Summary Both developmental nutrition and adult nutrition affect life‐history traits; however, little is known about whether the effect of developmental nutrition depends on the adult environment experienced. We used the fruit fly to determine whether life‐history traits, particularly life span and fecundity, are affected by developmental nutrition, and whether this depends on the extent to which the adult environment allows females to realize their full reproductive potential. We raised flies on three different developmental food levels containing increasing amounts of yeast and sugar: poor, control, and rich. We found that development on poor or rich larval food resulted in several life‐history phenotypes indicative of suboptimal conditions, including increased developmental time, and, for poor food, decreased adult weight. However, development on poor larval food actually increased adult virgin life span. In addition, we manipulated the reproductive potential of the adult environment by adding yeast or yeast and a male. This manipulation interacted with larval food to determine adult fecundity. Specifically, under two adult conditions, flies raised on poor larval food had higher reproduction at certain ages – when singly mated this occurred early in life and when continuously mated with yeast this occurred during midlife. We show that poor larval food is not necessarily detrimental to key adult life‐history traits, but does exert an adult environment‐dependent effect, especially by affecting virgin life span and altering adult patterns of reproductive investment. Our findings are relevant because (1) they may explain differences between published studies on nutritional effects on life‐history traits; (2) they indicate that optimal nutritional conditions are likely to be different for larvae and adults, potentially reflecting evolutionary history; and (3) they urge for the incorporation of developmental nutritional conditions into the central life‐history concept of resource acquisition and allocation.
Developmental diet is known to exert long-term effects on adult phenotypes in many animal species as well as disease risk in humans, purportedly mediated through long-term changes in gene expression. However, there are few studies linking developmental diet to adult gene expression. Here, we use a full-factorial design to address how three different larval and adult diets interact to affect gene expression in 1-day-old adult fruit flies ( Drosophila melanogaster ) of both sexes. We found that the largest contributor to transcriptional variation in young adult flies is larval, and not adult diet, particularly in females. We further characterized gene expression variation by applying weighted gene correlation network analysis (WGCNA) to identify modules of co-expressed genes. In adult female flies, the caloric content of the larval diet associated with two strongly negatively correlated modules, one of which was highly enriched for reproduction-related processes. This suggests that gene expression in young adult female flies is in large part related to investment into reproduction-related processes, and that the level of expression is affected by dietary conditions during development. In males, most modules had expression patterns independent of developmental or adult diet. However, the modules that did correlate with larval and/or adult dietary regimes related primarily to nutrient sensing and metabolic functions, and contained genes highly expressed in the gut and fat body. The gut and fat body are among the most important nutrient sensing tissues, and are also the only tissues known to avoid histolysis during pupation. This suggests that correlations between larval diet and gene expression in male flies may be mediated by the carry-over of these tissues into young adulthood. Our results show that developmental diet can have profound effects on gene expression in early life and warrant future research into how they correlate with actual fitness related traits in early adulthood.
Contact lens wearers may inadvertently expose their lenses during the lens insertion and removal process or while wearing their lenses to cosmetic products being used. This study investigated the impact of various cosmetics on the physical dimension and optical properties of three recently marketed monthly replacement silicone hydrogel contact lenses.In this in vitro study, three monthly replacement silicone hydrogel lens types including senofilcon C (ACUVUE VITA, Johnson & Johnson), samfilcon A (Bausch+Lomb ULTRA, Bausch+Lomb), and lotrafilcon B+EOBO (polyoxyethylene-polyoxybutylene) (AIR OPTIX plus HydraGlyde, ALCON), were individually coated with cosmetic products followed by a 1-hr soak in phosphate-buffered saline. Cosmetic products included; three hand creams (HC1: Glysomed; HC2: Vaseline Healthy Hand & Nail Conditioning; and HC3: Intense Relieve), three make-up removers (MR1: Lid-Care Towelettes; MR2: Gentle waterproof eye and Lip Makeup Remover; and MR3: Oil-Free Makeup Remover), and three mascaras (MA1: Great Lash-waterproof; MA2a: Wonder'Lash-waterproof, and MA3: Voluminous Original). The contact lens dimensions were determined for diameter, sagittal depth, and base curve, using the Chiltern (Optimec Limited), whereas lens power and optical quality were assessed using the Contest Plus II (Rotlex). Six replicates for each lens/cosmetic combination were used. The impact of cosmetics was tested between lenses and compared with uncoated control lenses.For lens diameter, makeup