Chronic blue light-emitting diode exposure harvests gut dysbiosis related to cholesterol dysregulation

doi:10.21203/rs.3.rs-1936247/v1

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Chronic blue light-emitting diode exposure harvests gut dysbiosis related to cholesterol dysregulation

https://doi.org/10.21203/rs.3.rs-1936247/v1

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Background

Night shift workers may be associated with circadian dysregulation and metabolic diseases. Mounting evidences illuminate that gut microbiota, circadian clock, and metabolic system are tightly co-evolved. In regarding with artificial light at night (ALAN) has been linking to circadian disruption and causal metabolic diseases, the present study therefore aims to explore the impact of chronic exposure of specific type and different exposing time of light-emitting diodes (LEDs) on the gut microbiota and associated physiological changes.

Results

Male C57BL/6 mice were exposed to blue or white LED lighting at two exposure time (i.e., 3.6J/cm² or 7.2J/cm²) from 11 to 44 weeks at ZT13.5-14. 16S rRNA sequencing was used to analyze related gut microbial compositions. Blue LED lighting specifically decreased alpha diversity at both 27 and 44 weeks (p = 0.007 and 0.013). Low dosage of both types of LED lighting did not cause significant changes of microbial compositions. Furthermore, the low irradiance of both blue and white LED illuminations significantly increased serum cholesterol, but not triglyceride. The ratio of beneficial to harmful bacteria was significantly increased at a high irradiance of blue light. This ratio was negatively correlated with serum cholesterol but positively correlated with bile acid biosynthesis.

Conclusion

Our results revealed that chronic blue LED lighting would promote gut dysbiosis and dysregulate cholesterol metabolism without any additional confounding factors. In addition, the effects of chronic blue LED lighting on shaping gut microbiota in response to optic stress through the brain-gut axis shed a new insight into the link between the host and gut microorganisms to circadian clock and cholesterol metabolism.

Chronic LED

Dysbiosis

Cholesterol dysregulation

Circadian rhythm (CR) refers to an endogenous process that regulates the repeated timing of physiological function [1–3], and also ensures that one’s internal physiology is synchronized with external environment [4]. In mammals, the suprachiasmatic nucleus (SCN) is the “master clock” responsible for coordinating and synchronizing daily rhythm via transmitting signals to other clocks in peripheral organs [5]. External environmental cues such as light can train the CR to be synchronized with the light–dark (LD) cycle through the circadian clock [6–8]. Light information can be transmitted by the retino-hypothalamic tract linking the eye to the SCN [9]. The non-visual effects of light such as CR regulation are mediated by a retinal photoreceptor system built from the intrinsically photosensitive retinal ganglion cells (ipRGC) [10, 11]. In these unique ipRGC cells, the triggering signal transduction is accomplished by the photopigment melanopsin, which shows maximum sensitivity to the blue, i.e., short wavelength, part of the spectrum (∼480 nm) [12, 13]. Although the genes involved in maintaining the CR drive many biological pathways, they are particularly relevant in metabolism [14, 15]. Therefore, following CR disruption, the metabolism and energy networks consequently become imbalanced, resulting in disorders such as obesity [16, 17]. CR can also regulate hepatic lipid metabolism and thus the disruption of CR can further result in the dysregulation of serum lipid [18]. It is Important to note that abnormal cholesterol rather than triglyceride metabolism is suggested to be a critical event in the pathogenesis of metabolic syndrome [19, 20], and hypercholesterolemia seems to be one of the most important risk factors involved in cardiovascular disease (CVD), coronary heart disease, and type 2 diabetes [21, 22].

Light-emitting diodes (LEDs) are widely used in electronic devices and are recognized as a major source of circadian dysregulation in modern society. The overuse of these devices has been increasingly linked to sedentary behavior at home [23], which presents a cardio-metabolic risk [24]. Although the light emitted by most of LEDs appears to be white, LEDs have a peak emission in the blue color range [25]. In humans, circadian responses to light are most sensitive to blue light [26–29]. Men show a strong response to blue light in the late evening, even at very low levels, compared to women [30]. Artificial light at night (ALAN) is associated with a higher risk of CVD [31, 32]. Most studies have indicated the effects of ALAN on the disruption of metabolic processes, resulting in obesity or diabetes and cancer incidence [33]. Nightshift work is also associated with a range of adverse health outcomes such as metabolic diseases[34]. Interestingly, on the other hand, blue light can be filtered out in electronic screens during the night [35, 36], and blue-enriched light is used by nightshift workers to optimize their body rhythm for achieving maximum performance [37–39]. In addition, the long-term reduction of short-wavelength light reduces sustained attention and visuospatial working memory but there is no evidence that it causes a change in circadian rhythmicity [40]. The chronic impacts of blue LED lighting on health as well as the metabolism remain to be investigated.

