Abstract

Drosophila Hsp70 is a highly conserved molecular chaperone with numerous cytoplasmic targets. Hsp22 is an alpha-crystallin–related chaperone (small hsp) that localizes to the mitochondrial matrix. The hsp70 and hsp22 genes are induced in response to acute heat and oxidative stress and are also upregulated during normal aging. Here the hsp22 promoter (−314 to +10) and the hsp70 promoter (−194 to +10) were used to drive expression of the fluorescent reporter proteins green fluorescent protein (GFP) and Discosoma sp. red fluorescent protein (DsRED) in transgenic flies. Multiple transgenic lines were analyzed under normal culture conditions and under oxidative stress and heat stress conditions that significantly shorten life span. Flies were individually housed, and GFP (or DsRED) was quantified at young-age time points using the fluorescence stereomicroscope and image analysis software. Expression of the hsp reporters in young flies was partially predictive of remaining life span: Young flies with high expression tended to die sooner under both control and stress conditions.

THE reasons for individual variability in life span are not understood and are a topic of active research (1). Only about 30% of life span appears to be “heritable” in humans (and flies) based on standard Mendelian genetic models. Because of the enormous individual variability in aging and life span, chronological age usually does not reflect the physiological age of humans and model organisms. A biomarker of aging, therefore, would be a powerful tool in aging studies. By definition, a biomarker of aging is “a biological parameter of an organism that either alone or in some multivariate composite will, in the absence of disease, better predict functional capability at some late age than will chronological age” (2). Thus, genes whose expression changes during aging are good candidates.

The 14,000 or so genes in Drosophila have been assayed in cross-sectional studies of aging, and only a few hundred change in expression, and they do so in a characteristic and relatively predictable manner (3–5). Some of these changes appear to be conserved in human aging and are therefore of particular interest, including the downregulation of electron transport chain and energy metabolism genes and the tissue-specific upregulation of oxidative stress response genes (6).

The current evolutionary theory of aging suggests that aging in flies and humans results from the decreasing force of natural selection with age (7). This predicts that genes with expression exclusively in very old animals should not exist, and so far there is no data to contradict this idea. Much of the aging-specific gene expression pattern observed in flies and humans should therefore result from normal homeostatic and stress response pathways responding to the particular types of disorganization and damage incurred during aging.

Aging in Drosophila is associated with changes in gene expression similar to an oxidative stress response, including the tissue-specific upregulation of hsp22 and hsp70 gene expression (4,8–10). During normal aging, hsp70 is upregulated preferentially in flight and leg muscle, whereas hsp22 is upregulated in all tissues, especially nervous tissue and retina tissue. Both genes respond to acute heat and oxidative stress; however, hsp22 is relatively more responsive to oxygen stress whereas hsp70 is relatively more responsive to heat stress (4), for as-yet-unknown reasons. Both the hsp70 and hsp22 aging expression patterns require functional heat shock response elements (HSEs) in the promoter (9,10). HSEs are the binding sites for the conserved heat shock factor (HSF; 11,12), and HSF has been shown to be a regular of life span in Caenorhabditis elegans (13–15).

Tissue-specific induction of hsp70 family and hsp22 family genes is also observed in mammals, both during normal aging and in neurodegenerative diseases (6,16). This indicates that hsp gene induction during aging is evolutionarily conserved across a broad range of taxa. Mammalian hsp27 is a critical regulator of apoptosis in neurons and is regulated at both the transcriptional and posttranscriptional levels (17,18). Tissues from old mammals, including skeletal muscle and T cells, exhibit both increased “basal” levels of Hsp70, as well as a reduced accumulation of Hsp70 in response to acute stresses (12,19,20). Strikingly, hsp70 gene alleles and blood Hsp70 levels have been found to correlate with longevity in human studies (21,22), making hsp70 a promising biomarker for human aging. Taken together, the current data suggest that studying hsp gene expression in Drosophila may ultimately inform on human aging mechanisms and health interventions.

In Drosophila, experimental manipulation of hsp gene expression is associated with increased life span under certain conditions and decreased life span under other conditions (23–27). In mammals, both hsp22 family and hsp70 gene expressions are observed in apoptotic cells; however, their function can be proapoptotic or antiapoptotic depending on the tissue and age of the animal (20). Taken together, the data suggest a model in which robust and regulated expression of hsp genes (on and off) favors longevity, whereas accumulation of Hsps to high levels in old animals may be toxic (28–30). Consistent with this idea, it was recently reported that in C. elegans the life span of genetically identical individuals correlates with ability to induce expression of heat shock genes in response to heat stress when they are young (31).

Here Drosophila melanogaster was transformed with constructs containing hsp gene promoter sequences fused to enhanced green fluorescent protein (eGFP), or to DsRED, to test for aging biomarker activity of both Drosophila hsp22 and hsp70. GFP and DsRED expression level was quantified using multiple images of individual flies generated with a fluorescence stereomicroscope. Although there was considerable variability across lines and experiments, both hsp22 and hsp70 transgene expression at early age time points was partially predictive of remaining life span of adult flies during normal aging and when flies were subjected to heat stress and oxidative stress.

MATERIALS AND METHODS

DNA Constructs

Plasmids for making transgenic GFP reporter flies were derived from pGreen pelican (32). phsp22p-Gpel was a derivative of pGreen pelican in which the sequence between the KpnI and BglII sites was replaced by the sequences from −312 to +10 of the hsp22 gene of D. melanogaster, and in phsp70-Gpel, these sequences were replaced by the sequences from −194 to +10 of the hsp70 gene. The hsp gene sequences used in cloning were generated using the following oligonucleotides containing engineered BglII and KpnI sites (underlined): hsp22 forward primer CC AGA TCT TCA ATG TGT CTC TCT GCG, hsp22 reverse primer CC GGT ACC TTT GAA CTG AGA GCG TAG, hsp70 forward primer CC AGA TCT CTC GAG AAA TTT CTC TGG, and hsp70 reverse primer CC GGT ACC GAA TTG AAT TGT CGC TCC. The template for amplification of hsp70 sequences was plasmid pBS70Z (9), and the template for amplification of hsp22 sequences was plasmid “hsp22 5′Δ(−314)” (10). Plasmids for making transgenic DsRED reporter flies were derived from Plasmid pRHP (hsp70core-DsRed-Pelican), which was obtained from James Posakony (University of California, San Diego). The pRHP plasmid was first modified by removing the hsp70 core promoter sequences. This was done using BamHI plus AgeI restriction digestion, followed by treatment with Klenow fragment to fill in 5′ overhangs and generate blunt ends. The linear blunt-ended plasmid was then ligated using DNA ligase to create circular plasmid pRpel. The hsp-DsRED reporter plasmids were then constructed analogous to the construction of the GFP reporters described earlier: phsp22p-Rpel was a derivative of pRpel in which the sequence between the KpnI and BglII sites were replaced by the sequences from −312 to +10 of the hsp22 gene, and in phsp70-Rpel, these sequences were replaced by the sequences from −194 to +10 of the hsp70 gene.