removers (MR2 & MR3) demonstrated the largest impact, with an increase of up to 0.26 mm (MR2) and 0.35 mm (MR3) for senofilcon C and samfilcon A, respectively (P<0.01 compared to baseline), whereas lotrafilcon B+EOBO showed a decrease of 0.01 mm (P<0.01 between lens types). For sagittal depth, mascara MA1 demonstrated the greatest impact, followed by makeup removers MR2 & MR3. All lenses showed increases in sagittal depth after MA1 exposure (0.16±0.06 mm in lotrafilcon B+EOBO, 0.24±0.22, and 0.26±0.09 mm in samfilcon A and senofilcon C, respectively; P<0.01 for all lenses compared with baseline). For base curve, the makeup removers (MR2 & MR3) caused increases for both senofilcon C (up to 0.36 mm) and samfilcon A (up to 0.35 mm), but lotrafilcon B+EOBO was unaffected. Lens power changes were generally minor (<0.25 D). However, senofilcon C showed a significant change of -1.18±0.65 D (more minus) after MA1 exposure (P<0.001). Image quality was most affected by mascaras, although given that all lens types were adversely affected to similar degrees, none of the lenses performed better or worse after mascara application (P>0.05). The parameters of the different lens types were not significantly affected by the hand creams.Makeup removers and mascaras changed the lens parameters to varying degrees, which may affect the fit and overall performance of the lens, whereas no such effect was noted with hand creams. Lotrafilcon B+EOBO was typically less affected compared with senofilcon C or samfilcon A.
chapter 1 8-ranging from the "live fast -die young" approach of mayflies and rock stars to the "slow-and-steady wins the race" approach of tortoises and Buddhist monks.Each strategy is a different solution to the problem of how best to leave behind the most offspring.For some species or individuals, it means investing considerably in building and maintaining a high-quality body in order to raise a few, high quality offspring.For others it means investing very little in a high-quality body, but a lot in very many, lower quality offspring.These different modes of living can be more precisely defined as life histories: the sequence of events related to survival and reproduction that occur from birth through death (Roff 2001; Stearns 1992).The traits that contribute the most to fitness, such as frequency and age at reproduction, size, and lifespan are termed life history traits (Roff 1992).Life history theory seeks to explain how the wide array of life history strategies observable in nature has evolved.Limited resources not only lead to a "struggle for survival" between individuals, but they also lead to a "struggle for investment" within an individual.The "struggle for investment" is conceptualised in the idea of trade-offs, a fundamental concept in life history theory.Because resources are limited, individuals cannot maximise all traits at once and thus, increased allocation of resources to one trait, such as reproduction, will by necessity lead to decreased allocation to another, such as lifespan (Stearns 1992).Acquisition-allocation theory seeks to understand how these allocation decisions are made in order to optimise an individuals fitness with a limited amount of resources (Sibley & Calow 1986), and also to explain the surprising lack of trade-offs observed in some instances (de Jong & van Noordwijk 1992; Roff & Fairbairn 2007; Van Noordwijk & de Jong 1986).More recent work has begun to characterise the genetic and physiological pathways underlying trade-offs (Braendle et al. 2011).For example, molecular genetic approaches have revealed that underlying signalling processes, rather than energy allocation per se may underpin the lifespan-reproduction tradeoff in the worm, C. elegans (Barnes & Partridge 2003).This new aspect of life history theory is only beginning to be explored, but argues that a mechanistic approach can offer a more complete understanding of life history evolution (Braendle et al. 2011).It is important to note that while generally, the limiting resource being referred to in the context of trade-offs is food (e.g.Agrawal et al. 2010), trade-offs can also result from the limitation of other resources such as space and time, from underlying physiological constraints, or from genes with antagonistic-pleiotropic effects (Hoffmann 2014; Stearns 1992; Zera & Harshman 2001). Plasticity, reaction norms, and developmentUltimately, life history traits are determined by the interaction of the genotype with the environment.One of the most important mechanisms whereby organisms can cope with environmental variation is via phenotypic plasticity
Article Figures and data Abstract eLife digest Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract In the mouse, the osteoblast-derived hormone Lipocalin-2 (LCN2) suppresses food intake and acts as a satiety signal. We show here that meal challenges increase serum LCN2 levels in persons with normal or overweight, but not in individuals with obesity. Postprandial LCN2 serum levels correlate inversely with hunger sensation in challenged subjects. We further show through brain PET scans of monkeys injected with radiolabeled recombinant human LCN2 (rh-LCN2) and autoradiography in baboon, macaque, and human brain sections, that LCN2 crosses the blood-brain barrier and localizes to the hypothalamus in primates. In addition, daily treatment of lean monkeys with rh-LCN2 decreases food intake by 21%, without overt side effects. These studies demonstrate the biology of LCN2 as a satiety factor and indicator and