Mounting evidence has revealed that the gut microbiota, the circadian clock, and the metabolic system are tightly co-evolved [6–8, 41, 42]. Although gut microbes are not directly exposed to light, diurnal host signals can induce oscillations in both the abundance and function of gut bacteria [42–44]. Emerging research has also demonstrated that gut microbes are capable of programming the host’s energy balance, such as lipid absorption and storage, and have a major impact on metabolic homeostasis [45, 46]. Moreover, gut microbiota are very sensitive to environmental changes, including dietary and physiological, changes, and exhibit rapid responses in both community members and functions, effects that can quickly feedback onto the host’s health outcomes [47–49]. Gut dysbiosis is a health outcome in which biodiversity is strongly reduced and the microbial action becomes progressively pro-inflammatory and detrimental to human health [50, 51]. In contrast, eubiosis is characterized by a high biodiversity, a harmonic inter-microbial condition and mutualistic relationship between the microbiota and the host. A eubiotic state can be recognized as having a “balanced” between beneficial and harmful bacteria [52, 53]. An increased ratio of beneficial to harmful bacteria can improve gut dysbiosis-related disorders, even with the administration of probiotics such as Lactobacillus species [54]. Similar probiotic approaches could be used to correct, re-establish, or maintain appropriate rhythm in the gut flora population. Animal studies have suggested that circadian disruption, similar to that in shift workers, contributes to the development of gastrointestinal complaints among shift workers by altering the composition and normal diurnal rhythmicity of the resident intestinal microbes [55]. Although some studies have pointed out no differences in the composition of the fecal microbiome between lean and obese individuals [56, 57], other studies in humans show that Firmicutes are associated with a higher propensity for obesity and metabolic disease [56, 58], conditions that are more common in night and rotating shift workers [55, 59]. The environmental disruption of mouse and human CR by phase-shifting LD cycles and jet lag across time zones, respectively, significantly altered 24-hour bacterial patterning. It can be proposed that the chronic exposure to LEDs’ illumination might disrupt CR and associated gut microbiota, harvesting a diseased niche in the gut and changing metabolic homeostasis. However, the information about long-lasting/chronic effects of artificial light (in particular a specific wavelength of LEDs) on the gut microbiota and metabolic changes is limited.

In the present study, we employed a mouse model to ascertain the chronic effects of blue and white LED lighting with a low and high irradiance on the gut microbiota and associated serum lipids. We found chronic blue LED lighting in particular decreased microbial ⍺ diversity and modulated the abundances and ratio of a specific set of gut microbes, causing increased serum total cholesterol, but not triglyceride, in mice. Our results revealed that chronic blue LED lighting would harvest gut dysbiosis in relation to cholesterol dysregulation through the disruption of CR and bile acid biosynthesis.

Chronic LED light exposure reduced the α-diversity of gut microbiota.

To explore the impacts of the chronic irradiance of blue and white LED light, mice were set under a dark phase and randomly categorized into four groups, including a native control group without a cage shift and LED lighting, and experimental groups receiving two regular and fixed exposure times of blue and white LED lighting from 11 weeks to 44 weeks. A long exposure time/high irradiance (7.2 J/cm²) of blue LED light significantly decreased the α-diversity of fecal microbiota as compared with the matched control group at both 27 and 44 weeks (p = 0.007 and 0.013, respectively; Fig. 1A). Chronic white LED lighting decreased the microbial α-diversity only at high irradiance and at 27 weeks (p = 0.020, Fig. 1A). It is noted that the lower α-diversity of the gut microbiota is associated with several diseases including obesity, diabetes, and colorectal cancer [60–62].

The β-diversity of the microbial compositions was not significantly different between each group when using Principal Coordinate Analysis (PCoA) with the weighted UniFrac distance method (Fig. 1B). However, it is noted that the microbial compositions of each group were obviously separated at 44 weeks (Fig. 1B). These results implied that high irradiance and a long time period were required for the LED lighting-mediated compositional change in the gut microbes. In addition, chronic exposure to blue LED lighting decreased the α-diversity of the gut microbiota, suggesting that chronic blue LED lighting might harvest a diseased niche such as gut dysbiosis.

Chronic LED lighting mainly changed the abundance of lipid metabolism-related gut microbes.