Drosophila P Element–Mediated Transformation

Transgenic fly strains were generated by microinjection of the P-element constructs into fly embryos along with delta2–3 “turbo” helper plasmid (pUChspD2-3wc) as a source of transposase, using standard methods (33). Strains with multiple inserts were generated in order to increase reporter expression levels, as follows: To generate strains with multiple inserts, strains with single inserts were crossed to the delta2-3 transposase source (34) to mobilize the inserts, and chromosomes bearing multiple inserts were first identified by increased expression of the mini-white+ marker gene, and then insert copy number was confirmed using genomic Southern blotting.

Generation of PEPCK-GFP Reporter Flies

A strain of flies was generated where GFP expression is under the control of a promoter that is not induced by heat or oxidative stress, in this case the PEPCK gene promoter. A gene-trap line of genotype w[1118]; P{w[+mGT] = GT1}BG02569 was obtained from Bloomington Drosophila stock center and produces GAL4 protein under the control of PEPCK gene regulatory sequences (35); this strain is hereafter referred to as PEPCK-GAL4. A strain was constructed containing multiple copies of a construct with a upstream activating sequence (UAS) promoter driving expression of eGFP as follows: starting strains were obtained from Ron Davis (Baylor College of Medicine) that contained the UAS-2XeGFP construct (36) inserted on the second chromosome (line U-202-3) and on the third chromosome (line U-307-1). These lines were crossed to a strain bearing the delta2-3 transposase source (34) to mobilize the inserts, and chromosomes were derived that contained multiple copies of the insert on the second and third chromosomes, named UAS-2xEGFP[m5B29] and UAS-2xEGFP[m6B1], respectively, where the “m” stands for multimer derivative chromosome. These second and third chromosomes bearing the multiple inserts were then placed into the same genetic background and made homozygous by appropriate crosses to double-balancer strains, to generate strain w; UAS-2xEGFP[m5B29]; UAS-2xEGFP[m6B1]. This strain was crossed to the PEPCK-GAL4 strain described earlier to generate progeny of genotype w; UAS-2xEGFP[m5B29]/PEPCK-GAL4; UAS-2xEGFP[m6B1]. In these progeny flies, the PEPCK gene regulatory sequences drive expression of GAL4 transcription factor, which in turn binds to the multiple UAS promoter constructs to drive expression of eGFP. Therefore, in these flies the GFP expression is ultimately driven by the regulatory sequences of PEPCK, and they are hereafter referred to as “PEPCK-GFP” reporter flies.

Drosophila Culture

Flies were cultured as previously described (4). Newly eclosed male flies were collected over a period of 24 hours, maintained at 25°C at 10 per vial in culture vials with food. All flies were transferred every other day into fresh media. At 4 days of age, flies were transferred to fresh media at one fly per vial. Each fly was given a specific number for the purpose of measuring its life span and reporter expression. The time of death of the flies was recorded at every transfer. For normal aging assays, flies were kept in an incubator at 25°C on a 12-h:12-h light–dark cycle.

Oxygen Stress Assay

Flies were treated in an enclosed chamber with 100% oxygen gas flow and transferred to fresh media every day, as previously described (4). GFP or DsRED expression level for each fly was assayed every other day (days 2, 4, and 6).

Heat Stress Assay

Flies were maintained in a 34°C incubation chamber and transferred to fresh media every day. GFP or DsRED expression level for each fly was assayed every other day (days 2, 4, and 6).

Quantification of GFP Expression in Live Flies

GFP fluorescence levels for each fly at each time point were determined from triplicate fluorescence images generated with the Leica MZFLIII fluorescence stereomicroscope (Leica, Inc., Deerfield, IL) and SPOT and Image-plus software, as previously described (4). This method yields GFP density, which is the average of green pixel numbers in the digital pictures, which is a measure of how green the picture is in red/green/blue (RGB) space. For clarity of presentation, the images of flies presented in Figure 1B were adjusted by increasing the contrast enhancement setting gamma from 1 to 1.6. Each data set was also analyzed using a custom Matlab script to quantify the GFP intensity of the fly, where GFP intensity is the hue value of a specific green wavelength (510 nm) with fixed pixel number, which indicates how bright the color is in HSL (hue/saturation/lightness) space. Similar results were obtained with both quantification methods (data not shown): Greater GFP expression should produce more emission of green light, thereby making the picture both greener and brighter, and therefore values calculated from both methods are reflective of GFP levels in the flies. The DsRED expression levels were quantified using analogous RGB methods.

Figure 1.

Transgenic hsp22 and hsp70 reporters. (A), Construct maps. The vector region between the P element inverted repeats (P) is diagrammed at the top, and the hsp gene sequences are diagrammed below. Solid boxes (I) indicate the insulator elements. (B) Image capture assay. Representative images are presented for male flies of the hsp22-GFP and hsp70-GFP transgenic strains under normal aging conditions (young = 4-d old; old = 70-d old) and heat stress (3 d at 34°C) and oxidative stress conditions (4 d in oxygen stress), as indicated. For each fly, the GFP fluorescence image is presented to the left and an overlay of the GFP and visible images is presented to the right. The young fly pictures are from line hsp22-GFP(3)1/TM3 Sb e and hsp70-GFP(3)2/TM3 Sb e. All other pictures are from lines hsp22-GFP(3)1 MI1/TM3 Sb e and hsp70-GFP(3)2 MI4/TM3 Sb e.

Figure 1.