anorexigenic signal in primates. Failure to stimulate postprandial LCN2 in individuals with obesity may contribute to metabolic dysregulation, suggesting that LCN2 may be a novel target for obesity treatment. eLife digest Obesity has reached epidemic proportions worldwide and affects more than 40% of adults in the United States. People with obesity have a greater likelihood of developing type 2 diabetes, cardiovascular disease or chronic kidney disease. Changes in diet and exercise can be difficult to follow and result in minimal weight loss that is rarely sustained overtime. In fact, in people with obesity, weight loss can lower the metabolism leading to increased weight gain. New drugs may help some individuals achieve 5 to 10% weight loss but have side effects that prevent long-term use. Previous studies in mice show that a hormone called Lipocalin-2 (LCN2) suppresses appetite. It also reduces body weight and improves sugar metabolism in the animals. But whether this hormone has the same effects in humans or other primates is unclear. If it does, LCN2 might be a potential obesity treatment. Now, Petropoulou et al. show that LCN2 suppressed appetite in humans and monkeys. In human studies, LCN2 levels increased after a meal in individuals with normal weight or overweight, but not in individuals with obesity. Higher levels of LCN2 in a person's blood were also associated with a feeling of reduced hunger. Using brain scans, Petropoulou et al. showed that LCN2 crossed the blood-brain barrier in monkeys and bound to the hypothalamus, the brain center regulating appetite and energy balance. LCN2 also bound to human and monkey hypothalamus tissue in laboratory experiments. When injected into monkeys, the hormone suppressed food intake and lowered body weight without toxic effects in short-term studies. The experiments lay the initial groundwork for testing whether LCN2 might be a useful treatment for obesity. More studies in animals will help scientists understand how LCN2 works, which patients might benefit, how it would be given to patients and for how long. Clinical trials would also be needed to verify whether it is an effective and safe treatment for obesity. Introduction Obesity is a global epidemic that results in millions of deaths every year; a chronic disease associated with other serious and chronic conditions including type 2 diabetes, coronary artery disease, stroke, cancer, and depression amongst others (Heymsfield and Wadden, 2017). Obesity affects adults and children and is linked to seven of the top ten leading causes of death and disability in the U.S. (National Center for Health Statistics (US), 2016). There are limited effective medical treatment options for long-term weight loss mainly due to our limited understanding of energy homeostasis—the mechanism that sustains weight by matching energy intake to energy expenditure over time (Schwartz et al., 2017). In individuals with longstanding obesity, the body responds to long-term weight loss by a reduction in metabolic rate, favoring weight regain (Fothergill et al., 2016; Rosenbaum et al., 2010). Diet and exercise programs have high relapse rates and available pharmacotherapies have limited effectiveness, with safety concerns and poor tolerability (American College of Cardiology/American American College of Cardiology/American Heart Association Task Force on Practice Guidelines, Obesity Expert Panel, 2013, 2014; Daubresse and Alexander, 2015). Lipocalin-2 (LCN2) is an endogenous hormone found in mice and humans (Liu et al., 2018; Rucci et al., 2015), secreted by osteoblasts and which suppresses food intake in mice (Mosialou et al., 2017). Long-term LCN2 administration to lean and obese mice suppresses appetite and body weight gain without loss of effect over time, and improves whole body glucose metabolism while at the same time increasing energy expenditure. Therefore, LCN2 overcomes the inherent compensatory decrease in energy expenditure that develops following a sustained decrease in food intake (Mosialou et al., 2017). Moreover, LCN2 acts as a satiety signal that is upregulated after feeding in mice to limit food intake. Its anorexigenic mechanism of action relies on its ability to cross the blood-brain barrier (BBB) and activate the melanocortin four receptor (MC4R)-dependent pathway, one of the most potent currently known regulators of obesity (Mosialou et al., 2017). Heterozygous mutations in MC4R are the commonest cause of monogenic obesity, affecting approximately 0.1% of the population (Farooqi et al., 2003). Based on genetic, molecular, and biochemical studies in mice (Mosialou et al., 2017; Rached et al., 2010) we sought to determine whether the postprandial regulation and hypothalamic action of LCN2 is conserved in humans and non-human primates and whether the systemic administration of LCN2 in primates induces appetite suppression. Results Serum LCN2 levels are postprandially increased in individuals with normal and overweight but not in individuals with obesity or with severe obesity To assess the postprandial regulation of serum LCN2, we used data from four separate studies where healthy individuals with normal weight, overweight, obesity, and severe obesity were challenged with a meal after an overnight fast. In Study 1 with young healthy lean women (BMI: 21.8 ± 0.6 Kg/m²; Supplementary file 1A), analysis revealed a tendency for increase of circulating LCN2 levels with time (F7, 70=3.07, p=0.065; Figure 1A), although not significant. LCN2 serum concentration at baseline (t = 