Hypotheses for mechanisms linking shiftwork and cancer. Med. Hypotheses. 2011 Sep; 77(3): 430–436. PubMed Abstract | Publisher Full Text

[37] 37. Panda S, Sato TK, Castrucci AM, et al.: Melanopsin (Opn4) requirement for normal light-induced circadian phase shifting. Science. 2002 Dec 13; 298(5601): 2213–2216. PubMed Abstract | Publisher Full Text

[38] 38. Buhr ED, Yue WW, Ren X, et al.: Neuropsin (OPN5)-mediated photoentrainment of local circadian oscillators in mammalian retina and cornea. Proc. Natl. Acad. Sci. U. S. A. 2015 Oct 20; 112(42): 13093–13098. PubMed Abstract | Publisher Full Text | Free Full Text

[39] 39. Buhr ED, Vemaraju S, Diaz N, et al.: Neuropsin (OPN5) Mediates Local Light-Dependent Induction of Circadian Clock Genes and Circadian Photoentrainment in Exposed Murine Skin. Curr. Biol. 2019 Oct 21; 29(20): 3478–3487.e4. PubMed Abstract | Publisher Full Text | Free Full Text

[40] 40. Damiola F, Le Minh N, Preitner N, et al.: Restricted feeding uncouples circadian oscillators in peripheral tissues from the central pacemaker in the suprachiasmatic nucleus. Genes Dev. 2000 Dec 1; 14(23): 2950–2961. PubMed Abstract | Publisher Full Text | Free Full Text

[41] 41. Stokkan KA, Yamazaki S, Tei H, et al.: Entrainment of the circadian clock in the liver by feeding. Science. 2001 Jan 19; 291(5503): 490–493. PubMed Abstract | Publisher Full Text

[42] 42. Koronowski KB, Kinouchi K, Welz PS, et al.: Defining the Independence of the Liver Circadian Clock. Cell. 2019 May 30; 177(6): 1448–1462.e14. PubMed Abstract | Publisher Full Text | Free Full Text

[43] 43. Suh S, Choi EH, Atanaskova MN: The expression of opsins in the human skin and its implications for photobiomodulation: A Systematic Review. Photodermatol. Photoimmunol. Photomed. 2020 Sep; 36(5): 329–338. PubMed Abstract | Publisher Full Text | Free Full Text

[44] 44. Papp SJ, Huber AL, Jordan SD, et al.: DNA damage shifts circadian clock time via Hausp-dependent Cry1 stabilization. elife. 2015 Mar 10; 4. Epub 20150310. PubMed Abstract | Publisher Full Text | Free Full Text

[45] 45. Ye R, Selby CP, Chiou YY, et al.: Dual modes of CLOCK:BMAL1 inhibition mediated by Cryptochrome and Period proteins in the mammalian circadian clock. Genes Dev. 2014 Sep 15; 28(18): 1989–1998. PubMed Abstract | Publisher Full Text | Free Full Text

[46] 46. Sancar A: Regulation of the mammalian circadian clock by cryptochrome. J. Biol. Chem. 2004 Aug 13; 279(33): 34079–34082. PubMed Abstract | Publisher Full Text

[47] 47. Thompson CL, Blaner WS, Van Gelder RN, et al.: Preservation of light signaling to the suprachiasmatic nucleus in vitamin A-deficient mice. Proc. Natl. Acad. Sci. U. S. A. 2001; 98: 11708–11713. PubMed Abstract | Publisher Full Text | Free Full Text

[48] 48. Thompson CL, Selby CP, Van Gelder RN, et al.: Effect of vitamin A depletion on nonvisual phototransduction pathways in cryptochromeless mice. J. Biol. Rhythms. 2004; 19: 504–517. PubMed Abstract | Publisher Full Text

[49] 49. Koritala BSC, Porter KI, Arshad OA, et al.: Night shift schedule causes circadian dysregulation of DNA repair genes and elevated DNA damage in humans. J. Pineal Res. 2021 Apr; 70(3): e12726. Epub 20210314. PubMed Abstract | Publisher Full Text | Free Full Text

[50] 50. Geyfman M, Kumar V, Liu Q, et al.: Brain and muscle Arnt-like protein-1 (BMAL1) controls circadian cell proliferation and susceptibility to UVB-induced DNA damage in the epidermis. Proc. Natl. Acad. Sci. U. S. A. 2012 Jul 17; 109(29): 11758–11763. PubMed Abstract | Publisher Full Text | Free Full Text

[51] 51. Sarkar S, Porter KI, Dakup PP, et al.: Circadian clock protein BMAL1 regulates melanogenesis through MITF in melanoma cells. Pigment Cell Melanoma Res. 2021 Sep; 34(5): 955–965. PubMed Abstract | Publisher Full Text | Free Full Text

[52] 52. Kosir R, Acimovic J, Golicnik M, et al.: Determination of reference genes for circadian studies in different tissues and mouse strains. BMC Mol. Biol. 2010 Aug 16; 11: 60. PubMed Abstract | Publisher Full Text | Free Full Text

[53] 53. Koritala BSC, Dakup PP, Porter KI, et al.: Cycle threshold values of qPCR data for genes in the liver and skin of animals that were exposed to both control and simulated shift conditions. [Dataset]. figshare. 2023. Publisher Full Text

[54] 54. Koritala B, Dakup PP, Porter KI, et al.: CircaCompare analysis of canonical clock genes in the mouse liver and skin following exposure to simulated shift-work light conditions. [Dataset]. figshare. 2023. Publisher Full Text

[55] 55. Koritala B, Dakup PP, Porter KI, et al.: Author Checklist - F1000 Research.pdf. figshare. 2023. Publisher Full Text

The impact of shift-work light conditions on tissue-specific circadian rhythms of canonical clock genes: insights from a mouse model study

Abstract

Keywords

Revised Amendments from Version 1

Introduction

Figure 1. Design of simulated shift-work light conditions for mice.

Methods

Ethics statement

Study design and sample collection

Gene expression analysis

Table 1. Primers used for measuring mRNA expression of canonical clock genes.

Circadian rhythm analysis

Results

Circadian analysis of canonical clock genes in the liver after exposure to simulated shift- work light conditions

Figure 2. Circadian rhythms of canonical clock genes in the liver following exposure to simulated shift-work light conditions.

Circadian analysis of canonical clock gene expression in the skin after exposure to simulated shift-work light conditions

Figure 3. Circadian rhythms of canonical clock genes in the skin following exposure to simulated shift-work light conditions.

Figure 4. Differential circadian properties of canonical clock genes in the liver and skin following exposure to simulated shift-work light conditions.

Discussion

Author contributions

Data availability

Underlying data

Extended data

Reporting guidelines

References

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