Toxic Effect of Visible Light on Drosophila Life Span Depending on Diet Protein Content

Toxic Effect of Visible Light on Drosophila Life Span Depending on Diet Protein Content Abstract We investigated the toxic effect of visible light on Drosophila life span in both sexes. The toxic effect of ultraviolet light on organisms is well known. However, the effects of illumination with visible light remain unclear. Here, we found that visible light could be toxic to Drosophila survival, depending on the protein content in diet. In addition, further analysis revealed significant interaction between light and sex and showed that strong light shortened life span by causing opposite direction changes in mortality rate parameters in females versus males. Our findings suggest that photoaging may be a general phenomenon and support the theory of sexual antagonistic pleiotropy in aging intervention. The results caution that exposure to visible light could be hazardous to life span and suggest that identification of the underlying mechanism would allow better understanding of aging intervention. Life span, Light, Diet, Mortality, Sex specificity Aging is not a disease but rather a fundamental biological process, involving biological, chemical, and physical processes. Light is a crucial environmental factor influencing living organisms during their whole lives. It contributes to the regulation of circadian rhythms and affects growth, metabolic rate, locomotor activity, and reproduction (1–4). Therefore, light is closely associated with animal health and well-being and, in turn, affects scientific outcomes. Light intensity, duration of exposure, and spectral quality or wavelength are all considerations to be factored into both facility design and experimental protocols when using animal models in research. The mechanisms of the influence of light on longevity are poorly understood. There are a few studies about effects of specific wavelengths on development and life span. Old flies exposed to long wavelength light (670 nm) showed improved mitochondrial metabolism and reduced motor and cognitive decline (5). Blue-light exposure induces phototransduction-dependent oxidative stress, lipid peroxidation, and retinal degeneration in Drosophila melanogaster (6). However, in nature and in laboratory culture conditions, organisms are exposed to a mix of spectrum of lights, such as sun light, fluorescent light, and LED light. Human beings are exposed to these light sources as well in daily life. Therefore, it would be interesting to find out how the intensity of visible light could affect aging. In this study, we found that visible light could be toxic to Drosophila survival, depending on the protein content in diet. Analysis of variance (ANOVA) revealed significant interaction between light and sex. Further analysis showed that visible light had sexually specific effects on mortality rate parameters, consistent with our previous data on sexual antagonistic pleiotropy (7). The results caution that exposure to visible light could be hazardous to life span. Methods Drosophila Culture and Life-Span Assays The Drosophila melanogaster wild-type stock w1118 was obtained from the Bloomington Stock Center and maintained on a 12:12 hour light:dark cycle at constant humidity of 60% ± 5% using cornmeal/sugar/yeast/agar medium. Eclosing adult flies were collected over an 8-hour period. Flies were mated for 48 hours before sorting into male vials or female vials. Life-span experiments were conducted at 29°C on a 12:12 hour light:dark cycle on standard diet (100-g yeast per 1 L of diet) or high-protein diet (300-g yeast per 1 L of diet). Flies were maintained in vials at a density of 40 flies per vial on Day 0 of the life-span assay. Flies were transferred to new vials every other day, and the number of deaths was counted. Two cohorts of flies were tested for the light effect. Hundred microliter water (Cohort 1) or 50-µL ethanol (EtOH; Cohort 2) was added to the surface of each vial and vials were let dry for 2 days before use, to examine whether light has different effects on the two cohorts. The experiment was designed in this way, as our initial research plan was to screen drugs and chemicals that can extend life span. Depending on the solubility, drugs or chemicals are dissolved in EtOH or water and diffuse into the top 1 mL of food in the vial (8). Previous test showed that 50 µL of EtOH was enough to cover the food surface evenly, whereas 100-µL water solution was needed to evenly cover the food surface in the vial. Light Treatments To test the effect of visible light, we cultured flies under two light treatments with LED lights (model KS-T5 #KS-876, cool white, color temperature 6,500 K, manufactured by Kosoom Lighting & Electric Co., Ltd). The “strong light” treatment condition (intensity of 3,000 ± 50 lux) and the “weak light” treatment condition (intensity of 1,000 ± 50 lux) were set with an illuminometer, by putting fly vials at different distances to the same light source, to control the light intensity (1,000 vs. 3,000 lux). Thermometers were set at the two places. The temperatures under two conditions were the same. The spectrum view measured by a spectroscope (model #FX2000-EX, manufactured by Ideaoptics) is also presented (Supplementary Figure 1A), to show the range of wavelengths for the light source. Light treatments were configured to 12:12 hour light:dark daily photic cycle. Statistical Analysis Statistical analyses were performed using GraphPad Prism v. 6 and SPSS 13.0. The mean, median, maximum, minimum, and log-rank tests were performed on survival curves. Three-way ANOVA was conducted on standard diet data set and high-protein diet data set. Mortality Analysis Gompertz–Makeham (G–M) modeling was conducted using WinModest software (version 1.0.0.1) as described previously (9). Briefly, the age-specific mortality rate (μx) was calculated using WinModest. μx is the mortality rate at Day x. In the G–M equation, the increase of mortality (μx) with age (x) is expressed as follows: μx = aebx + c. The G–M equation describes survival curves in terms of parameter a (initial mortality rate), parameter b (rate of exponential increase in mortality), and parameter c (age-independent mortality). Parameters (a and b) were calculated using WinModest based on a likelihood ratio test. The mortality rate parameter analysis was conducted on the combination of Cohorts 1 and 2. Results Toxic Effect of Visible Light on Drosophila melanogaster Survival on Standard Diet, but Not on High-Protein Diet First, we investigated the effect of visible light of different intensities (intensities of 3,000 ± 50 and 1,000 ± 50 lux) on Drosophila melanogaster adult. Illumination with light of 3,000 lux (strong light) on a 12:12 hour light:dark cycle throughout the adult stage significantly decreased the survival compared with the life span under 1,000 lux (weak light) condition on standard diet (Figure 1A, B, E, and F). The toxic effect of the strong light was not observed on high-protein diet (Figure 1C, D, G, and H). The standard diet and the high-protein diet recipes contain sugar, yeast, and agar as the main ingredients and have been used in multiple studies (10–12). Because diet manipulation is an important factor regulating life span, it would be interesting to see whether light effects would be different when life-span assays are conducted on different diets. Figure 1. View largeDownload slide Toxic effect of visible light on Drosophila melanogaster survival on standard diet, but not on high-protein diet. (A–D) Cohort 1 (water) survival curves. (E–H) Cohort 2 (EtOH) survival curves. A, B, E, F are on standard diet. C, D, G, H are on high-protein diet. L–S means strong light. L–W means weak light. Detailed statistics are provided in Table 1 and detailed procedures in Methods. Figure 1. View largeDownload slide Toxic effect of visible light on Drosophila melanogaster survival on standard diet, but not on high-protein diet. (A–D) Cohort 1 (water) survival curves. (E–H) Cohort 2 (EtOH) survival curves. A, B, E, F are on standard diet. C, D, G, H are on high-protein diet. L–S means strong light. L–W means weak light. Detailed statistics are provided in Table 1 and detailed procedures in Methods. Life span is one of the most robust measures of aging and is typically reported in terms of median life span. In our experiments, we found that light could reduce life span in both males and females on standard diet. Light of 3,000 lux (strong light) caused 15.38% decrease in female median life span and 9.09% decrease in male median life span compared with 1,000 lux (weak light) condition in Cohort 1 on standard diet (Figure 1A and B; Table 1). The percentage of reduction in life span in Cohort 2 is similar (Table 1). However, interestingly, on high-protein diet, the toxic effect of strong light was not observed (Table 1). Table 1. Statistical Analysis of Visible Light Effect on Life Span Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Note: aDiet composition: standard refers to standard diet; high-Pro refers to high-protein diet. bLight intensity: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large Table 1. Statistical Analysis of Visible Light Effect on Life Span Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Note: aDiet composition: standard refers to standard diet; high-Pro refers to high-protein diet. bLight intensity: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large The 3-way ANOVA test reveals that on both standard and high-protein diets, there are significant differences between males and females, between strong light and weak light, and between water and EtOH treatment; there are also significant interactions between sex and light and between sex and water/EtOH treatment (Table 2). Table 2. Three-Way ANOVA on Standard Diet and High-Protein Diet Data Set   Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)    Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)  Note: ANOVA = analysis of variance; EtOH = ethanol. View Large Table 2. Three-Way ANOVA on Standard Diet and High-Protein Diet Data Set   Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)    Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)  Note: ANOVA = analysis of variance; EtOH = ethanol. View Large These results reveal that the aging process and life span could be relevant to the intensity of visible light and that visible light at strong intensity can be toxic, depending on the protein content in the diet. Besides, light could interact with sex factor, to affect survival. Sexually Specific Effect of Visible Light on Mortality Rate Parameters in Males and Females To understand how the interaction between light and sex affects survival, we further investigated how mortality rate parameters altered when visible light played toxic effect on standard diet. Here, survival data were fitted to the G–M equation separately for males and females to determine which mortality rate parameters have been altered. Strong light and weak light groups were compared using WinModest software (13), which determines whether there was a statistically significant change for each parameter. We found that strong light shortened life span compared with weak light, with decreased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b) in females (Table 3). By contrast, in males, the analysis revealed increased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b). Therefore, visible light has sexually specific effects on mortality rate parameters. Table 3. Parameters for Gompertz–Makeham Model and Likelihood Ratio Test Results Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Note: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large Table 3. Parameters for Gompertz–Makeham Model and Likelihood Ratio Test Results Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Note: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large The results show that visible light can cause sexually specific change in mortality rate parameters. This may explain how light interacts with sex factor to affect survival, as indicated by ANOVA analysis. Discussion In this study, we revealed that visible light may be a major factor in the aging process for Drosophila. It has been clearly established that ultraviolet (UV) light produces a wide range of changes including DNA damage and tumor induction. UVB and UVC directly damage DNA by inducing cis-syn cyclobutane pyrimidine dimers and pyrimidine (6–4) pyrimidone photoproducts (14). UVA is not absorbed by native DNA but indirectly damages lipids, proteins, and DNA by enhancing the production of reactive oxygen species (15). Visible light, although popularly considered benign, has also been shown to produce changes of a negative nature. Blue-light (short-wavelength visible light) irradiation injures organisms by stimulating the production of reactive oxygen species. Many microbial cells are highly sensitive to blue light as a result of the accumulation of photosensitizers such as porphyrins and flavins (16). Reactive oxygen species produced by blue-light irradiation can also severely damage mammalian retinas (17). What is more, even incandescent light (which lacks UV and most of the blue wavelengths) can produce pyrimidine dimers in DNA (18). Startlingly, 