0 min) trended to differ from the one at t = 30 min (F1, 10=3.8, p=0.080), t = 45 min (F1, 10=4.6, p=0.058), t = 60 min (F1, 10=4.87, p=0.052), and t = 90 min (F1, 10=3.9, p=0.076), a similar magnitude of postprandial upregulation to what was previously reported (Paton et al., 2013). Interestingly, postprandial LCN2 serum levels (mean concentration at each timepoint) were robustly inversely correlated with hunger scores (mean hunger scores at each timepoint) of the challenged subjects (Spearman r = −0.98, p=0.0004) after the consumption of the liquid meal (Figure 1B). Serum LCN2 levels peaked at 45 min after meal ingestion, increasing by 16% (Supplementary file 1A, Figure 1—figure supplement 1, A). Figure 1 with 3 supplements see all Download asset Open asset Serum LCN2 levels are postprandially increased in individuals with normal weight and overweight but not in individuals with obesity or with severe obesity. (A–B) Study 1: (A) Serum LCN2 levels and hunger and (B) Spearman correlation between serum LCN2 levels and hunger in normal-weight women (n = 11). (C) Study 2: serum LCN2 levels in normal-weight women (n = 9). (D–L) Study 3: (D–E) serum LCN2 levels in (D) all subjects (n = 47) and (E) subcategories of the cohort classified according to their postprandial response in raising LCN2 (R [n = 25]; NR [n = 22]). (F) Spearman correlation between serum LCN2 levels and hunger in the responders of the mixed cohort. (G) Serum LCN2 levels, (H) Spearman correlation between serum LCN2 levels and hunger and (I) BMI and waist circumference in female R (n = 15) and NR (n = 13) individuals. (J) Serum LCN2 levels, (K) Spearman correlation between serum LCN2 levels and hunger and (L) BMI and waist circumference in male R (n = 10) and NR (n = 9) individuals. (M–O) Study 4: (M) Fold change in serum LCN2 levels in female and male individuals with obesity, before (pre) and after (post) gastric bypass (n = 12). The asterisk denotes the difference before and after surgery at the indicated timepoint. (N–O) Spearman correlation between serum LCN2 levels and hunger in individuals with severe obesity (N) before and (O) after bariatric surgery. Values represent mean ± SEM. * indicates p<0.05, ‡ indicates p<0.06, and † indicates p<0.1 of each timepoint versus baseline, unless otherwise stated. 'Serum LCN2' represents log-transformed postprandial levels and 'hunger' represents hunger scores BMI = basic metabolic Index, LCN2 = Lipocalin-2, R = responders (elevated LCN2 levels in multiple timepoints after the meal), NR = non-responders (reduced LCN2 levels after the meal), RYGB = Roux en-Y Gastric Bypass. Figure 1—source data 1 Serum LCN2 levels are postprandially increased in individuals with normal weight and overweight but not in individuals with obesity or with severe obesity. https://cdn.elifesciences.org/articles/58949/elife-58949-fig1-data1-v1.xlsx Download elife-58949-fig1-data1-v1.xlsx Similarly, postprandial circulating LCN2 levels were significantly altered with time (F2, 16=27.87, p=0.002) in a separate, second study of young healthy lean women (BMI: 20.8 ± 0.5 Kg/m²; Supplementary file 1A). Specifically, serum LCN2 concentration at t = 60 min (F1, 8=59.64, p=0.002) and t = 105 min (F1, 8=15.36, p=0.009; Figure 1C) were significantly increased from baseline. Here serum LCN2 levels peaked at 60 min increasing by 54% (Supplementary file 1A, Figure 1—figure supplement 1, G). The third study included 47 subjects, 28 women and 19 men, with overweight and/or obesity (BMI: 28.7 ± 0.5 Kg/m²). The whole cohort consisted of 30 subjects (18 women and 12 men) with overweight (BMI = 26.4 ± 0.3 Kg/m²) and 17 subjects (10 women and 7 men) with obesity (BMI = 32.7 ± 0.4 Kg/m²). Contrary to lean groups, LCN2 significantly decreased after the meal challenge (F5, 215=2.61, p=0.026; Figure 1D). Interestingly, based on their postprandial LCN2 response, this initial cohort could be divided into two subgroups (Figure 1E). The first group (n = 25) included responders (R), that is, subjects that had a 'positive' postprandial LCN2 response with elevated LCN2 levels in multiple timepoints after the meal. The second group (n = 22) consisted of non-responders (NR), that is, subjects that had a 'negative' postprandial LCN2 response with decreased LCN2 levels after the meal challenge. Responders showed a trend, though not statistically significant, toward a 12% increase in serum LCN2 levels 60 min after meal consumption (F1, 21=3, 24, p=0.086; Figure 1E; Supplementary file 1B; Figure 1—figure supplement 2A). The inverse correlation between postprandial LCN2 serum levels and hunger scores was attenuated compared to that of Study 1 (Spearman r = −0.66, p=0.33; Figure 1F). On the other hand, non-responders showed decreased LCN2 levels at all timepoints examined, reaching a nadir 60 min after the meal, with a 19% reduction (F1,21=37.08, p<0.0001; Supplementary file 1B). Non-responders trended to have a significantly larger waist circumference (Supplementary file 1B). Higher values for BMI, body fat, diastolic blood pressure, and fasting serum glucose and LCN2 levels were also observed in the non-responders but did not reach statistical significance (Supplementary file 1B). When the 47-subject mixed cohort was analyzed by sex, subjects could again be divided into responders and non-responders, based on their postprandial LCN2 response. Women (Figure 1G; Figure 1—figure supplement 2, B) and men (Figure 1J; Figure 1—figure supplement 2, C) responders showed a trend, though not statistically significant, toward