Transgenic hsp22 and hsp70 reporters. (A), Construct maps. The vector region between the P element inverted repeats (P) is diagrammed at the top, and the hsp gene sequences are diagrammed below. Solid boxes (I) indicate the insulator elements. (B) Image capture assay. Representative images are presented for male flies of the hsp22-GFP and hsp70-GFP transgenic strains under normal aging conditions (young = 4-d old; old = 70-d old) and heat stress (3 d at 34°C) and oxidative stress conditions (4 d in oxygen stress), as indicated. For each fly, the GFP fluorescence image is presented to the left and an overlay of the GFP and visible images is presented to the right. The young fly pictures are from line hsp22-GFP(3)1/TM3 Sb e and hsp70-GFP(3)2/TM3 Sb e. All other pictures are from lines hsp22-GFP(3)1 MI1/TM3 Sb e and hsp70-GFP(3)2 MI4/TM3 Sb e.

Statistical Analysis of GFP and DsRED Expression

Linear regression analysis was conducted to determine the significance of the correlation between GFP expression and life span (if any), using SPSS statistical software. Both the hsp-GFP strain and the PEPCK-GFP strain were analyzed. First, each data set was tested to confirm that the data conformed to a normal distribution using Shapiro–Wilks test, and each data set had a normal distribution except for one. The one nonnormal data set could not be corrected by transforming the data and was therefore discarded. For the regression analyses, the predictor variables were always GFP levels, whereas the outcome variable was always life span. Adjusted R2, significance of the Predictor, and standardized beta are presented for each data set (Table 2).

RESULTS

Longitudinal Assay of GFP and DsRED Reporter Expression

Transgenic fly strains were generated where GFP or DsRED expression was under the control of the regulatory regions of either the hsp70 gene or the hsp22 gene (Figure 1A), whereas in control flies GFP expression was driven by the regulatory region of the PEPCK gene (Materials and Methods). PEPCK was chosen because it is not induced by heat or oxidative stress, and in this way serves as one control to demonstrate that any relationship between transgene expression and life span that might be observed with the hsp reporters is not simply due to a correlation between life span and global levels of transcription, translation, or GFP turnover. The hsp transgenic strains generated and analyzed in this study are listed along with a summary of results (Table 1). Age-synchronized cohorts of approximately 50 male flies were generated for each strain. Reporter expression was assayed at three young-age time points: 10, 20, and 30 days for normal aging conditions and at 2, 4, and 6 days for oxygen stress and heat stress conditions where life span was reduced. This allowed for assay of most flies before significant mortality of the cohort had begun (Figure 2), which is the time period at which a predictive biomarker would be most useful. The flies were maintained individually and transferred to fresh culture vials every other day, so that GFP or DsRED intensity could be correlated with individual life spans. GFP and DsRED intensity was quantified at each time point by briefly anesthetizing the fly with CO2 gas and then taking three photographs of the fluorescence of the fly using the Leica MZFLIII fluorescence stereomicroscope; and this assay has little to no effect on fly life span (4). Representative images of GFP fluorescence from transgenic reporter flies are presented (Figure 1B), and as expected, the expression of both hsp22 and hsp70 transgenic reporters increased during aging and in response to heat and oxygen stress. Image analysis software was used to outline the part of the image representing the flies’ body, and the pixel intensity in that region of the three pictures was averaged. The GFP or DsRED intensity measured for each fly at each age time point was then correlated with the subsequent life span of the flies. Experiments were conducted under normal culture conditions, as well as under heat stress conditions and with exposure to 100% oxygen atmosphere. Statistical significance of the correlations of GFP or DsRED expression and life span was determined using linear regression to compare life span and fluorescence for each cohort in each experiment (Figure 3A; Table 2; data summarized in Table 1). For ease of presentation and comparison of certain aspects of the data, the life span for flies was separated in to three groups containing equal numbers of flies, short lived, medium lived, and long lived, and the average plus or minus standard deviation of GFP or DsRED intensity in each group at each time point is presented in bar graph form (Figures 3 and 4).

Table 1.

Transgenic Reporter Strains and Summary of Results

Strain Name Inserts Predictivity
 
Aging Oxygen Heat 
hsp22-GFP(2)1 nc [67] Neg (1) [10] Neg (1)* [5] 
hsp22-GFP(3)1/TM3 Neg (2) [74] Neg (1,2,3) [13] Nc* [10] 
hsp22-GFP(3)1MI1/TM3 Neg (3) [56] Neg (2)* [10] Nc† [6] 
hsp22-DsRed(3)1/TM3 ND Nc† [7] nc† [4] 
hsp70-GFP(3)1 MI2/TM3 Neg (2,3) [52] Nc* [15] Nc† [10] 
hsp70-GFP(3)2/TM3 nc [80] Neg (1) [10] ND 
hsp70-GFP(3)2 MI4/TM3 Neg (2,3) [60] Nc* [8] Nc† [13] 
hsp70-DsRed(3)1 MI2/TM3 ND Nc† [14] Neg (1)† [12] 
PEPCK-GFP 1, >4‡ nc [77] nc [11] ND 
Strain Name Inserts Predictivity
 
Aging Oxygen Heat 
hsp22-GFP(2)1 nc [67] Neg (1) [10] Neg (1)* [5] 
hsp22-GFP(3)1/TM3 Neg (2) [74] Neg (1,2,3) [13] Nc* [10] 
hsp22-GFP(3)1MI1/TM3 Neg (3) [56] Neg (2)* [10] Nc† [6] 
hsp22-DsRed(3)1/TM3 ND Nc† [7] nc† [4] 
hsp70-GFP(3)1 MI2/TM3 Neg (2,3) [52] Nc* [15] Nc† [10] 
hsp70-GFP(3)2/TM3 nc [80] Neg (1) [10] ND 
hsp70-GFP(3)2 MI4/TM3 Neg (2,3) [60] Nc* [8] Nc† [13] 
hsp70-DsRed(3)1 MI2/TM3 ND Nc† [14] Neg (1)† [12] 
PEPCK-GFP 1, >4‡ nc [77] nc [11] ND 

Notes: The hsp22GFP(2)1 insert is on the second chromosome and is homozygous. The remaining inserts are on the third chromosome and are balanced over TM3, Sb, e. Numbers in parentheses indicate at which of the three time points (TP1, TP2, TP3) a significant negative (Neg) correlation between GFP intensity and subsequent life span was detected by regression analysis (p < .05). ND = assay not done; nc = no significant correlation detected. Certain experiments included less than three time points due to the limited survival of the flies.

*

Experiments that included only two time points (TP1 and TP2).

Experiments that included only one time point (TP1).

The PEPCK-GFP reporter flies contain one insert of the PEPCK-GAL4 gene trap and ≥4 inserts of the UAS-GFP construct (materials and methods). The median life span of each cohort is indicated in brackets.