3 hours of fluorescent light at 1,000 lux induce more DNA strand breaks in mammalian cells in culture than 300 rads of X-rays (19). As a result of visible light exposure, mammalian hepatocytes show photodamage (20). The finding in this study that the intensity of visible light could affect life span would provide useful information about the intensity of light and fly life-span culture condition for researchers. There are some studies about effect of specific wavelengths or dim artificial light at night on development and life span (5,6,21). However, in nature, organisms are exposed to sun light, which is a mix of spectrum of lights (Supplementary Figure 1B). Laboratory animal culture, lighting industry, and common households use fluorescent lighting and LED lighting, which are a mix of spectrum of lights as well (Supplementary Figure 1A, C, and D). It is probable that the toxic effect of visible light on Drosophila survival on standard diet that we found in this study is caused by the production of reactive oxygen species, and the afterwards damages on DNA, proteins, and lipids. This is supported by the photosensitizer and aging of Drosophila study, which found that the photosensitizer, methylene blue, resulted in the production of singlet oxygen and increased rate of aging (22). It is also possible that the light was affecting the microbiota, as opposed to having a direct effect on the physiology of the flies. Although severe bacterial infection, which is shown as sticky fly food surface, was not observed during the whole assay, it would be interesting to find out whether light would increase microbial load and therefore increase mortality, by using antibiotic treatment on the adult flies to knock down microbial load (23). In our experiment, the life-span assay was conducted at 29°C to speed up the assay, as based on our previous research data (24), when sticky fly food surface was not observed, the results of life-span assay at 29°C are consistent with the results at 25°C. There is possibility that light could change the microbiota and the immunologic, hormonal, and metabolic homeostasis of the host, and therefore affect life span, or light could induce heat shock response. In these cases, the high culture temperature may interfere with the effect of light on life span. It is interesting that in our finding the toxic effect of visible light was not observed on the high-protein diet. Because mechanisms of the influence of light on living organisms are not well understood, the strong light might affect life span by affecting bacteria growth or metabolism and so on. If the high-protein diet and the strong light caused reduced life span for the same reason, then the high-protein diet might mask the negative effects of the strong light. We found that there was a significant interaction between light and sex by ANOVA. Mortality rate parameter analysis indicated that visible light has sex-specific effect on mortality rate parameters. This sexual dimorphism could be due to sex-specific selective pressures that are hypothesized to lead to gene functions that are suboptimal in one or both sexes, thereby potentially contributing to the aging phenotype (sexual antagonistic pleiotropy) (25). The strong light led to decreased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b) in females, but increased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b) in males (Table 3). Our previous research found that p53 mutation in Drosophila caused opposite direction changes in mortality rate parameters in females versus males, which are decreased initial mortality rate and increased age-dependent mortality rate in females, but increased initial mortality rate and decreased age-dependent mortality rate in males (7). One possible explanation of the effects of light on mortality rate parameters in females could be that the toxic effect of light might act through DNA damage, and the DNA damage could activate p53 activity, as the pattern of mortality rate parameter changes caused by light is similar to that of p53. However, in males, the pattern of mortality rate parameter changes is different from that of p53. Therefore, other mechanisms would explain the different effects of light on mortality rate parameters in males versus females. Overall, the results reveal that the effect of visible light on survival depends on the protein content of diet, and visible light has sex-specific effect on mortality rate parameters. The results caution that exposure to visible light could be hazardous to life span and suggest that identification of the underlying mechanisms may allow better understanding of the influence of light on longevity. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online. Funding This work was supported by a grant from the National Natural Science Foundation of China (31500970 to J.S.), the Project sponsored by SRF for ROCS, SEM (to J.S.), the Returned Overseas Chinese Scholars Research Merit Aid, Zhejiang [2014]115 (to J.S.), and the Graduate Scientific Research Foundation of Hangzhou Dianzi University (CXJJ2017070 to X.Z.). Conflict of Interest None reported. References 1. Vinogradova IA, Anisimov VN, Bukalev AV, Semenchenko AV, Zabezhinski MA. Circadian disruption induced by light-at-night accelerates aging and promotes tumorigenesis in rats. Aging (Albany, NY) . 2009; 1: 855– 865. doi: 10.18632/aging.100092 Google Scholar CrossRef Search ADS   2. Tucker HA, Petitclerc D, Zinn SA. The influence of photoperiod on body weight gain, body composition, nutrient intake and hormone secretion. J Anim Sci . 1984; 59: 1610– 1620. doi:10.2527/jas1984.5961610x Google Scholar CrossRef Search ADS PubMed  3. Sheeba V, Sharma VK, Shubha K, Chandrashekaran MK, Joshi A. The effect of different light regimes on adult life span in Drosophila melanogaster is partly mediated through reproductive output. J Biol Rhythms . 2000; 15: 380– 392. doi: 10.1177/074873000129001477 Google Scholar CrossRef Search ADS PubMed  4. Northrop JH. The influence of the intensity of light on the rate of growth and duration of life of Drosophila. J Gen Physiol . 1925; 9: 81– 86. doi:10.1085/jgp.9.1.81 Google Scholar CrossRef Search ADS PubMed  5. Weinrich TW, Coyne A, Salt TE, Hogg C, Jeffery G. Improving mitochondrial function significantly reduces metabolic, visual, motor and cognitive decline in aged Drosophila melanogaster. Neurobiol Aging . 2017; 60: 34– 43. doi: 10.1016/j.neurobiolaging.2017.08.016 Google Scholar CrossRef Search ADS PubMed  6. Chen X, Hall H, Simpson JP, Leon-Salas WD, Ready DF, Weake VM. Cytochrome b5 protects photoreceptors from light stress-induced lipid peroxidation and retinal degeneration. NPJ Aging Mech Dis . 