a 10% and 15% increase in serum LCN2 levels 60 min after meal consumption, respectively (Supplementary file 1B). The inverse correlation between postprandial LCN2 serum levels and hunger sensation found in women with normal weight (in Study 1), was not present in these overweight/obese groups of women (Figure 1H; Figure 1—figure supplement 2, E) or men (Figure 1K; Figure 1—figure supplement 2, F). On the other hand, non-responders showed a significant LCN2 decrease postprandially at all timepoints examined, reaching a nadir at 60 min for women (F1,12=36.9, p<0.0001; Figure 1G) and at 90 min for men (F1,8=25.21, p=0.001; Figure 1J). Whereas women NRs had significantly higher waist circumference (Figure 1I) and showed a trend toward higher BMI, body fat, serum glucose, diastolic blood pressure (Supplementary file 1B), men NRs did not show any major differences in BMI, waist circumference (Figure 1L) or any other parameters (Supplementary file 1B). The Study 4 included individuals with severe obesity, studied before and after Roux-en-Y gastric bypass surgery. The initial BMI of 47.4 ± 1.9 kg/m2 was reduced to 29.6 ± 1.8 kg/m2 one year after the surgery (Stano et al., 2017). Baseline fasting LCN2 levels were marginally decreased after surgery (Supplementary file 1C, Figure 1—figure supplement 3A,C). Postprandial levels of serum LCN2 were rather decreased before surgery (F10, 109=1.4, p=0.253) and trended to be significantly increased after surgery (F10, 107=1.97, p=0.079), suggesting re-sensitization of these subjects after normalization of BMI. Similar to the overweight and obese non-responders of the previous study, pre-surgery postprandial circulating levels of LCN2 showed a 19% decrease from baseline at 90 min (F1,11=6.54, p=0.026) after the ingestion of the liquid meal (Supplementary file 1C). Interestingly, post-surgery, postprandial concentrations of LCN2 changed to the opposite direction showing a 42% increase at 15 min (F1, 10=7.54, p=0.023) and a trend, though not statistically significant, toward 59% increase from baseline at 90 min (F1, 11=4.32, p=0.065) after ingestion of the meal (Supplementary file 1C). Furthermore, Roux-en-Y gastric bypass significantly affected (F1, 220=5.89, p=0.024) the observed difference in LCN2 levels at 90 min before and after surgery (Figure 1M). Of note, while postprandial LCN2 concentration did not correlate with hunger score before surgery (Spearman r = −0.18, p=0.64; Figure 1N; Figure 1—figure supplement 3B), there was an association, albeit non-significant after surgery (Spearman r = −0.64, p=0.096; Figure 1O; Figure 1—figure supplement 3D). In order to place in context the regulation of postprandial LCN2 serum levels and its association with hunger, to those of other feeding-regulating hormones, we measured glucagon-like peptide 1 (GLP-1) and insulin circulating concentrations. In the normal-weighted cohorts (1st and 2nd Study) LCN2 showed a postprandial response similar in magnitude to that of GLP-1 (Figure 2A–D and Figure 1—figure supplement 1A–B, G–H). In both studies circulating insulin showed higher postprandial upregulation than LCN2 (Figure 2A,C and Figure 1—figure supplement 1C,I). However, the total response of LCN2 was significantly lower than GLP-1 (p=0.035; Figure 2B and Figure 1—figure supplement 1A–B) in Study 1, but not in study 2 (p=0.385; Figure 2D and Figure 1—figure supplement 1G–H). In study 1, LCN2 was the postprandial protein with the highest inverse correlation with hunger score (Figure 1—figure supplement 1D–F); GLP-1 was also inversely correlated with hunger, yet less strongly (Figure 1—figure supplement 1E). We did not find any correlation between insulin levels and hunger in this cohort (Figure 1—figure supplement 1F). For this reason, we more closely compared total responses of LCN2 and GLP-1. Figure 2 Download asset Open asset Similar postprandial regulation of serum LCN2 and GLP-1 levels in subjects with normal weight but not in subjects with overweight or obesity. (A–B) Study 1: (A) serum LCN2, GLP-1, and insulin levels of n = 11 normal-weight women and (B) area under the curve comparison for LCN2 and GLP-1. (C–D) Study 2: (C) serum LCN2, GLP-1, and insulin levels of n = 9 normal-weight women and (D) area under the curve comparison for LCN2 and GLP-1. (E–J) Study 3: (E) serum LCN2, GLP-1, and insulin levels of n = 47 overweight and obese subjects (whole, sex-mixed cohort), (F) of n = 28 overweight and obese women and (G) of n = 19 overweight and obese men and subcategorization of the cohort to responders and non-responders. Continuous lines were used for the whole, sex-mixed cohort (-A), the dashed line for the responders (-R) and the dash-and-dots line for the non-responders (-NR). Symbols mark the significant differences between each timepoint and baseline. (H) Area under the curve comparison for LCN2 and GLP-1 of the sex-mixed cohort, (I) women and (J) men. (K–M) Study 4: serum LCN2, GLP-1, and insulin levels of n = 12 obese subjects before/pre and (L) after/post gastric bypass. (M) Area under the curve comparison for LCN2 and GLP-1 pre- and post-gastric bypass surgery. Values represent mean ± SEM. * indicates p<0.05, ‡ indicates p<0.06 and † indicates p<0.1 of each timepoint versus baseline. 