Circadian dysregulation has been regarded as one of the risk factors for a wide spectrum of diseases such as metabolic syndrome [63]. Circadian disruption and consequent dysregulation by chronic LED lighting might be associated with gut dysbiosis as shown above (Fig. 1). The LEfSe and heatmap abundance analysis were used to explore the critical bacteria changed by chronic LED lighting (Additional file: Fig. 1). It was noted that the low exposure time of both types of chronic LED lighting could not make significant changes in the microbial compositions at 27 weeks (data not shown). Intriguingly, 15 to 19 bacteria detected from LEfSe and heatmaps were related to lipid metabolism according to the Kyoto Encyclopedia of Genes and Genomes (KEGG), level 2 (15/19, in yellow) and other pathways (4/19, in black) (Fig. 2). Interestingly, after the high irradiance of blue LED light at 44 weeks, compared to the matched control, Akkermansia muciniphila, well-known third generation probiotics, were increased (p = 0.037, Fig. 2A), while Ruminococcus spp. and Oscillospira spp. were found to be reduced at a high level of irradiance of blue LED light (p = 0.031 and 0.008, respectively; Fig. 2B). Aldercreutzia spp. and Clostridium spp. could be induced (p = 0.007 and 0.049, Fig. 2B), whereas Dehalobacterium spp. were reduced by a high irradiance of white LED light (p = 0.010, Fig. 2B). A high irradiance of both types of LED lighting could signify that chronic LED lighting would change the composition of gut microbiota by specific wavelengths of LED lighting.

These critical bacteria altered by chronic LED lighting might be merely a reflection of the aging process and other experimental factors such as cage shift. Therefore, in order to adjust the potential impacts of aging and the movement of the cage, the composition of gut microbiota at 11, 27 and 44 weeks of the native control (NC), control (i.e., the cage shift without LED lighting on), and various LED lighting treatment group were rearranged and compared in Additional file: Fig. 2. Ruminococcus spp. and Bacteroides spp. increased as the weeks increased (p < 0.001 and 0.008, respectively; Additional file: Fig. 2). Both low and high irradiances of blue and white LED lighting on Bacteroides spp. were similar to those seen in the native control. The abundances of Oscillospira spp. and Rumincoccus spp. were both reduced in the group with high irradiance of blue LED lighting along with increasing age/exposure time (p = 0.002 and 0.001, respectively; Additional file: Fig. 2). In contrast, Allobaculum spp. were increased in the group with high irradiance of blue LED lighting along with aging (p = 0.003, Additional file: Fig. 2). In short, both types of LED lighting harvested gut dysbiosis with altered abundances of some overlapping and other distinct specific bacteria. However, the change in the core bacteria by chronic LED lighting was not a result of the aging and cage shift in our study, because there was an increasing trend in Turicibacter spp. (p = 0.028 and 0.004, Fig. 2B). Dorea spp. were the only bacteria induced at low irradiance of white LED light (p = 0.021, Fig. 2B). These findings on chronic LED lighting were not in alignment with the trends related to aging.

Chronic blue LED lighting-induced gut dysbiosis resulted in alterations in serum cholesterol but not triglyceride.

To further examine the impacts of chronic blue and white LED lighting on metabolic homeostasis, the blood of each mouse was collected after 183 times of LED light exposure at 44 weeks. Intriguingly, chronic LED lighting at low irradiance, but not at a high irradiance, caused impacts specifically on serum total cholesterol (TCHO) but not triglyceride (TG) or glucose levels in mice. The low irradiance of both chronic blue and white LED lighting increased TCHO but not TG levels (p = 0.029 and 0.033, respectively; Table 1).

Table 1

Blood biochemistry in the mice exposed to various irradiances of LED lighting after 44 weeks.
Group (J/cm²)	Cholesterol (mg/dL)	Triglyceride (mg/dL)	Glucose (mg/dL)
C-3.6	85.5 ± 1.5	39.0 ± 15.0	175.0 ± 24.0
B-3.6	95.9* ± 2.3	49.8 ± 13.4	172.8 ± 25.5
W-3.6	119.0* ± 1.5	64.0 ± 9.5	199.0 ± 26.7
C-7.2	87.7 ± 3.5	60.3 ± 9.4	179.3 ± 7.4
B-7.2	86.7 ± 5.6	67.9 ± 2.7	202.8 ± 17.8
W-7.2	82.5 ± 10.9	56.6 ± 13.5	267.5 ± 43.7
NC	98.7 ± 4.4	54.5 ± 12.0	256.4 ± 10.5
* Indicated p < 0.05 as compared to C-3.6 J. Mean ± SEM

Chronic blue LED lighting changed the ratio of beneficial to harmful bacteria in a specific set, altering serum TCHO levels.