Table 2.

Regression Analyses

 GFP at TP1 GFP at TP2 GFP at TP3 
Normal aging    
    hsp22GFP(3)1/TM3 Sb e    
        N 43 41 40 
        Adjusted R2 .017 .141 .000 
        Significance of predictor .198 .015 .960 
        Standardized beta −.200 −.376 −.008 
    hsp22GFP(2)1    
        N 38 38 35 
        Adjusted R2 .069 .012 .007 
        Significance of predictor .061 .234 .271 
        Standardized beta −.307 −.198 −.191 
    hsp22 GFP (3)1MI1/TM3 Sb e    
        N 45 45 43 
        Adjusted R2 −.022 −.023 .237 
        Significance of predictor .850 .918 .001 
        Standardized beta −.029 .016 −.505 
    hsp70 GFP (3)2/TM3 Sb e    
        N 45 45 45 
        Adjusted R2 −.019 −.007 −.019 
        Significance of predictor .672 .408 .666 
        Standardized beta .065 .126 .066 
    hsp70 GFP (3)2MI4/TM3 Sb e    
        N 48 47 47 
        Adjusted R2 .008 .116 .064 
        Significance of predictor .246 .011 .047 
        Standardized beta −.171 −.368 −.291 
    hsp70 GFP (3)1MI2/TM3 Sb e    
        N 47 46 44 
        Adjusted R2 .000 .064 .120 
        Significance of predictor .320 .049 .012 
        Standardized beta −.148 −.292 −.374 
    PEPCK-GFP    
        N 46 46 45 
        Adjusted R2 −.006 −.023 .002 
        Significance of predictor .402 .952 .304 
        Standardized beta .127 .009 −.157 
Oxygen stress    
    hsp22 GFP (3)1/TM3 Sb e    
        N 29 29 29 
        Adjusted R2 .234 .151 .193 
        Significance of predictor .005 .021 .010 
        Standardized beta −.511 −.425 −.471 
    hsp22 GFP (2)1    
        N 28 27 27 
        Adjusted R2 .123 .051 .054 
        Significance of predictor .038 .135 .128 
        Standardized beta −.394 −.295 −.301 
    hsp22 GFP (3)1MI1/TM3 Sb e    
        N 29 29  
        Adjusted R2 .084 .285  
        Significance of predictor .070 .002  
        Standardized beta −.341 −.557  
    hsp70 GFP (3)2/TM3 Sb e    
        N 30 30 29 
        Adjusted R2 .113 −.034 −.029 
        Significance of predictor .039 .831 .649 
        Standardized beta −.379 .041 −.088 
    hsp70 GFP (3)2MI4/TM3 Sb e    
        N 30 30  
        Adjusted R2 .031 −.036  
        Significance of predictor .175 .969  
        Standardized beta −.254 −.007  
    hsp70 GFP (3)1MI2/TM3 Sb e    
        N 30 30  
        Adjusted R2 −.033 .041  
        Significance of predictor .780 .146  
        Standardized beta −.053 −.272  
    PEPCK-GFP    
        N 30 30 30 
        Adjusted R2 −.030 −.020 .002 
        Significance of predictor .709 .517 .315 
        Standardized beta −.071 −.123 −.190 
Heat stress    
    hsp22 GFP (3)1/TM3 Sb e    
        N 48 47  
        Adjusted R2 −.021 −.007  
        Significance of predictor .860 .421  
        Standardized beta −.026 .120  
    hsp22 GFP (2)1    
        N 49 32  
        Adjusted R2 .088 −.021  
        Significance of predictor .022 .545  
        Standardized beta −.328 −.111  
    hsp22 GFP (3)1MI1/TM3 Sb e    
        N 50   
        Adjusted R2 −.020   
        Significance of predictor .816   
        Standardized beta −.034   
    hsp70 GFP (3)2MI4/TM3 Sb e    
        N 39   
        Adjusted R2 .020   
        Significance of predictor .191   
        Standardized beta −.214   
    hsp70 GFP (3)1MI2/TM3 Sb e    
        N 47   
        Adjusted R2 .004   
        Significance of predictor .281   
        Standardized beta −.161   
 DsRed at TP1   
Oxygen stress    
    hsp22 DsRed (3)1/TM3 Sb e    
        N 26   
        Adjusted R2 −.022   
        Significance of predictor .507   
        Standardized beta .136   
    hsp70 DsRed (3)1MI2/TM3 Sb e    
        N 30   
        Adjusted R2 −.033   
        Significance of predictor .808   
        Standardized beta −.046   
Heat stress    
    hsp22 DsRed (3)1/TM3 Sb e    
        N 22   
        Adjusted R2 .058   
        Significance of predictor .146   
        Standardized beta −.320   
    hsp70 DsRed (3)1MI2/TM3 Sb e    
        N 33   
        Adjusted R2 .200   
        Significance of predictor .005   
        Standardized beta −.474   
 GFP at TP1 GFP at TP2 GFP at TP3 
Normal aging    
    hsp22GFP(3)1/TM3 Sb e    
        N 43 41 40 
        Adjusted R2 .017 .141 .000 
        Significance of predictor .198 .015 .960 
        Standardized beta −.200 −.376 −.008 
    hsp22GFP(2)1    
        N 38 38 35 
        Adjusted R2 .069 .012 .007 
        Significance of predictor .061 .234 .271 
        Standardized beta −.307 −.198 −.191 
    hsp22 GFP (3)1MI1/TM3 Sb e    
        N 45 45 43 
        Adjusted R2 −.022 −.023 .237 
        Significance of predictor .850 .918 .001 
        Standardized beta −.029 .016 −.505 
    hsp70 GFP (3)2/TM3 Sb e    
        N 45 45 45 
        Adjusted R2 −.019 −.007 −.019 
        Significance of predictor .672 .408 .666 
        Standardized beta .065 .126 .066 
    hsp70 GFP (3)2MI4/TM3 Sb e    
        N 48 47 47 
        Adjusted R2 .008 .116 .064 
        Significance of predictor .246 .011 .047 
        Standardized beta −.171 −.368 −.291 
    hsp70 GFP (3)1MI2/TM3 Sb e    
        N 47 46 44 
        Adjusted R2 .000 .064 .120 
        Significance of predictor .320 .049 .012 
        Standardized beta −.148 −.292 −.374 
    PEPCK-GFP    
        N 46 46 45 
        Adjusted R2 −.006 −.023 .002 
        Significance of predictor .402 .952 .304 
        Standardized beta .127 .009 −.157 
Oxygen stress    
    hsp22 GFP (3)1/TM3 Sb e    
        N 29 29 29 
        Adjusted R2 .234 .151 .193 
        Significance of predictor .005 .021 .010 
        Standardized beta −.511 −.425 −.471 
    hsp22 GFP (2)1    
        N 28 27 27 
        Adjusted R2 .123 .051 .054 
        Significance of predictor .038 .135 .128 
        Standardized beta −.394 −.295 −.301 
    hsp22 GFP (3)1MI1/TM3 Sb e    
        N 29 29  
        Adjusted R2 .084 .285  
        Significance of predictor .070 .002  
        Standardized beta −.341 −.557  
    hsp70 GFP (3)2/TM3 Sb e    
        N 30 30 29 
        Adjusted R2 .113 −.034 −.029 
        Significance of predictor .039 .831 .649 
        Standardized beta −.379 .041 −.088 
    hsp70 GFP (3)2MI4/TM3 Sb e    
        N 30 30  
        Adjusted R2 .031 −.036  
        Significance of predictor .175 .969  
        Standardized beta −.254 −.007  
    hsp70 GFP (3)1MI2/TM3 Sb e    
        N 30 30  
        Adjusted R2 −.033 .041  
        Significance of predictor .780 .146  
        Standardized beta −.053 −.272  
    PEPCK-GFP    
        N 30 30 30 
        Adjusted R2 −.030 −.020 .002 
        Significance of predictor .709 .517 .315 
        Standardized beta −.071 −.123 −.190 
Heat stress    
    hsp22 GFP (3)1/TM3 Sb e    
        N 48 47  
        Adjusted R2 −.021 −.007  
        Significance of predictor .860 .421  
        Standardized beta −.026 .120  
    hsp22 GFP (2)1    
        N 49 32  
        Adjusted R2 .088 −.021  
        Significance of predictor .022 .545  
        Standardized beta −.328 −.111  
    hsp22 GFP (3)1MI1/TM3 Sb e    
        N 50   
        Adjusted R2 −.020   
        Significance of predictor .816   
        Standardized beta −.034   
    hsp70 GFP (3)2MI4/TM3 Sb e    
        N 39   
        Adjusted R2 .020   
        Significance of predictor .191   
        Standardized beta −.214   
    hsp70 GFP (3)1MI2/TM3 Sb e    
        N 47   
        Adjusted R2 .004   
        Significance of predictor .281   
        Standardized beta −.161   
 DsRed at TP1   
Oxygen stress    
    hsp22 DsRed (3)1/TM3 Sb e    
        N 26   
        Adjusted R2 −.022   
        Significance of predictor .507   
        Standardized beta .136   
    hsp70 DsRed (3)1MI2/TM3 Sb e    
        N 30   
        Adjusted R2 −.033   
        Significance of predictor .808   
        Standardized beta −.046   
Heat stress    
    hsp22 DsRed (3)1/TM3 Sb e    
        N 22   
        Adjusted R2 .058   
        Significance of predictor .146   
        Standardized beta −.320   
    hsp70 DsRed (3)1MI2/TM3 Sb e    
        N 33   
        Adjusted R2 .200   
        Significance of predictor .005   
        Standardized beta −.474   