'Serum LCN2, GLP-1 and insulin' represent log-transformed postprandial levels. The units for log LCN2 and GLP-1 concentrations are in ng/mL, whereas for insulin in mIU/mL. LCN2 = Lipocalin-2, GLP-1 = Glucagon like peptide 1, RYGB = Roux en-Y Gastric Bypass. Figure 2—source data 1 Similar postprandial regulation of serum LCN2 and GLP-1 levels in subjects with normal weight but not in subjects with overweight or obesity. https://cdn.elifesciences.org/articles/58949/elife-58949-fig2-data1-v1.xlsx Download elife-58949-fig2-data1-v1.xlsx In study 3, the total GLP-1 response was significantly higher than LCN2 (p<0.0001). For consistency purposes, we also analyzed GLP-1 and serum levels in responders and non-responders, although segregation in these two groups was based on LCN2 serum levels. The response of LCN2 was significantly different between responders and non-responders (p=0.014; Figure 2H) and this was more pronounced in females (Figure 2I), than males (Figure 2J). GLP-1 or insulin response between responders and non-responders was not in the opposite direction, as in the case of LCN2 (Figure 2E-G; Figure 1—figure supplement 2, G–I,M–O). Within the responders, an inverse correlation with hunger was present for insulin (Figure 1—figure supplement 2, P–R) but not for LCN2 (Figure 1—figure supplement 2, D–F) or GLP-1 (Figure 1—figure supplement 2, J–L,). In study 4, the improvement of body weight and BMI after gastric bypass surgery was accompanied by a large increase in postprandial GLP-1 and insulin concentrations and to a lesser extent in LCN2 concentration (Figure 2K-L). GLP-1 response was higher than that of LCN2, both before (pre) and after (post) bariatric surgery (Figure 2K-L). While the GLP-1 response was significantly increased after the surgery, LCN2 only showed a tendency for increase (Figure 2M). GLP-1 and insulin showed a strong inverse correlation with hunger both before (Figure 1—figure supplement 3, F,J, respectively) and after the bariatric surgery (Figure 1—figure supplement 3, H,L, respectively). In contrast to LCN2, which did not correlate with hunger scores before surgery (Figure 1—figure supplement 3, B), tended to inversely correlate with it after the surgery (Figure 1—figure supplement 3, D), although not significantly. Combined, our studies in humans show a postprandial increase in circulating LCN2 levels in humans with normal weight, which notably correlates with a drop in hunger sensation in the same individuals. Furthermore, subjects with overweight or obesity lose postprandial regulation of LCN2 and this may be a new mechanism of resistance that contributes to obesity. LCN2 crosses the blood-brain barrier of vervets and binds to the hypothalamus of human, baboon, and rhesus macaque brain sections Next, we examined whether the mechanism of action of LCN2 is conserved in primates. As a first approach we evaluated whether [124I] rh-LCN2 crosses the blood-brain barrier in non-human primates. Combined analysis of MRI and PET representative images of vervet monkey brain demonstrated an initial peak of activity throughout the brain during the first 30 s after the end of intravenous administration of [124I] rh-LCN2 that is characteristic of BBB permeability. The sagittal, coronal, and axial MRI T1-weighted template images show a volume of interest (VOI) in the anatomical area of the hypothalamus where there is an indication of tracer binding although it may partially be spillover from an adjacent area outside the brain that also shows substantial tracer uptake (Figure 3A-I, Figure 3—figure supplement 1A–M). Figure 3 with 1 supplement see all Download asset Open asset LCN2 crosses the blood-brain barrier of vervets. (A, D, G) MRI, (B, E, H) PET/MRI and (C, F, I) PET representative images of monkey brain 30 s after infusion of [124I]-rh-LCN2. (A, B, C) Sagittal, (D, E, F) coronal, and (G, H, I) axial MRI T1-weighted template images (Invia19) demonstrate the volume of interest (VOI) and the anatomy of the hypothalamus (outlined with white and black line). (J–M) Time-activity curves (TACs) for the (J) left thalamus and (K) hypothalamus and (L) right thalamus, and (M) hypothalamus in a chase and a no-chase experiment in the same animal; TACs are reported in standard uptake value (SUV) units. Figure 3—source data 1 LCN2 crosses the blood-brain barrier of vervet monkeys. https://cdn.elifesciences.org/articles/58949/elife-58949-fig3-data1-v1.xlsx Download elife-58949-fig3-data1-v1.xlsx PET acquisition was repeated using a chase/blocking paradigm to determine whether there is specific binding of [124I] rh-LCN2 in the hypothalamus. The results from the chase experiment—standard uptake values at every timepoint—were compared to those of the no-chase experiment, by using the same procedure, software and atlas. Infusion of the MC4R receptor ligand, α-MSH, 15 min after [124I] rh-LCN2 did not seem to affect the tracer uptake in the thalamic region (Figure 3J and L), whereas it did reduce uptake compared with the no-chase condition in the hypothalamus (Figure 3K and M). We observed a 6.3% and 5.7% difference in the standard uptake value (SUV) in the left and right thalamus respectively, and a 49.8% and 51.2% reduction in the left and right hypothalamus. These results indicate that [124I] rh-LCN2 penetrates the BBB and shows specific binding defined by displacement with α-MSH in the hypothalamus but not in the thalamus. To further prove that LCN2 can bind to the hypothalamic feeding center of primates and to also exclude the possibility, inherent to PET studies, that a spillover signal from outside the brain may confound the findings, we examined LCN2 binding to brain sections where no such potential confounder exists. Rhesus macaque, baboon, and human brain sections containing the hypothalamus were incubated with either [125I] rh-LCN2 alone or in the presence of excess unlabeled LCN2 or α-MSH to assess the specificity of binding. [125I] rh-LCN2 binding was observed in the hypothalamic area of the baboon (Figure 4A; Figure 4—figure supplement 1B,F) and the rhesus macaque (Figure 4—figure supplement 1, C–D). Figure 4 with 1 supplement see all Download asset Open asset LCN2 binds to the hypothalamus of human, baboon, and rhesus macaque brain sections. (A–B) Autoradiographic images showing (A) [125I] rh-LCN2 binding and (B) blocking of [125I] rh-LCN2 binding with not radiolabeled rh-LCN2 on the baboon hypothalamus; the hypothalamic area is outlined with a black line. (C–E) Autoradiographic images showing (C) [125I] rh-LCN2 binding, (D) blocking of [125I] rh-LCN2 binding with α-MSH, and (E) blocking of [125I] rh-LCN2 binding with not radiolabeled rh-LCN2 on the human hypothalamus. (F–G) Binding of biotinylated LCN2 to the hypothalamic area (outlined in A, B from baboon brain sections) in the (F) absence or (G) presence of hundred-fold excess of non-biotinylated LCN2 and (I) quantitation of LCN2-positive cells in both conditions (as percent of total cells in each field of view; n = 1 brain section and n = 4 fields of view for (F) and n = 2 for (G)). Bar graphs were obtained from a single brain section and therefore depict qualitative representations of binding. (H) Binding of biotinylated LCN2 to the hypothalamic area (outlined in C-E) from the human brain. (J) Quantification of specific [125I] rh-LCN2 binding to human brain sections (n = 3). Values are mean ± standard deviation of the mean. DM = dorsomedial, PVN = paraventricular nucleus of the hypothalamus, VM = ventromedial, VL = ventrolateral nucleus of the hypothalamus. Figure 4—source data 1 LCN2 binds to the hypothalamus of primates. https://cdn.elifesciences.org/articles/58949/elife-58949-fig4-data1-v1.xlsx Download elife-58949-fig4-data1-v1.xlsx In the baboon, the specificity of binding was confirmed by the use of unlabeled LCN2 which blocked part of the [125I] rh-LCN2 binding (Figure 4B). Specific binding was observed in the paraventricular nucleus of the hypothalamus (PVN) and both the dorsomedial (DM) and ventrolateral (VL) nuclei of the human hypothalamus, all areas where MC4R is expressed (Figure 4C, and Figure 4—figure supplement 1, A). Unlabeled LCN2 blocked part of the binding of labeled LCN2 (Figure 4E; Figure 4—figure supplement 1, E), indicating specific binding. Similarly, unlabeled a-MSH also blocked some LCN2 binding to the hypothalamus, indicating that LCN2 binds to MC4R (Figure 4D; Figure 4—figure supplement 1, E). That a-MSH blocked less [125I] rh-LCN2 binding than non-radiolabeled LCN2 may suggest that, at least in primates [125I] rh-LCN2 has a higher binding affinity for MC4R than α-MSH. To enhance the rigor of the autoradiography experiments, we also examined LCN2 binding using immunofluorescence in baboon (Figure 4F, G) and human brain sections (Figure 4H) containing the hypothalamus. Binding was again shown in both human and baboon brain sections and quantified as the average of LCN2-positive cells (21.3 ± 1.3% and 17.6 ± 1.8%, respectively) and it was specific since it was competed by non-biotinylated LCN2 (Figure 4G, I). The reduction in binding was approximately 75%. If the concentration of the blocking agent is insufficient then the block may be incomplete and explain why 25% nonspecific or non-displaceable binding is observed even when the tracer and blocking drugs are almost the same. It is also possible that a slightest difference in structure may mean differences in nonspecific binding or off-target high-affinity binding (Hamill et al., 2005). Of note, bar graphs were obtained from a single brain section and therefore depict qualitative representations of binding. Overall, we observed a consistent and comparable degree of binding in the hypothalamus, among the three species examined (Figure 4—figure supplement 1A–F), which indicates that the PET findings are evidence of specific binding in the non-human primate hypothalamus and supports the premise of a common interspecies target of action for LCN2. rh-LCN2 treatment suppresses food intake and body weight in vervets within five days of treatment Having established that rh-LCN2 is able to cross the BBB of vervets and localize to the hypothalamus, we then sought to examine whether a daily treatment of lean monkeys with intravenously administered rh-LCN2 would lead to appetite suppression. As described in Materials and methods, this was a cross-over study with two treatment weeks and one washout period in between (Figure 5A). The LCN2 dose was extrapolated from our studies in mice (Mosialou et al., 2017). In the mouse hypothalamus, the amount of naturally occurring LCN2 is 28 pg/mg and in the adult mouse and human serum, it is on average 100–150 ng/mL. In mice, the administration of LCN2 by intraperitoneal injection of 150 ng/g daily crosses the blood-brain barrier and suppresses appetite. Using interspecies conversion per m2, we calculated the monkey dose to be 0.0375 mg/kg. This dose is equivalent to the amount used to treat mice and it is calculated based on body surface area; it takes into account the interspecies variation in several physiological parameters including oxygen utilization, caloric expenditure, basal metabolism, and blood volume (Reagan-Shaw et al., 2008). Figure 5 with 1 supplement see all Download asset Open asset Rh-LCN2 administration suppresses food intake in vervets within 5 days of treatment. (A) Timeline in weeks