To explore why a low, but not a high, irradiance of chronic LED lighting altered the levels of blood lipid (Fig. 3A), the Venn diagram plot was used and showed that four genera were independently involved in circadian regulation and ten genera were independently included in cholesterol metabolism. There were six genera intersected in both circadian regulation- and cholesterol metabolism-related gut bacteria (Fig. 3A). To see the dynamic balance between the catabolism and biosynthesis of cholesterol metabolism as well as between light and dark phase/induced CR regulation, the ratio of catabolism and biosynthesis was specifically analyzed in cholesterol metabolism-related bacteria between groups (Fig. 3B-1), and the ratio of light and dark induction was specifically analyzed in CR regulation-related bacteria between groups (Fig. 3B-1). The ratio of catabolism-related bacteria (i.e., Bifidobacterium, Akkermansia, Adlercreutzia, Allobaculum, rc4-4, and Mucispirillum spp.) to biosynthesis-related (i.e., Bacteroides, and Turicibacter) bacteria with a focus on cholesterol-related metabolism, which was determined from the KEGG, was increased only after a high irradiance of chronic blue LED lighting in mice (p = 0.007, Fig. 3B-1). The ratio of light phase-induced bacteria (i.e., Dehalobacterium) to dark phase-induced bacteria (i.e., Dorea and Anaerotruncus spp.), however, was not significantly different at both a low and high irradiance of chronic blue LED lighting, but was decreased at a high irradiance of chronic white LED lighting (Fig. 3C-1). Decreased beneficial bacteria and/or increased harmful or pathogenic bacteria can result in diseased conditions. Since it is hard to dissect six intersected genera into cholesterol metabolism or CR regulation, the ratio of beneficial (i.e., Lactobacillus, Coprococcus and Anaerostipes spp.) to harmful (i.e., Ruminococcus, Clostridium, and Anaeroplasma spp.) bacteria was determined. Intriguingly, there was decrease in the ratio of beneficial to harmful gut bacteria was decreased after a low irradiance of chronic blue LED lighting (p = 0.001, Fig. 3D-1) but there was an increase in the ratio at a high irradiance (p = 0.016, Fig. 3D-1). In the composition of cholesterol metabolism, cholesterol catabolism-related bacteria could be induced after a high irradiance of chronic blue LED lighting (p = 0.020, Fig. 3B-2). Additionally, dark phase-induced bacteria were reduced after a high irradiance of chronic blue LED lighting (p = 0.004, Fig. 3C-2). Importantly, harmful bacteria were found to be significantly increased at a low irradiance of blue LED lighting (p = 0.040, Fig. 3D-2). Beneficial bacteria, however, were not changed at low irradiance of chronic blue LED lighting, but were dramatically increased after a high irradiance of both blue and white LED lighting (p = 0.011 and 0.002, respectively, Fig. 3D-2). These results might indicate that a high irradiance of chronic blue LED lighting would increase beneficial bacteria to facilitate cholesterol catabolism. The correlations between the obtained microbial biomarkers with blood cholesterol in mice were further analyzed using Spearman’s correlation. Single bacteria, however, did not show any significant correlation with serum TCHO (Additional file: Fig. 3). It is important to note that the ratio of beneficial to harmful gut bacteria was significantly and inversely correlated with serum TCHO, but not TG levels (p = 0.041, Fig. 3E). Serum TG levels were also analyzed using the same strategy. The Venn diagram plot showed that two genera were independently involved in circadian regulation and nine genera were independently included in triglyceride metabolism (Fig. 4A). There were eight genera intersected in both circadian regulation- and triglyceride metabolism-related gut bacteria (Fig. 4A). Chronic white LED lighting significantly decreased the ratio of the catabolism (i.e., Bifidobacterium, Akkermansia, Bacteroides, Adlercreutzia and Parabacteroides spp.) to the synthesis (i.e., Allobaculum, Turicibacter, Mucispirillum and Corprobacillus spp.) of triglycerides at high irradiance (p = 0.007, Fig. 4B-1). Both bacteria related to the catabolism and synthesis of triglycerides were increased at high irradiance (Fig. 4B-2). In circadian regulation-related bacteria, the ratio of light (i.e., Clostridium spp.)- to dark (i.e., Anaerotruncus spp.)-induced bacteria was dramatically increased at a high irradiance of both blue and white LED lighting but did not reach statistical significance (Fig. 4C-1). Light-induced bacteria were increased at a high irradiance of white LED lighting (p = 0.049, Fig. 4C-1). There was no significant difference in the ratio of beneficial to harmful bacteria upon exposure to chronic LED lighting regardless of low and high irradiance (Fig. 4D). Both beneficial (i.e., Coprococcus, Lactobacillus, Anaerostipes, and Oscillospira spp.) and harmful (i.e., Ruminococcus, Dehalobacterium, Dorea and Anaeeroplasma spp.) bacteria intersected between circadian regulation and triglyceride metabolism were significantly decreased at a high irradiance of blue LED lighting (p = 0.024 and 0.025, respectively; Fig. 4E). In short, a high irradiance of chronic blue LED lighting triggered a dramatic increase in the ratio of beneficial to harmful gut bacteria at high irradiance, which might antagonize a heavier optic stress-related CR disruption.