TP1 = time point 1; TP2 = time point 2; TP3 = time point 3.

Figure 2.

Survival curves for transgenic fly cohorts. (A) Survival curves for flies under normal aging conditions. Time points for fluorescence assay were 10 d (time point 1), 20 d (time point 2), and 30 d (time point 3), respectively. (B) Survival curves for flies under oxygen stress conditions. Time points for fluorescence assay were 2 d (time point 1), 4 d (time point 2), and 6 d (time point 3), respectively. (C) Survival curves for flies under heat stress conditions. Time points for fluorescence assay were 2 d (time point 1), 4 d (time point 2), and 6 d (time point 3), respectively. Median life spans for each cohort are summarized in Table 1.

Figure 2.

Survival curves for transgenic fly cohorts. (A) Survival curves for flies under normal aging conditions. Time points for fluorescence assay were 10 d (time point 1), 20 d (time point 2), and 30 d (time point 3), respectively. (B) Survival curves for flies under oxygen stress conditions. Time points for fluorescence assay were 2 d (time point 1), 4 d (time point 2), and 6 d (time point 3), respectively. (C) Survival curves for flies under heat stress conditions. Time points for fluorescence assay were 2 d (time point 1), 4 d (time point 2), and 6 d (time point 3), respectively. Median life spans for each cohort are summarized in Table 1.

Figure 3.

GFP levels of flies with different life spans under normal aging conditions. Image capture was performed in triplicate for each fly at time point 1 (TP1 = Day 10), time point 2 (TP2 = Day 20), and time point 3 (TP3 = Day 30). (A) Scatter plot, line hsp22-GFP (3)1/TM3 Sb e, data for time point 3. (B–D) The data for the flies were divided into three equal groups based on their life spans. (B) hsp22-GFP(3)1MI1/TM3 Sb e. (C) hsp70-GFP(3)2MI4/TM3 Sb e. (D) PEPCK-GFP.

Figure 3.

GFP levels of flies with different life spans under normal aging conditions. Image capture was performed in triplicate for each fly at time point 1 (TP1 = Day 10), time point 2 (TP2 = Day 20), and time point 3 (TP3 = Day 30). (A) Scatter plot, line hsp22-GFP (3)1/TM3 Sb e, data for time point 3. (B–D) The data for the flies were divided into three equal groups based on their life spans. (B) hsp22-GFP(3)1MI1/TM3 Sb e. (C) hsp70-GFP(3)2MI4/TM3 Sb e. (D) PEPCK-GFP.

Figure 4.

GFP level of flies with different life span ranges under oxygen stress. Image capture was performed in triplicate for each fly at time point 1 (TP1 = Day 2), time point 2 (TP2 = Day 4), and time point 3 (TP3 = Day 6). (A) Scatter plot, line hsp22-GFP (3)1/TM3 Sb e, data for time point 1. (B–D) The data for the flies were divided into three equal groups based on their life spans. (B) hsp22-GFP(3)/TM3 Sb e. (C) hsp70-GFP(3)1MI2/TM3 Sb e. (D) PEPCK-GFP.

Figure 4.