2017; 3: 18. doi: 10.1038/s41514-017-0019-6 Google Scholar CrossRef Search ADS PubMed  7. Shen J, Landis GN, Tower J. Multiple metazoan life-span interventions exhibit a sex-specific Strehler-Mildvan inverse relationship between initial mortality rate and age-dependent mortality rate acceleration. J Gerontol A Biol Sci Med Sci . 2017; 72: 44– 53. doi: 10.1093/gerona/glw005 Google Scholar CrossRef Search ADS PubMed  8. Ren C, Webster P, Finkel SE, Tower J. Increased internal and external bacterial load during Drosophila aging without life-span trade-off. Cell Metab . 2007; 6: 144– 152. doi: 10.1016/j.cmet.2007.06.006 Google Scholar CrossRef Search ADS PubMed  9. Shen J, Ford D, Landis GN, Tower J. Identifying sexual differentiation genes that affect Drosophila life span. BMC Geriatr . 2009; 9: 56. doi: 10.1186/1471-2318-9-56 Google Scholar CrossRef Search ADS PubMed  10. Magwere T, Chapman T, Partridge L. Sex differences in the effect of dietary restriction on life span and mortality rates in female and male Drosophila melanogaster. J Gerontol A Biol Sci Med Sci . 2004; 59: 3– 9. doi:10.1093/gerona/59.1.B3 Google Scholar CrossRef Search ADS PubMed  11. Zajitschek F, Zajitschek SR, Friberg U, Maklakov AA. Interactive effects of sex, social environment, dietary restriction, and methionine on survival and reproduction in fruit flies. Age (Dordr) . 2013; 35: 1193– 1204. doi: 10.1007/s11357-012-9445-3 Google Scholar CrossRef Search ADS PubMed  12. Zajitschek F, Jin T, Colchero F, Maklakov AA. Aging differently: diet- and sex-dependent late-life mortality patterns in Drosophila melanogaster. J Gerontol A Biol Sci Med Sci . 2014; 69: 666– 674. doi: 10.1093/gerona/glt158 Google Scholar CrossRef Search ADS PubMed  13. Pletcher SD. Model fitting and hypothesis testing for age-specific mortality data. J Evol Biol . 1999; 12: 430– 439. doi: 10.1046/j.1420-9101. 1999.00058.x Google Scholar CrossRef Search ADS   14. Pfeifer GP. Formation and processing of UV photoproducts: effects of DNA sequence and chromatin environment. Photochem Photobiol . 1997; 65: 270– 283. doi:10.1111/j.1751-1097.1997.tb08560.x Google Scholar CrossRef Search ADS PubMed  15. Santos AL, Oliveira V, Baptista I, et al.   Wavelength dependence of biological damage induced by UV radiation on bacteria. Arch Microbiol . 2013; 195: 63– 74. doi: 10.1007/s00203-012-0847-5 Google Scholar CrossRef Search ADS PubMed  16. Yin R, Dai T, Avci P, et al.   Light based anti-infectives: ultraviolet C irradiation, photodynamic therapy, blue light, and beyond. Curr Opin Pharmacol . 2013; 13: 731– 762. doi: 10.1016/j.coph.2013.08.009 Google Scholar CrossRef Search ADS PubMed  17. Kuse Y, Ogawa K, Tsuruma K, Shimazawa M, Hara H. Damage of photoreceptor-derived cells in culture induced by light emitting diode-derived blue light. Sci Rep . 2014; 4: 5223. doi: 10.1038/srep05223 Google Scholar CrossRef Search ADS PubMed  18. Ciarrocchi G, Sutherland BM, Sutherland JC. Incandescent lamps can produce pyrimidine dimers in DNA. Photochem Photobiol . 1985; 41: 703– 705. doi:10.1111/j.1751-1097.1985.tb03625.x Google Scholar CrossRef Search ADS PubMed  19. Bradley MO, Erickson LC, Kohn KW. Non-enzymatic DNA strand breaks induced in mammalian cells by fluorescent light. Biochim Biophys Acta . 1978; 520: 11– 20. doi:10.1016/0005-2787(78)90003-5 Google Scholar CrossRef Search ADS PubMed  20. Cheng LY, Packer L. Photodamage to hepatocytes by visible light. FEBS Lett . 1979; 97: 124– 128. doi:10.1016/0014-5793(79)80066-6 Google Scholar CrossRef Search ADS PubMed  21. McLay LK, Green MP, Jones TM. Chronic exposure to dim artificial light at night decreases fecundity and adult survival in Drosophila melanogaster. J Insect Physiol . 2017; 100: 15– 20. doi: 10.1016/j.jinsphys.2017.04.009 Google Scholar CrossRef Search ADS PubMed  22. Massie HR, Aiello VR, Williams TR. Influence of photosensitizers and light on the life span of Drosophila. Mech Ageing Dev . 1993; 68: 175– 182. doi:10.1016/0047-6374(93)90149-L Google Scholar CrossRef Search ADS PubMed  23. Tower J, Landis GN, Shen J, et al.   Mifepristone/RU486 acts in Drosophila melanogaster females to counteract the life span-shortening and pro-inflammatory effects of male sex peptide. Biogerontology . 2017; 18: 413– 427. doi: 10.1007/s10522-017-9703-y Google Scholar CrossRef Search ADS PubMed  24. Shen J, Tower J. Drosophila foxo acts in males to cause sexual-dimorphism in tissue-specific p53 life span effects. Exp Gerontol . 2010; 45: 97– 105. doi: 10.1016/j.exger.2009.10.009 Google Scholar CrossRef Search ADS PubMed  25. Pomatto LCD, Tower J, Davies KJA. Sexual dimorphism and aging differentially regulate adaptive homeostasis. J Gerontol A Biol Sci Med Sci . 2018; 73: 141– 149. doi: 10.1093/gerona/glx083 Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The Journals of Gerontology Series A: Biomedical Sciences and Medical Sciences Oxford University Press

Toxic Effect of Visible Light on Drosophila Life Span Depending on Diet Protein Content

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© The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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Abstract

Abstract We investigated the toxic effect of visible light on Drosophila life span in both sexes. The toxic effect of ultraviolet light on organisms is well known. However, the effects of illumination with visible light remain unclear. Here, we found that visible light could be toxic to Drosophila survival, depending on the protein content in diet. In addition, further analysis revealed significant interaction between light and sex and showed that strong light shortened life span by causing opposite direction changes in mortality rate parameters in females versus males. Our findings suggest that photoaging may be a general phenomenon and support the theory of sexual antagonistic pleiotropy in aging intervention. The results caution that exposure to visible light could be hazardous to life span and suggest that identification of the underlying mechanism would allow better understanding of aging intervention. Life span, Light, Diet, Mortality, Sex specificity Aging is not a disease but rather a fundamental biological process, involving biological, chemical, and physical processes. Light is a crucial environmental factor influencing living organisms during their whole lives. It contributes to the regulation of circadian rhythms and affects growth, metabolic rate, locomotor activity, and reproduction (1–4). Therefore, light is closely associated with animal health and well-being and, in turn, affects scientific outcomes. Light