Chronic blue LED lighting changed the ratio of beneficial to harmful bacteria which was positively correlated with bile acid biosynthesis.

There were 12 and 13 function pathways associated with beneficial and harmful bacteria, respectively (Additional file: Fig. 4). Three pathways were regulated by both beneficial and harmful bacteria (Fig. 5A). Primary and secondary bile acid biosynthesis showed a positive correlation with the ratio of beneficial to harmful bacteria (r = 0.796, p < 0.001, Fig. 5B). The synthesis and degradation of ketone bodies, however, were negatively correlated with the ratio of beneficial to harmful bacteria (r = − 0.788, p < 0.001, Fig. 5B). Bile acid biosynthesis pathways (both primary and secondary bile acid biosynthesis) were significantly increased after a high irradiance of blue LED lighting compared to the control (both p = 0.023, Fig. 5B). It is noted that bile acids were synthesized from cholesterol in the liver [64]. Increased bile acid biosynthesis might be the key regulator in serum TCHO after a high irradiance of blue LED lighting. Although there was broader significance, these two pathways showed an inverse correlation with serum TCHO, suggesting that beneficial bacteria might activate primary and secondary bile acid biosynthesis and in turn down-regulate serum TCHO levels in mice. In summary, a low irradiance of chronic blue LED lighting could increase serum TCHO levels and also promoted an increase in harmful bacteria. A high irradiance of chronic blue LED lighting would enrich beneficial bacteria to facilitate cholesterol catabolism through inducing primary and secondary bile acid biosynthesis. These phenomena would protect the host from the risk of cardiovascular disease in relation to the elevation of serum TCHO levels. Paste your results here.

Circadian disruption has been linked to metabolic diseases such as obesity [65] and type 2 diabetes [66, 67]. Circadian disruption may cause gut dysbiosis and subsequently result in disease status. In regard to e-readers and smartphones, which are mostly composed of LED-based technology, we therefore investigated the impacts of chronic exposure to white and blue LED lighting on gut microbiota and serum lipids in mice. Notably, the term ‘chronic’ is applied when the course of the disease lasts for more than three months in humans [68]. We found that chronic, persistent exposure of more than three months, with a high irradiance of blue LED light significantly decreased α-diversity, but not β-diversity, after 44 weeks. Notably, the weighted UniFrac distance of the microbial community had been distinctly separated until 44 weeks (Fig. 1). It has been reported that 33 weeks in adult mice is about 18.84 years in the life of a human adult [69]. Since each microbial community presented a dissimilarity, a short period of LED lighting might not be able to sufficiently determine a disease-related dysbiosis. The α-diversity of microbes can be described by their richness and evenness [70, 71]. Increased α-diversity provides benefits such as lower weight gain, decreased inflammatory mediators, and harvesting a healthier gastrointestinal environment [61, 72, 73], whereas a lower α-diversity of the gut microbiota is associated with such disorders and diseases as obesity, diabetes, colorectal cancer and children suffering from epilepsy [60, 61, 74]. It is noted that a high irradiance of blue LED light also significantly decreased the α-diversity at 27 weeks. Chronic exposure to blue LED lighting might harvest the niche of metabolic disorders and may also increase an inflammatory gut environment early, at least in mice.

Although most studies have proposed that a short period of light-mediated circadian dysregulation is linked to glucose dysregulation and insulin resistance [41, 75, 76], there is still an absence of information regarding the impacts of a long-lasting (up to a decade) of exposure to LED lighting on human health. Night shift workers may serve as a reference template. The frequency of night shifts appears to affect short-term physiological effects and is suggested to also affect long-term health [77]. A higher number of night shifts per month has been found to be positively associated with obesity [78–80]. However, people working longer than 20 years in night shift work appear to have a lower level of LDL cholesterol and showed a decrease in the rates of overweightness and obesity [81, 82]. We have no idea which heath problem (perhaps metabolic disorders, either glucose or lipid) will be caused by a very long time of exposure to LED lighting in humans and in mice. Our results revealed that most of the bacteria (15/19) altered by chronic LED lighting were related to lipid metabolism. Accordingly, chronic LED lighting specifically alters serum lipid but not glucose levels in mice. We found that, a low irradiance of both chronic blue and white LED lighting significantly increased TCHO but not TG levels (Table 1). It is important to note that white LED light consists of 19 ~ 21% of blue light [83]. In this experiment, white LED containing 17.4% of blue light was used. Hence, when the microbial abundance was altered by both white and blue LED light, it is rational that the impacts of blue LED light are dominant on the abundance of specific microbiomes if significant result were present in blue LED light-mediated alterations.