GFP level of flies with different life span ranges under oxygen stress. Image capture was performed in triplicate for each fly at time point 1 (TP1 = Day 2), time point 2 (TP2 = Day 4), and time point 3 (TP3 = Day 6). (A) Scatter plot, line hsp22-GFP (3)1/TM3 Sb e, data for time point 1. (B–D) The data for the flies were divided into three equal groups based on their life spans. (B) hsp22-GFP(3)/TM3 Sb e. (C) hsp70-GFP(3)1MI2/TM3 Sb e. (D) PEPCK-GFP.

Previously, the expression pattern of hsp22 and hsp70 during aging has been characterized using Northern blots, Western blots, and transgenic reporter constructs where the hsp22 gene region from −314 to +275 and the hsp70 gene region from −194 to +276 were fused to LacZ. In those studies, the expression of hsp22 during aging was tissue general (10), whereas hsp70 expression was preferentially observed in flight muscle and leg muscle (8,9). In the present experiments, the hsp70-GFP reporter was expressed in other tissues in addition to flight and leg muscle, including the head and abdomen (Figure 1B). The reason for this apparently broader distribution of the hsp70-GFP reporter relative to the hsp70-LacZ reporters may be the smaller amount of hsp70 gene sequences present in the hsp70-GFP construct (−194 to +10) and/or differences in the stability and resolution afforded by GFP relative to LacZ.

hsp Expression and Drosophila Life Span Under Normal Aging Conditions

When adult flies were cultured under normal aging conditions, GFP levels were negatively correlated with remaining life span for two out of three hsp22-GFP lines assayed, at a subset of the young time points (Table 1). For example, flies of line hsp22-GFP(3)1MI1 that had lower expression of GFP at 30 days of age (time point 3) tended to be longer lived than their siblings (Figure 3A and B). Similarly, GFP levels were negatively correlated with remaining life span for two out of three hsp70-GFP lines assayed, at a subset of the young time points (Figure 3C; Table 1). No correlation was observed between GFP expression and life span with the PEPCK-GFP control at any time points in any experiment (Figure 3D; Table 1).

hsp Expression and Drosophila Life Span Under Oxidative Stress Conditions

When adult flies were cultured in 100% oxygen atmosphere, life spans were dramatically reduced, as expected (Figure 1; Table 1). Under these oxidative stress conditions, expression levels were negatively correlated with remaining life spans for three out of four hsp22 reporter lines assayed and for one out of four hsp70 reporter lines, at a subset of young time points (Figure 4 and Table 2), whereas again no correlation was observed for the PEPCK control strain.

hsp Expression and Drosophila Life Span Under Heat Stress Conditions

When flies were cultured at an elevated temperature (34°C), life spans were again significantly reduced relative to normal culture conditions, as expected (Figure 1; Table 1). Under these heat stress conditions, expression levels were negatively correlated with remaining life spans for one out of four hsp22 reporter lines and for one out of three hsp70 reporter lines (Table 2). No correlation was observed for the PEPCK control strain.

DISCUSSION

In transgenic lines where hsp22 and hsp70 gene promoters were used to drive expression of eGFP or DsRED, the fluorescence intensity could be assayed longitudinally and correlated with individual life span. The hsp22 and hsp70 genes are known to be induced in response to heat and oxidative stress and to be induced during normal aging. Consistent with this, in the longitudinal assays of individual flies, the expression of the hsp22 and hsp70 reporters was generally observed to increase with age and duration of stress treatment. However, at the level of cohorts of flies, the changes in average expression with age and duration of stress treatment were more complex. For most cohorts, the average level of expression increased across the three time points in concordance with the increase in expression level in the individual flies (e.g., see Figure 3B and C; Figure 4B). In contrast, for certain cohorts, the average expression level remained relatively constant with time, or actually went down, for example the line hsp70-GFP(3)1MI2 with oxygen stress (Figure 4C). We conclude that this decrease in average expression in certain cohorts is due to “cohort effects”: because the most highly expressing flies die earlier, this can sometimes produce a decrease in the average expression of the cohort over certain time intervals.

In the experiments where a significant correlation was observed, the expression of the hsp reporters was always negatively correlated with life span under both normal and stress conditions. The negative correlation between hsp reporter expression and life span is likely related to the fact that these genes are induced in response to stress; flies experiencing a relatively larger degree of physiological stress are expected to exhibit a larger induction of the transgene and may survive for a shorter period due to the life-shortening effects of that stress. This result is somewhat counterintuitive in relation to studies where hsp gene expression has been examined in animals that have been genetically selected for increased life span: In cross-sectional assays of control and long-lived fly strains, the long-lived strains exhibited higher levels of hsp22 RNA (37). Moreover, in C. elegans strains that are long lived due to reduced insulin/insulin like growth factor 1-like signaling, the long-lived strains exhibit higher levels of expression of certain small hsp genes in response to heat stress (38). We conclude that the correlation between longevity and robust hsp expression in such cross-sectional assays indicates a more effective stress response, likely involving the ability to efficiently turn the genes off as well as on. Consistent with this idea, in young C. elegans, the level of induction of a shsp reporter in response to a mild and transient heat stress is positively correlated with remaining life span (31), consistent with the idea that animals with a more robust stress response live longer. In contrast, in longitudinal assays of individual animals under normal conditions or constant stress, the level of hsp reporter expression may be indicative of that particular individuals’ susceptibility to stress, failing homeostasis and imminent mortality. In other words, in cross-sectional comparisons of strains with different life spans, the induction of hsp genes positively correlates with life span, whereas within a given strain, the longitudinal time course of hsp gene expression in an individual animal is negatively correlated with remaining life span. In the future, the longitudinal assay of the Drosophila hsp reporters in control and long-lived genetic backgrounds should allow for definitive tests of this model.

One possible way that the correlation between life span and hsp-GFP reporter expression could be an artifact would be if GFP expression itself were having a significant negative effect on life span. For example, the PEPCK-GFP control flies had lower expression of GFP at late ages than did the hsp-GFP flies, and conceivably the GFP itself could have been toxic to the flies. However, the PEPCK-GFP flies had GFP expression at time point 1 that was equal to that of several hsp-GFP lines (compare Figure 3D with 3B), yet these PEPCK-GFP flies had normal life span and no correlation between GFP expression and life span. Moreover, the hsp70-GFP(3)2 strain had robust GFP expression at late ages and the longest life span of all the strains analyzed (Table 1). Therefore, there was no evidence for a negative effect of GFP itself on life span.