intensity, duration of exposure, and spectral quality or wavelength are all considerations to be factored into both facility design and experimental protocols when using animal models in research. The mechanisms of the influence of light on longevity are poorly understood. There are a few studies about effects of specific wavelengths on development and life span. Old flies exposed to long wavelength light (670 nm) showed improved mitochondrial metabolism and reduced motor and cognitive decline (5). Blue-light exposure induces phototransduction-dependent oxidative stress, lipid peroxidation, and retinal degeneration in Drosophila melanogaster (6). However, in nature and in laboratory culture conditions, organisms are exposed to a mix of spectrum of lights, such as sun light, fluorescent light, and LED light. Human beings are exposed to these light sources as well in daily life. Therefore, it would be interesting to find out how the intensity of visible light could affect aging. In this study, we found that visible light could be toxic to Drosophila survival, depending on the protein content in diet. Analysis of variance (ANOVA) revealed significant interaction between light and sex. Further analysis showed that visible light had sexually specific effects on mortality rate parameters, consistent with our previous data on sexual antagonistic pleiotropy (7). The results caution that exposure to visible light could be hazardous to life span. Methods Drosophila Culture and Life-Span Assays The Drosophila melanogaster wild-type stock w1118 was obtained from the Bloomington Stock Center and maintained on a 12:12 hour light:dark cycle at constant humidity of 60% ± 5% using cornmeal/sugar/yeast/agar medium. Eclosing adult flies were collected over an 8-hour period. Flies were mated for 48 hours before sorting into male vials or female vials. Life-span experiments were conducted at 29°C on a 12:12 hour light:dark cycle on standard diet (100-g yeast per 1 L of diet) or high-protein diet (300-g yeast per 1 L of diet). Flies were maintained in vials at a density of 40 flies per vial on Day 0 of the life-span assay. Flies were transferred to new vials every other day, and the number of deaths was counted. Two cohorts of flies were tested for the light effect. Hundred microliter water (Cohort 1) or 50-µL ethanol (EtOH; Cohort 2) was added to the surface of each vial and vials were let dry for 2 days before use, to examine whether light has different effects on the two cohorts. The experiment was designed in this way, as our initial research plan was to screen drugs and chemicals that can extend life span. Depending on the solubility, drugs or chemicals are dissolved in EtOH or water and diffuse into the top 1 mL of food in the vial (8). Previous test showed that 50 µL of EtOH was enough to cover the food surface evenly, whereas 100-µL water solution was needed to evenly cover the food surface in the vial. Light Treatments To test the effect of visible light, we cultured flies under two light treatments with LED lights (model KS-T5 #KS-876, cool white, color temperature 6,500 K, manufactured by Kosoom Lighting & Electric Co., Ltd). The “strong light” treatment condition (intensity of 3,000 ± 50 lux) and the “weak light” treatment condition (intensity of 1,000 ± 50 lux) were set with an illuminometer, by putting fly vials at different distances to the same light source, to control the light intensity (1,000 vs. 3,000 lux). Thermometers were set at the two places. The temperatures under two conditions were the same. The spectrum view measured by a spectroscope (model #FX2000-EX, manufactured by Ideaoptics) is also presented (Supplementary Figure 1A), to show the range of wavelengths for the light source. Light treatments were configured to 12:12 hour light:dark daily photic cycle. Statistical Analysis Statistical analyses were performed using GraphPad Prism v. 6 and SPSS 13.0. The mean, median, maximum, minimum, and log-rank tests were performed on survival curves. Three-way ANOVA was conducted on standard diet data set and high-protein diet data set. Mortality Analysis Gompertz–Makeham (G–M) modeling was conducted using WinModest software (version 1.0.0.1) as described previously (9). Briefly, the age-specific mortality rate (μx) was calculated using WinModest. μx is the mortality rate at Day x. In the G–M equation, the increase of mortality (μx) with age (x) is expressed as follows: μx = aebx + c. The G–M equation describes survival curves in terms of parameter a (initial mortality rate), parameter b (rate of exponential increase in mortality), and parameter c (age-independent mortality). Parameters (a and b) were calculated using WinModest based on a likelihood ratio test. The mortality rate parameter analysis was conducted on the combination of Cohorts 1 and 2. Results Toxic Effect of Visible Light on Drosophila melanogaster Survival on Standard Diet, but Not on High-Protein Diet First, we investigated the effect of visible light of different intensities (intensities of 3,000 ± 50 and 1,000 ± 50 lux) on Drosophila melanogaster adult. Illumination with light of 3,000 lux (strong light) on a 12:12 hour light:dark cycle throughout the adult stage significantly decreased the survival compared with the life span under 1,000 lux (weak light) condition on standard diet (Figure 1A, B, E, and F). The toxic effect of the strong light was not observed on high-protein diet (Figure 1C, D, G, and H). The standard diet and the high-protein diet recipes contain sugar, yeast, and agar as the main ingredients and have been used in multiple studies (10–12). Because diet manipulation is an important factor regulating life span, it would be interesting to see whether light effects would be different when life-span assays are conducted on different diets. Figure 1. View largeDownload slide Toxic effect of visible light on Drosophila melanogaster survival on standard diet, but not on high-protein diet. (A–D) Cohort 1 (water) survival curves. (E–H) Cohort 2 (EtOH) survival curves. A, B, E, F are on standard diet. C, D, G, H are on high-protein diet. L–S means strong light. L–W means weak light. Detailed statistics are provided in Table 1 and detailed procedures in Methods. Figure 1. View largeDownload slide Toxic effect of visible light on Drosophila melanogaster survival on standard diet, but not on high-protein diet. (A–D) Cohort 1 (water) survival curves. (E–H) Cohort 2 (EtOH) survival curves. A, B, E, F are on standard diet. C, D, G, H are on high-protein diet. L–S means strong light. L–W means weak light. Detailed statistics are provided in Table 1 and detailed procedures in