Our results revealed that chronic LED lighting would significantly change the abundances of eight gut bacteria by specific wavelengths of LED lighting among 19 gut microbes. Akkermansia muciniphila were increased, but Ruminococcus spp. and Oscillospira spp. were both reduced at a high irradiance of blue LED light (Fig. 2A and 2B). Aldercreutzia spp. and Clostridium spp. could be increased (Fig. 2B), whereas Dehalobacterium spp. were reduced by a high irradiance of white LED light (Fig. 2B). On the other hand, a high irradiance of both blue and white LED light could significantly increase Turicibacter spp. (Fig. 2B). Dorea spp. were the only bacteria induced at a low irradiance of white LED light (Fig. 2B). Although these critical bacteria might reflect the aging process or were modulated by experimental factors such as cage shifts, our results showed that the change in the core bacteria due to chronic LED lighting was not the result of aging and cage shifts because the trend upon chronic LED lighting trend was not in alignment with the trends related to aging. For example, Ruminococcus spp. were increased along with increasing weeks/age, but reduced at a high irradiance of blue LED lighting (Additional file: Fig. 2). Therefore, blue LED lighting might in major contribute to the reduced abundance of Ruminococcus spp., which are also less abundant in people with inflammatory bowel disease (IBD) [84] and in patients with Parkinson's disease [85]. Taken together, chronic blue LED lighting might contribute to inflammatory disease through its inhibitory modulation of the abundance of beneficial Ruminococcus spp. Similar observations were also evident in Oscillospira spp. Oscillospira have been positively associated with leanness and health, and are enriched in non-obese individuals and reduced in individuals with inflammatory disease [86, 87]. These results suggest that chronic exposure to LED lighting, in particular blue LED light, may contribute to metabolic syndrome and inflammatory niches in the gut. Nevertheless, it is noted that the ratio of light-to-dark-induced bacteria, in relation to neither cholesterol nor triglyceride metabolism, was not significantly different at both low and high level of irradiance of chronic blue LED lighting (Figs. 3 and 4). Intriguingly, Lactobacillus siliginis were dramatically decreased at a low irradiance of blue LED lighting but were elevated after high irradiance (Additional file: Fig. 5). Lactobacillus hayakitensis, however, showed a significant increase at a high irradiance of both blue and white LED lighting (Additional file: Fig. 5). These results imply that Lactobacillus spp. might be beneficial to hypercholesteremia induced by LED lighting-related CR dysregulation. Additionally noted, Lactobacillus are the only beneficial bacteria responsible for the catabolism of both lipids, cholesterol and triglycerides, and can be induced by light at the same time (Fig. 3A and 4A). Chronic blue LED lighting might enrich their abundance (Fig. 2A) to tune CR disruption. It has been suggested that blue-enriched light can be used by nightshift workers to optimize their body rhythm [37–39].

Our results revealed that a low irradiance of both blue and white LED light could increase serum TCHO (Table 1). The ratio of cholesterol catabolism to biosynthesis-related bacteria was significantly increased after a high irradiance of chronic blue LED lighting (Fig. 3B-1) and cholesterol catabolism-related bacteria were concomitantly upregulated (Fig. 3B-2). The ratio of light to dark-induced bacteria was not significantly different at both low and high level of irradiance of blue LED lighting, but was significantly decreased at a high irradiance of white LED lighting (Fig. 3C-1). There were six genera intersected in both circadian regulation- and cholesterol metabolism-related gut bacteria. Single bacteria did not show any significant correlation with serum TCHO (Additional file: Fig. 3). It was found that the ratio of beneficial to harmful bacteria in six bacteria was decreased after a low irradiance of chronic blue LED lighting, whereas this ratio was significantly increased at high irradiance of blue LED lighting (Fig. 3D-1). Notably, harmful bacteria were found to be increased at a low irradiance of blue LED lighting (Fig. 3D-2). Importantly, the reduced ratio of beneficial to harmful gut bacteria was significantly and inversely correlated with serum TCHO (Fig. 3E). These results suggested that a high irradiance of chronic blue LED lighting could increase beneficial bacteria to facilitate cholesterol catabolism. On the other hand, chronic white LED lighting significantly decreased the ratio of catabolism to the synthesis of triglyceride at high irradiance (Fig. 4B-1), but these bacteria related to catabolism and the synthesis of triglyceride were both increased at a high irradiance of blue LED lighting (Fig. 4B-2), leading to the misalignment of blue and white LED lighting on triglyceride metabolism. Both beneficial and harmful bacteria intersected between circadian regulation and triglyceride metabolism were significantly decreased only at a high irradiance of blue LED lighting (Fig. 4D-2), but there was no significant difference in the ratio of beneficial to harmful bacteria upon chronic LED lighting (Fig. 4E). Our results strengthen the consensus that there is a complex inter-bacteria network, and not only a single bacterium, in the modulation of metabolism homeostasis between microorganisms and the host; this can be seen in the Firmicutes to Bacteroidetes (F/B) ratio, which contributes to a dozens of diseases, such as obesity, and inflammatory bowel diseases [88]. More intriguingly, both primary and secondary bile acid biosynthesis were positively correlated with the ratio of beneficial to harmful bacteria (Fig. 5). Both primary and secondary bile acid biosynthesis were significantly increased after a high irradiance of blue LED lighting (Fig. 5C). There were borderline negatively significant correlations between bile acid synthesis serum TCHO. Taken together, a low irradiance of chronic blue LED lighting promoted an increase in harmful bacteria leading to a lower beneficial to harmful bacteria ratio which resulted in the upregulation of serum TCHO levels through reduced bile acid synthesis, as demonstrated in Table 1. Furthermore, a high irradiance of chronic blue LED lighting enriched beneficial bacteria to facilitate cholesterol catabolism through increased bile acid biosynthesis. As bacterial enzymes that conjugate bile acids vary according to bacterial strain, the microbial community is a key determinant of bile acid pool size and composition [89, 90]. Bile acids themselves also affect the composition of the gut microbiome, via direct detergent effects on bacteria as well as effects on intestinal mucosa integrity [91]. A previous study showed that the antioxidant tempol preferentially reduced the relative abundance of the Lactobacillus genus, decreased bile salt hydrolase (BSH) activity, and led to changes in bile acids composition that ultimately improved obesity [92].