The Drosophila Drosomycin gene encodes a small peptide that is induced in response to microbial (fungal) infections and has antimicrobial properties (39). Previously, a transgenic reporter construct consisting of the Drosomycin gene promoter fused to GFP was analyzed in young adult flies and shown to be partially predictive of remaining life span (4). Similar to the hsp gene reporters, the Drosomycin-GFP reporter was negatively correlated with life span, in that young flies with high expression tended to die sooner. Flies cultured in the absence of detectable microbes and in the presence of antimicrobial drugs had unchanged life spans (40), indicating that microbes do not typically limit life span in the laboratory, and making it unlikely that the predictive power of the Drosomycin reporter was due to a response to some life span–limiting infection. However, antimicrobial peptides can sometimes have additional functions, for example the human Hepcidin antimicrobial peptide is also a critical regulator of iron homeostasis (41). Like hsp70 and hsp22, the Drosophila Drosomycin gene is induced in response to oxidative stress and during normal aging (4). Because oxidative stress appears to increase during aging, it may be the ability of the hsp70, hsp22, and Drosomycin genes to respond to oxidative stress that marks a physiologically older fly.

The ability of the Drosophila hsp22 and hsp70 reporters to act as predictors of remaining life span is promising; however, the predictive power is partial. One way, we are attempting to improve the predictive power is to further increase the copy number of the reporter constructs in the same fly strain, in an attempt to produce higher levels of expression. Similarly, we are developing more sensitive video-based methods for continuous and longitudinal assay of GFP fluorescence levels during fly aging (D. Grover, J. Yang, S. Tavaré, and J. Tower, 2009, unpublished data). Another approach will be to combine two different gene reporters in the same strain, for example hsp22-GFP along with hsp70-DsRED, and such strains are under construction. Even the partial predictive power of the present strains and assays should be useful in experiments such as in genetic screens designed to identify life span regulators, by screening for increased or decreased reporter expression in young- or middle-aged animals.

FUNDING

This work was supported by a grant from the Department of Health and Human Services, National Institute on Aging, to J.T. (AG11833), and by pilot project funding from the Southern California Environmental Health Sciences Center, which is funded by a grant from the National Institute of Environmental Health Sciences (5P30ES007048). J.Y. was supported in part by the Genetics, Molecular, and Cellular Biology Training Grant (T32GM067587).

We thank Morris Waskar for generating the UAS-2XeGFP multimer strains, Christina Curtis for comments on the manuscript draft, and Dhruv Grover for advice on data analysis and statistics.

References

1.
Kirkwood
TB
Feder
M
Finch
CE
, et al.  . 
What accounts for the wide variation in life span of genetically identical organisms reared in a constant environment?
Mech Ageing Dev
 , 
2005
, vol. 
126
 (pg. 
439
-
443
)
2.
Sprott
RL
Biomarkers of aging
Exp Gerontol
 , 
1988
, vol. 
23
 (pg. 
1
-
3
)
3.
Pletcher
SD
Macdonald
SJ
Marguerie
R
, et al.  . 
Genome-wide transcript profiles in aging and calorically restricted Drosophila melanogaster
Curr Biol
 , 
2002
, vol. 
12
 (pg. 
712
-
723
)
4.
Landis
GN
Abdueva
D
Skvortsov
D
, et al.  . 
Similar gene expression patterns characterize aging and oxidative stress in Drosophila melanogaster
Proc Natl Acad Sci U S A
 , 
2004
, vol. 
101
 (pg. 
7663
-
7668
)
5.
Girardot
F
Lasbleiz
C
Monnier
V
Tricoire
H
Specific age-related signatures in Drosophila body parts transcriptome
BMC Genomics
 , 
2006
, vol. 
7
 pg. 
69
 
6.
Zahn
JM
Sonu
R
Vogel
H
, et al.  . 
Transcriptional profiling of aging in human muscle reveals a common aging signature
PLoS Genet
 , 
2006
, vol. 
2
 pg. 
e115
 