Methods. Life span is one of the most robust measures of aging and is typically reported in terms of median life span. In our experiments, we found that light could reduce life span in both males and females on standard diet. Light of 3,000 lux (strong light) caused 15.38% decrease in female median life span and 9.09% decrease in male median life span compared with 1,000 lux (weak light) condition in Cohort 1 on standard diet (Figure 1A and B; Table 1). The percentage of reduction in life span in Cohort 2 is similar (Table 1). However, interestingly, on high-protein diet, the toxic effect of strong light was not observed (Table 1). Table 1. Statistical Analysis of Visible Light Effect on Life Span Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Note: aDiet composition: standard refers to standard diet; high-Pro refers to high-protein diet. bLight intensity: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large Table 1. Statistical Analysis of Visible Light Effect on Life Span Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Dieta  Water/EtOH  Light b  Sex  N  Mean  Median  Maximum  Minimum  ΔMean  ΔMedian  p Value  Standard  Water  L-W  F  39  23.47  26  34  6  –  –  –  Standard  Water  L-S  F  40  21.60  22  26  8  −7.97  −15.38  <.001  Standard  Water  L-W  M  40  20.45  22  26  6  –  –  –  Standard  Water  L-S  M  41  16.78  20  22  4  −17.95  −9.09  <.001  High-Pro  Water  L-W  F  39  9.95  10  18  4  –  –  –  High-Pro  Water  L-S  F  39  11.18  12  18  6  12.36  20.00  .07  High-Pro  Water  L-W  M  34  12.06  12  16  4  –  –  –  High-Pro  Water  L-S  M  46  11.96  12  18  2  −0.83  0.00  .42  Standard  EtOH  L-W  F  41  20.63  24  28  2  –  –  –  Standard  EtOH  L-S  F  41  20.88  20  24  16  1.21  −16.67  <.001  Standard  EtOH  L-W  M  42  21.00  22  28  4  –  –  –  Standard  EtOH  L-S  M  42  17.81  20  22  4  −15.19  −9.09  <.001  High-Pro  EtOH  L-W  F  41  7.37  8  12  2  –  –  –  High-Pro  EtOH  L-S  F  41  9.56  10  14  6  29.72  25.00  <.001  High-Pro  EtOH  L-W  M  41  11.17  10  16  2  –  –  –  High-Pro  EtOH  L-S  M  40  11.45  12  16  2  2.51  20.00  .93  Note: aDiet composition: standard refers to standard diet; high-Pro refers to high-protein diet. bLight intensity: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large The 3-way ANOVA test reveals that on both standard and high-protein diets, there are significant differences between males and females, between strong light and weak light, and between water and EtOH treatment; there are also significant interactions between sex and light and between sex and water/EtOH treatment (Table 2). Table 2. Three-Way ANOVA on Standard Diet and High-Protein Diet Data Set   Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)    Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)  Note: ANOVA = analysis of variance; EtOH = ethanol. View Large Table 2. Three-Way ANOVA on Standard Diet and High-Protein Diet Data Set   Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)    Tests of Between-Subject Effects  Dependent Variable: Life Span  Standard diet  Source  Type III Sum of Squares  df  Mean Square  F  Significance  Corrected model  1,491.796(a)  7  213.114  7.784  .000  Intercept  122,143.305  1  122,143.305  4,461.298  .000  Sex  595.533  1  595.533  21.752  .000  Light  390.631  1  390.631  14.268  .000  water/EtOH  168.178  1  168.178  6.143  .014  Sex × light  125.258  1  125.258  4.575  .033  Sex × (water/EtOH)  149.023  1  149.023  5.443  .020  Light × (water/EtOH)  41.831  1  41.831  1.528  .217  Sex × light × (water/EtOH)  18.542  1  18.542  0.677  .411  Error  8,706.339  318  27.378      Total  132,256.000  326        Corrected total  10,198.135  325        (a) R2 = .146 (adjusted R2 = .127)  High-protein diet  Corrected model  701.779(a)  7  100.254  10.374  .000  Intercept  35,754.999  1  35,754.999  3,699.913  .000  Sex  367.064  1  367.064  37.984  .000  Light  64.708  1  64.708  6.696  .010  water/EtOH  156.104  1  156.104  16.154  .000  Sex × light  52.619  1  52.619  5.445  .020  Sex × (water/EtOH)  39.271  1  39.271  4.064  .045  Light × (water/EtOH)  9.030  1  9.030  0.934  .334  Sex × light × (water/EtOH)  1.693  1  1.693  0.175  .676  Error  3,024.751  313  9.664      Total  39,612.000  321        Corrected total  3,726.530  320        (a) R2 = .188 (adjusted R2 = .170)  Note: ANOVA = analysis of variance; EtOH = ethanol. View Large These results reveal that the aging process and life span could be relevant to the intensity of visible light and that visible light at strong intensity can be toxic, depending on the protein content in the diet. Besides, light could interact with sex factor, to affect survival. Sexually Specific Effect of Visible Light on Mortality Rate Parameters in Males and Females To understand how the interaction between light and sex affects survival, we further investigated how mortality rate parameters altered when visible light played toxic effect on standard diet. Here, survival data were fitted to the G–M equation separately for males and females to determine which mortality rate parameters have been altered. Strong light and weak light groups were compared using WinModest software (13), which determines whether there was a statistically significant change for each parameter. We found that strong light shortened life span compared with weak light, with decreased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b) in females (Table 3). By contrast, in males, the analysis revealed increased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b). Therefore, visible light has sexually specific effects on mortality rate parameters. Table 3. Parameters for Gompertz–Makeham Model and Likelihood Ratio Test Results Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Note: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large Table 3. Parameters for Gompertz–Makeham Model and Likelihood Ratio Test Results Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Parameters  L-S  L-W  χ2  df  p Value  χ2  df  p Value  χ2  df  p Value      One Parameter Compared at Each Time                        a Is Constrained  b Is Constrained  F  a  1.00 × 10−5  2.5 × 10−4  1.86  1  0.17        20.9  1  <0.01    b  9.48 × 10−1  5.74 × 10−1  3.96  1  0.05  22.99  1  <0.01          c  9.68 × 10−3  8.87 × 10−3  0.01  1  0.93  0.49  1  0.48  1.28  1  0.26  M  a  2.86 × 10−7  1.13 × 10−7  0.06  1  0.81        47.01  1  <0.01    b  1.52  1.33  0.3  1  0.58  47.25  1  <0.01          c  3.37 × 10−2  3.02 × 10−2  0.05  1  0.82  0.09  1  0.77  0.01  1  0.91  Note: L-S refers to strong light; L-W refers to weak light. Statistical significance was defined as a p value of 