In summary, chronic blue LED lighting might harvest gut dysbiosis through the brain-gut axis (Additional file: Fig. 6). Our novel findings included: (1) a high irradiance of blue LED lighting decreased alpha diversity; (2) at low irradiance, chronic blue LED lighting increased the abundance of harmful bacteria, leading to a decreased ratio of beneficial to harmful bacteria, and might subsequently increase serum cholesterol levels; (3) at high irradiance, chronic blue LED lighting increased beneficial bacteria as well as the ratio of beneficial to harmful bacteria which in turn reduced serum TCHO; and (4) the ratio of beneficial to harmful bacteria was negatively correlated with serum TCHO but was positively correlated with bile acid biosynthesis. Our results showed for the first time that chronic blue LED lighting could harvest gut dysbiosis and specifically dysregulate cholesterol metabolism in mice. The results of our study provide a theoretical basis for the idea that long-lasting exposure to blue LED lighting at night plays a predisposing role in inducing hypercholesterinemia-related disorders in humans.

Animals. Wild-type male C57BL/6 mice were purchased from the National Laboratory Animal Center, National Applied Research Laboratories, Taiwan. Mice were housed in a temperature (22–26 ℃)- and humidity (40–60%)-controlled room with a 12 hours light/12 hours dark cycle. Food and water were supplied ad libitum accessing to normal chow. All animal protocols were approved by the Institutional Animal Care and Use Committee of the National Health Research Institutes accredited by the AAALAC International (Protocol No: NHRI-IACUC-104125AE).

Light irradiation. Two customized light boxes with light-emitting diodes (LED) of adjustable light intensity on the ceiling were used. LEDs of blue light (473 ± 12.0 nm, and white light (containing about 17.4% blue light) were used in this study. 9-week-old mice were randomly assigned to 4 groups (NC: in the origin cage; C: move to the light box without light; W-3.6J/7.2J: 3.6 J/cm2 or 7.2 J/cm2 of white light irradiation for 1hr/2hrs; B-3.6J/7.2J: 3.6 J/cm2 or 7.2 J/cm2 of blue light irradiation for 1hr/2hrs) and allowed to adopt the environment for 2 weeks. Mice were exposed five days a week to the blue light irradiation (3.6 J/cm2 or 7.2 J/cm2, each N = 3, total N = 6) or to the white light irradiation (3.6 J/cm2 or 7.2 J/cm2, each N = 3, total N = 6) at ZT13.5-14 being equal to AM 9:30 − 10:00 under un-anesthetized condition. Mice given the same treatments without the light on was defined as the control group (C, N = 3) and in the origin cage without movement was defined as the negative control group (NC, N = 3).