7.
Hughes
KA
Reynolds
RM
Evolutionary and mechanistic theories of aging
Annu Rev Entomol
 , 
2005
, vol. 
50
 (pg. 
421
-
445
)
8.
Wheeler
JC
Bieschke
ET
Tower
J
Muscle-specific expression of Drosophila hsp70 in response to aging and oxidative stress
Proc Natl Acad Sci U S A
 , 
1995
, vol. 
92
 (pg. 
10408
-
10412
)
9.
Wheeler
JC
King
V
Tower
J
Sequence requirements for upregulated expression of Drosophila hsp70 transgenes during aging
Neurobiol Aging
 , 
1999
, vol. 
20
 (pg. 
545
-
553
)
10.
King
V
Tower
J
Aging-specific expression of Drosophila hsp22
Dev Biol
 , 
1999
, vol. 
207
 (pg. 
107
-
118
)
11.
Jedlicka
P
Mortin
MA
Wu
C
Multiple functions of Drosophila heat shock transcription factor in vivo
EMBO J
 , 
1997
, vol. 
16
 (pg. 
2452
-
2462
)
12.
Jurivich
DA
Choo
M
Welk
J
Qiu
L
Han
K
Zhou
X
Human aging alters the first phase of the molecular response to stress in T-cells
Exp Gerontol
 , 
2005
, vol. 
40
 (pg. 
948
-
958
)
13.
Garigan
D
Hsu
AL
Fraser
AG
Kamath
RS
Ahringer
J
Kenyon
C
Genetic analysis of tissue aging in Caenorhabditis elegans: a role for heat-shock factor and bacterial proliferation
Genetics
 , 
2002
, vol. 
161
 (pg. 
1101
-
1112
)
14.
Hsu
AL
Murphy
CT
Kenyon
C
Regulation of aging and age-related disease by DAF-16 and heat-shock factor
Science
 , 
2003
, vol. 
300
 (pg. 
1142
-
1145
)
15.
Morley
JF
Morimoto
RI
Regulation of longevity in Caenorhabditis elegans by heat shock factor and molecular chaperones
Mol Biol Cell
 , 
2004
, vol. 
15
 (pg. 
657
-
664
)
16.
Schultz
C
Dick
EJ
Cox
AB
Hubbard
GB
Braak
E
Braak
H
Expression of stress proteins alpha B-crystallin, ubiquitin, and hsp27 in pallido-nigral spheroids of aged rhesus monkeys
Neurobiol Aging
 , 
2001
, vol. 
22
 (pg. 
677
-
682
)
17.
Benn
SC
Perrelet
D
Kato
AC
, et al.  . 
Hsp27 upregulation and phosphorylation is required for injured sensory and motor neuron survival
Neuron
 , 
2002
, vol. 
36
 (pg. 
45
-
56
)
18.
Lewis
SE
Mannion
RJ
White
FA
, et al.  . 
A role for HSP27 in sensory neuron survival
J Neurosci
 , 
1999
, vol. 
19
 (pg. 
8945
-
8953
)
19.
Broome
CS
Kayani
AC
Palomero
J
, et al.  . 
Effect of lifelong overexpression of HSP70 in skeletal muscle on age-related oxidative stress and adaptation after nondamaging contractile activity
FASEB J
 , 
2006
, vol. 
20
 (pg. 
1549
-
1551
)
20.
Chung
L
Ng
YC
Age-related alterations in expression of apoptosis regulatory proteins and heat shock proteins in rat skeletal muscle
Biochim Biophys Acta
 , 
2006
, vol. 
1762
 (pg. 
103
-
109
)
21.
Singh
R
Kolvraa
S
Bross
P
, et al.  . 
Heat-shock protein 70 genes and human longevity: a view from Denmark
Ann N Y Acad Sci
 , 
2006
, vol. 
1067
 (pg. 
301
-
308
)
22.
Terry
DF
Wyszynski
DF
Nolan
VG
, et al.  . 
Serum heat shock protein 70 level as a biomarker of exceptional longevity
Mech Ageing Dev
 , 
2006
, vol. 
127
 (pg. 
862
-
868
)
23.
Zhao
Y
Sun
H
Lu
J
, et al.  . 
Lifespan extension and elevated hsp gene expression in Drosophila caused by histone deacetylase inhibitors
J Exp Biol
 , 
2005
, vol. 
208
 (pg. 
697
-
705
)
24.
Bhole
D
Allikian
MJ
Tower
J
Doxycycline-regulated over-expression of hsp22 has negative effects on stress resistance and life span in adult Drosophila melanogaster
Mech Ageing Dev
 , 
2004
, vol. 
125
 (pg. 
651
-
663
)
25.
Morrow
G
Samson
M
Michaud
S
Tanguay
RM
Overexpression of the small mitochondrial Hsp22 extends Drosophila life span and increases resistance to oxidative stress
FASEB J
 , 
2004
, vol. 
18
 (pg. 
598
-
599
)
26.
Morrow
G
Battistini
S
Zhang
P
Tanguay
RM
Decreased lifespan in the absence of expression of the mitochondrial small heat shock protein Hsp22 in Drosophila
J Biol Chem
 , 
2004
, vol. 
279
 (pg. 
43382
-
43385
)
27.
Wang
HD
Kazemi-Esfarjani
P
Benzer
S
Multiple-stress analysis for isolation of Drosophila longevity genes
Proc Natl Acad Sci U S A
 , 
2004
, vol. 
101
 (pg. 
12610
-
12615
)
28.
Landis
GN
Tower
J
Superoxide dismutase evolution and life span regulation
Mech Ageing Dev
 , 
2005
, vol. 
126
 (pg. 
365
-
379
)
29.
Lehtinen
MK
Yuan
Z
Boag
PR
, et al.  . 
A conserved MST-FOXO signaling pathway mediates oxidative-stress responses and extends life span
Cell
 , 
2006
, vol. 
125
 (pg. 
987
-
1001
)
30.
Lithgow
GJ
White
TM
Melov
S
Johnson
TE
Thermotolerance and extended life-span conferred by single-gene mutations and induced by thermal stress
Proc Natl Acad Sci U S A
 , 
1995
, vol. 
92
 (pg. 
7540
-
7544
)
31.
Rea
SL
Wu
D
Cypser
JR
Vaupel
JW
Johnson
TE
A stress-sensitive reporter predicts longevity in isogenic populations of Caenorhabditis elegans
Nat Genet
 , 
2005
, vol. 
37
 (pg. 
894
-
898
)
32.
Barolo
S
Carver
LA
Posakony
JW
GFP and beta-galactosidase transformation vectors for promoter/enhancer analysis in Drosophila
Biotechniques
 , 
2000
, vol. 
29
 pg. 
726
  
728, 730, 732
33.
Spradling
AC
Roberts
DB
P element-mediated transformation
Drosophila A Practical Approach
 , 
1986
Oxford, UK
IRL Press
(pg. 
175
-
197
)
34.
Robertson
HM
Preston
CR
Phillis
RW
Johnson-Schlitz
DM
Benz
WK
Engels
WR
A stable genomic source of P element transposase in Drosophila melanogaster
Genetics
 , 
1988
, vol. 
118
 (pg. 
461
-
470
)
35.
Lukacsovich
T
Asztalos
Z
Awano
W
, et al.  . 
Dual-tagging gene trap of novel genes in Drosophila melanogaster
Genetics
 , 
2001
, vol. 
157
 (pg. 
727
-
742
)
36.
Halfon
MS
Gisselbrecht
S
Lu
J
Estrada
B
Keshishian
H
Michelson
AM
New fluorescent protein reporters for use with the Drosophila Gal4 expression system and for vital detection of balancer chromosomes
Genesis
 , 
2002
, vol. 
34
 (pg. 
135
-
138
)
37.
Kurapati
R
Passananti
HB
Rose
MR
Tower
J
Increased hsp22 RNA levels in Drosophila lines genetically selected for increased longevity
J Gerontol A Biol Sci Med Sci
 , 
2000
, vol. 
55
 (pg. 
B552
-
B559
)
38.
Walker
GA
White
TM
McColl
G
, et al.  . 
Heat shock protein accumulation is upregulated in a long-lived mutant of Caenorhabditis elegans
J Gerontol A Biol Sci Med Sci
 , 
2001
, vol. 
56
 (pg. 
B281
-
B287
)
39.
Lemaitre
B
Hoffmann
J
The host defense of Drosophila melanogaster
Annu Rev Immunol
 , 
2007
, vol. 
25
 (pg. 
697
-
743
)
40.
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
, vol. 
6
 (pg. 
144
-
152
)
41.
Ganz
T
Iron homeostasis: fitting the puzzle pieces together
Cell Metab
 , 
2008
, vol. 
7
 (pg. 
288
-
290
)

Author notes

Decision Editor: Huber R. Warner, PhD