0.05. View Large The results show that visible light can cause sexually specific change in mortality rate parameters. This may explain how light interacts with sex factor to affect survival, as indicated by ANOVA analysis. Discussion In this study, we revealed that visible light may be a major factor in the aging process for Drosophila. It has been clearly established that ultraviolet (UV) light produces a wide range of changes including DNA damage and tumor induction. UVB and UVC directly damage DNA by inducing cis-syn cyclobutane pyrimidine dimers and pyrimidine (6–4) pyrimidone photoproducts (14). UVA is not absorbed by native DNA but indirectly damages lipids, proteins, and DNA by enhancing the production of reactive oxygen species (15). Visible light, although popularly considered benign, has also been shown to produce changes of a negative nature. Blue-light (short-wavelength visible light) irradiation injures organisms by stimulating the production of reactive oxygen species. Many microbial cells are highly sensitive to blue light as a result of the accumulation of photosensitizers such as porphyrins and flavins (16). Reactive oxygen species produced by blue-light irradiation can also severely damage mammalian retinas (17). What is more, even incandescent light (which lacks UV and most of the blue wavelengths) can produce pyrimidine dimers in DNA (18). Startlingly, 3 hours of fluorescent light at 1,000 lux induce more DNA strand breaks in mammalian cells in culture than 300 rads of X-rays (19). As a result of visible light exposure, mammalian hepatocytes show photodamage (20). The finding in this study that the intensity of visible light could affect life span would provide useful information about the intensity of light and fly life-span culture condition for researchers. There are some studies about effect of specific wavelengths or dim artificial light at night on development and life span (5,6,21). However, in nature, organisms are exposed to sun light, which is a mix of spectrum of lights (Supplementary Figure 1B). Laboratory animal culture, lighting industry, and common households use fluorescent lighting and LED lighting, which are a mix of spectrum of lights as well (Supplementary Figure 1A, C, and D). It is probable that the toxic effect of visible light on Drosophila survival on standard diet that we found in this study is caused by the production of reactive oxygen species, and the afterwards damages on DNA, proteins, and lipids. This is supported by the photosensitizer and aging of Drosophila study, which found that the photosensitizer, methylene blue, resulted in the production of singlet oxygen and increased rate of aging (22). It is also possible that the light was affecting the microbiota, as opposed to having a direct effect on the physiology of the flies. Although severe bacterial infection, which is shown as sticky fly food surface, was not observed during the whole assay, it would be interesting to find out whether light would increase microbial load and therefore increase mortality, by using antibiotic treatment on the adult flies to knock down microbial load (23). In our experiment, the life-span assay was conducted at 29°C to speed up the assay, as based on our previous research data (24), when sticky fly food surface was not observed, the results of life-span assay at 29°C are consistent with the results at 25°C. There is possibility that light could change the microbiota and the immunologic, hormonal, and metabolic homeostasis of the host, and therefore affect life span, or light could induce heat shock response. In these cases, the high culture temperature may interfere with the effect of light on life span. It is interesting that in our finding the toxic effect of visible light was not observed on the high-protein diet. Because mechanisms of the influence of light on living organisms are not well understood, the strong light might affect life span by affecting bacteria growth or metabolism and so on. If the high-protein diet and the strong light caused reduced life span for the same reason, then the high-protein diet might mask the negative effects of the strong light. We found that there was a significant interaction between light and sex by ANOVA. Mortality rate parameter analysis indicated that visible light has sex-specific effect on mortality rate parameters. This sexual dimorphism could be due to sex-specific selective pressures that are hypothesized to lead to gene functions that are suboptimal in one or both sexes, thereby potentially contributing to the aging phenotype (sexual antagonistic pleiotropy) (25). The strong light led to decreased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b) in females, but increased initial mortality rate (parameter a) and increased age-dependent mortality rate (parameter b) in males (Table 3). Our previous research found that p53 mutation in Drosophila caused opposite direction changes in mortality rate parameters in females versus males, which are decreased initial mortality rate and increased age-dependent mortality rate in females, but increased initial mortality rate and decreased age-dependent mortality rate in males (7). One possible explanation of the effects of light on mortality rate parameters in females could be that the toxic effect of light might act through DNA damage, and the DNA damage could activate p53 activity, as the pattern of mortality rate parameter changes caused by light is similar to that of p53. However, in males, the pattern of mortality rate parameter changes is different from that of p53. Therefore, other mechanisms would explain the different effects of light on mortality rate parameters in males versus females. Overall, the results reveal that the effect of visible light on survival depends on the protein content of diet, and visible light has sex-specific effect on mortality rate parameters. The results caution that exposure to visible light could be hazardous to life span and suggest that identification of the underlying mechanisms may allow better understanding of the influence of light on longevity. Supplementary Material Supplementary data is available at The Journals of Gerontology, Series A: Biological Sciences and Medical Sciences online. Funding This work was supported by a grant from the National Natural Science Foundation of China (31500970 to J.S.), the Project sponsored by SRF for ROCS, SEM (to J.S.), the Returned Overseas Chinese Scholars Research Merit Aid, Zhejiang [2014]115 (to J.S.), and the Graduate Scientific Research Foundation of Hangzhou Dianzi University (CXJJ2017070 to X.Z.). Conflict of Interest None reported. References 1. Vinogradova IA, Anisimov VN, Bukalev AV, Semenchenko AV, Zabezhinski MA. Circadian disruption induced by light-at-night accelerates aging and promotes tumorigenesis in rats. Aging (Albany, NY) . 