16s v3v4 rDNA Amplicon Sequencing. Fecal samples were collected at ZT18 being equal to PM 2:00 and all specimens were extracted using Qiagen DNA kit according to the manufacturer’s instructions. DNA samples with OD 260/280 in the range of 1.8 ~ 2.0 for further 16s rDNA amplicon PCR. 16S rDNA PCR was using metagenomic DNA as template was amplified with the bacterial-specific primers S17 (5’-TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CCT ACG GGN GGC WGC AG-3’) and A21 (5’-GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACA GGA CTA CHV GGG TAT CTA ATC C-3’). The amplified DNA sizing was checked by Fragment Analyzer M5330AA (Agilent Technologies). Sequencing was carried out by Illumina MiSeq platform. DNA samples were attached indices and Illumina sequencing adapters using the Nextera XT Index Kit. After library construction, samples were mixed with MiSeq Reagent Kit v3 (600-cycle) and loaded onto a MiSeq cartridge, then onto the instrument. Automated cluster generation and a 2x300 bp paired-end sequencing run was performed. The sequences generated went through a filtering process to obtain the qualified reads. Total reads were merged, remove low-quality sequence, remove chimera sequence and cluster OTU at 97% similarity with the Greengenes database (v13.8). All OTU sequences and diversity analysis were using CLC Microbial Genomics Module (v10.0, Qiagen, Germany), BaseSpace (Illumina, USA) and Graphpad prism 9 (v9.1.1 Graphpad Software, USA).

Bioinformatics analysis. Bioinformatics was performed using the CLC Microbial Genomics Module. Alpha diversity was measured using Shannon index, which calculates the overall diversity of each group including the number of observed species (Richness) and how evenly of observed taxonomic (Evenness). Beta diversity was measured using PCoA-Weighted UniFrac, which determines the difference of microbial composition between groups. Hierarchical clustering of the top 25 abundance of OTU taxonomic were deduced using a heatmap to determine distribution patterns between groups. OTU table was generated by CLC Microbial Genomics Module and further analyzed with Linear discriminant analysis Effect Size (LEfSe) and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis. LEfSe was performed by website of Galaxy/HutLab to identify specific microbial markers between groups with an alpha value for the factorial Kruskal-Wallis test/ pairwise Wilcoxon test of 0.05 and LDA score cut-off of 2.0. PICRUSt prediction was performed by website of Galaxy according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) functional pathways database and analyzed with Statistical Analysis of Metagenomic Profiles (STAMP, v2.1.3) software. The criteria of STAMP were set up with remove unclassified reads, p < 0.01, and effect size 0.2. The results revealed those functional pathways with a significantly different abundance at level 3 between groups. Spearman’s correlation and principal component analysis (PCA) were utilized by R language (v4.0.2). Comparison of different groups was performed by t test with two-tailed. A p value less than 0.05 were considered statistically significant.

Statistics analysis. Statistical analysis was also performed using Microsoft Excel software and GraphPad Prism software (v9.1.1 Graphpad Software, USA). Graphs and tables represent mean ± standard error of mean (SEM) obtained from two or three independent experiments and collected from 3 animals. Differences were evaluated using one-way ANOVA. Multiple comparison was performed by Duncan's new multiple range test (MRT). Results with p values of less than 0.05 were considered significant.

Ethics approval and Consent to participate

All animal protocols were approved by the Institutional Animal Care and Use Committee of the National Health Research Institutes accredited by the AAALAC International (Protocol No: NHRI-IACUC-104125AE).

Consent for publication

Not applicable.

Availability of data and materials

All data generated and analyzed during this study are included in this published article and its supplementary information files. The 16S rRNA gene sequences and metagenomic sequences were provided and available at Science Data Bank, data DOI: 10.57760/sciencedb.0175. Data link: https://www.scidb.cn/s/aEBze2

Competing interests

The authors declare that they have no competing interests.

Funding

Ministry of Science and Technology, Taiwan, MOST 106-3111-Y-043-001

Ministry of Science and Technology, Taiwan, MOST 110-2314-B-037-137

Authors' contributions

Hsin-Su Yu and Yao-Tsung Yeh conceived, organized, and supervised the project. Hsin-Su Yu, Yao-Tsung Yeh, and Cheng-Hsieh Huang interpreted the results and prepared the manuscript. Hsu-Sheng Yu and Sebastian Yu contributed to process the sample. Hung-Pin Tu and Cheng-Hsieh Huang contributed to statistical analysis. Hsu-Sheng Yu, Sebastian Yu, and Cheng-Hsieh Huang contributed to experimental design and animal maintenance. All authors read and approved the final version of the manuscript before submission.

Acknowledgments

This work was supported by grant number MOST 106-3111-Y-043-001 and MOST 110-2314-B-037-137 (Ministry of Science and Technology, Taiwan).

Competing Interest Statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Classification: Biological Sciences/Microbiology, Physical Sciences/Environmental Sciences.

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Chronic blue light-emitting diode exposure harvests gut dysbiosis related to cholesterol dysregulation

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