2009; 1: 855– 865. doi: 10.18632/aging.100092 Google Scholar CrossRef Search ADS   2. Tucker HA, Petitclerc D, Zinn SA. The influence of photoperiod on body weight gain, body composition, nutrient intake and hormone secretion. J Anim Sci . 1984; 59: 1610– 1620. doi:10.2527/jas1984.5961610x Google Scholar CrossRef Search ADS PubMed  3. Sheeba V, Sharma VK, Shubha K, Chandrashekaran MK, Joshi A. The effect of different light regimes on adult life span in Drosophila melanogaster is partly mediated through reproductive output. J Biol Rhythms . 2000; 15: 380– 392. doi: 10.1177/074873000129001477 Google Scholar CrossRef Search ADS PubMed  4. Northrop JH. The influence of the intensity of light on the rate of growth and duration of life of Drosophila. J Gen Physiol . 1925; 9: 81– 86. doi:10.1085/jgp.9.1.81 Google Scholar CrossRef Search ADS PubMed  5. Weinrich TW, Coyne A, Salt TE, Hogg C, Jeffery G. Improving mitochondrial function significantly reduces metabolic, visual, motor and cognitive decline in aged Drosophila melanogaster. Neurobiol Aging . 2017; 60: 34– 43. doi: 10.1016/j.neurobiolaging.2017.08.016 Google Scholar CrossRef Search ADS PubMed  6. Chen X, Hall H, Simpson JP, Leon-Salas WD, Ready DF, Weake VM. Cytochrome b5 protects photoreceptors from light stress-induced lipid peroxidation and retinal degeneration. NPJ Aging Mech Dis . 2017; 3: 18. doi: 10.1038/s41514-017-0019-6 Google Scholar CrossRef Search ADS PubMed  7. Shen J, Landis GN, Tower J. Multiple metazoan life-span interventions exhibit a sex-specific Strehler-Mildvan inverse relationship between initial mortality rate and age-dependent mortality rate acceleration. J Gerontol A Biol Sci Med Sci . 2017; 72: 44– 53. doi: 10.1093/gerona/glw005 Google Scholar CrossRef Search ADS PubMed  8. Ren C, Webster P, Finkel SE, Tower J. Increased internal and external bacterial load during Drosophila aging without life-span trade-off. Cell Metab . 2007; 6: 144– 152. doi: 10.1016/j.cmet.2007.06.006 Google Scholar CrossRef Search ADS PubMed  9. Shen J, Ford D, Landis GN, Tower J. Identifying sexual differentiation genes that affect Drosophila life span. BMC Geriatr . 2009; 9: 56. doi: 10.1186/1471-2318-9-56 Google Scholar CrossRef Search ADS PubMed  10. Magwere T, Chapman T, Partridge L. Sex differences in the effect of dietary restriction on life span and mortality rates in female and male Drosophila melanogaster. J Gerontol A Biol Sci Med Sci . 2004; 59: 3– 9. doi:10.1093/gerona/59.1.B3 Google Scholar CrossRef Search ADS PubMed  11. Zajitschek F, Zajitschek SR, Friberg U, Maklakov AA. Interactive effects of sex, social environment, dietary restriction, and methionine on survival and reproduction in fruit flies. Age (Dordr) . 2013; 35: 1193– 1204. doi: 10.1007/s11357-012-9445-3 Google Scholar CrossRef Search ADS PubMed  12. Zajitschek F, Jin T, Colchero F, Maklakov AA. Aging differently: diet- and sex-dependent late-life mortality patterns in Drosophila melanogaster. J Gerontol A Biol Sci Med Sci . 2014; 69: 666– 674. doi: 10.1093/gerona/glt158 Google Scholar CrossRef Search ADS PubMed  13. Pletcher SD. Model fitting and hypothesis testing for age-specific mortality data. J Evol Biol . 1999; 12: 430– 439. doi: 10.1046/j.1420-9101. 1999.00058.x Google Scholar CrossRef Search ADS   14. Pfeifer GP. Formation and processing of UV photoproducts: effects of DNA sequence and chromatin environment. Photochem Photobiol . 1997; 65: 270– 283. doi:10.1111/j.1751-1097.1997.tb08560.x Google Scholar CrossRef Search ADS PubMed  15. Santos AL, Oliveira V, Baptista I, et al.   Wavelength dependence of biological damage induced by UV radiation on bacteria. Arch Microbiol . 2013; 195: 63– 74. doi: 10.1007/s00203-012-0847-5 Google Scholar CrossRef Search ADS PubMed  16. Yin R, Dai T, Avci P, et al.   Light based anti-infectives: ultraviolet C irradiation, photodynamic therapy, blue light, and beyond. Curr Opin Pharmacol . 2013; 13: 731– 762. doi: 10.1016/j.coph.2013.08.009 Google Scholar CrossRef Search ADS PubMed  17. Kuse Y, Ogawa K, Tsuruma K, Shimazawa M, Hara H. Damage of photoreceptor-derived cells in culture induced by light emitting diode-derived blue light. Sci Rep . 2014; 4: 5223. doi: 10.1038/srep05223 Google Scholar CrossRef Search ADS PubMed  18. Ciarrocchi G, Sutherland BM, Sutherland JC. Incandescent lamps can produce pyrimidine dimers in DNA. Photochem Photobiol . 1985; 41: 703– 705. doi:10.1111/j.1751-1097.1985.tb03625.x Google Scholar CrossRef Search ADS PubMed  19. Bradley MO, Erickson LC, Kohn KW. Non-enzymatic DNA strand breaks induced in mammalian cells by fluorescent light. Biochim Biophys Acta . 1978; 520: 11– 20. doi:10.1016/0005-2787(78)90003-5 Google Scholar CrossRef Search ADS PubMed  20. Cheng LY, Packer L. Photodamage to hepatocytes by visible light. FEBS Lett . 1979; 97: 124– 128. doi:10.1016/0014-5793(79)80066-6 Google Scholar CrossRef Search ADS PubMed  21. McLay LK, Green MP, Jones TM. Chronic exposure to dim artificial light at night decreases fecundity and adult survival in Drosophila melanogaster. J Insect Physiol . 2017; 100: 15– 20. doi: 10.1016/j.jinsphys.2017.04.009 Google Scholar CrossRef Search ADS PubMed  22. Massie HR, Aiello VR, Williams TR. Influence of photosensitizers and light on the life span of Drosophila. Mech Ageing Dev . 1993; 68: 175– 182. doi:10.1016/0047-6374(93)90149-L Google Scholar CrossRef Search ADS PubMed  23. Tower J, Landis GN, Shen J, et al.   Mifepristone/RU486 acts in Drosophila melanogaster females to counteract the life span-shortening and pro-inflammatory effects of male sex peptide. Biogerontology . 2017; 18: 413– 427. doi: 10.1007/s10522-017-9703-y Google Scholar CrossRef Search ADS PubMed  24. Shen J, Tower J. Drosophila foxo acts in males to cause sexual-dimorphism in tissue-specific p53 life span effects. Exp Gerontol . 2010; 45: 97– 105. doi: 10.1016/j.exger.2009.10.009 Google Scholar CrossRef Search ADS PubMed  25. Pomatto LCD, Tower J, Davies KJA. Sexual dimorphism and aging differentially regulate adaptive homeostasis. J Gerontol A Biol Sci Med Sci . 2018; 73: 141– 149. doi: 10.1093/gerona/glx083 Google Scholar CrossRef Search ADS PubMed  © The Author(s) 2018. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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The Journals of Gerontology Series A: Biomedical Sciences and Medical SciencesOxford University Press

Published: Mar 1, 2018

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