showing the design and major events of the non-human primate study. (B) Change in food intake of saline- and LCN2-treated vervets during the first week of treatment (n = 3 monkeys/treatment). (C) Change in food intake of saline- and LCN2-treated vervets during the baseline, the first week of treatment, and the subsequent washout period (n = 3 monkeys/treatment). (D–E) Change in food intake of saline- and LCN2-treated vervets during (D) the second week of treatment (n = 3 monkeys/treatment) and (E) when treatment weeks were combined and values were averaged (n = 6 monkeys/treatment). (F) Circulating levels of monkey and human LCN2 in the treated monkeys. Two different ELISA assays were used; one for human and one for monkey LCN2. Each ELISA has selective reactivity for the designated species. In G, gray bars indicate serum levels of monkey whereas red bars represent human LCN2 following its administration. Values represent mean ± SEM. * indicates p<0.05 and † indicates p<
Long-term effects of developmental diet on adult life history traits and health have been identified across a range of organisms, including humans. However, there has been considerable debate about the adaptive significance of such effects and the mechanisms responsible. In particular, we still lack insight into whether and how much such effects depend on the adult environment (as has been hypothesised to be the case in humans), and if and how such effects manifest as long term effects on gene expression, a proposed mechanism for the long-term effects. The aim of this thesis was to use the fruit fly, Drosophila melanogaster, as a model to gain insight into the effects of developmental diet on adult phenotypes and gene expression, and if and how this effect is also contingent on the actual adult environment experienced. I addressed this question from two angles by assessing the effects of developmental diet both within a single generation (plasticity) and when experienced across many generations (adaptation). Chapters 2, 3 and 4 address the plastic effects of developmental diet on phenotypes and gene expression across adult diets and across the lifespan, while Chapter 5 uses experimental evolution to address how flies adapt to differing larval diets over many generations, and how this interacts with classical selection for increased age-at-reproduction. Throughout the thesis I used the same three diets (poor, control, and rich) which differ 10 fold in the amount of sugar and yeast they contain and thus represent drastically different nutritional environments. Chapter 2 begins by determining the general effects of the three diets used throughout this thesis on both developmental and adult traits. It addresses the fundamental question of whether variation in developmental diet affects developmental and adult life history traits, with a particular emphasis on whether the effect of developmental diet depends on the reproductive potential of the adult environment. I found that both the rich and especially the poor developmental diet lead to what would classically be considered negative effects on developmental traits relative to the control - both slowing development and decreasing adult size in young adulthood, however, their effects on adult traits were distinct: the poor larval diet lead to increased virgin lifespan and increased female fecundity at certain ages and in certain adult reproductive environments relative to the control, while the rich larval diet had the opposite effect. This suggests that while over- and under-feeding share certain similarities with respect to their effects on traits in early life, their long-term effects differ. It also indicates differing nutritional optima between the developmental and adult stage in flies, as the poor diet is known to drastically decrease both lifespan and fecundity when experienced during adulthood, but is shown here to be largely beneficial for these traits when experienced in development. In addition, we found that the adult reproductive environment was considerably more important for determining traits than the developmental environment, thus, while long-term effects of developmental diet do exist, they are marginal when related to the plastic response effected in adulthood - a recurring theme in this thesis. In Chapter 3 the focus shifts from the effect of developmental diet on life history traits to its effect on the adult transcriptome. It has frequently been proposed that long-term effects of developmental diet on adult phenotypes are mediated by changes in gene expression. Thus, in this chapter I addressed the scope for such effects in fruit flies, by determining the relative effect of developmental versus adult diet on gene expression in very young adult flies (one-day old) in both sexes. I used a full factorial design combining three larval and three adult diets (9 treatments total). I found that the largest contributor to transcriptional variation in one day old flies is larval, not adult diet, especially in females. Furthermore, the global effect of increasing caloric content of the larval diet on gene expression was not linear, but rather followed the same pattern as that observed for developmental phenotypes in Chapter 2 (i.e. rich-raised flies were intermediate between poor and control) suggesting that calories per se do not drive global patterns of gene expression variation. Next, using Weighted Gene Correlation Networks Analysis (WGCNA) I identified modules of co-expressed genes whose expression was affected by larval or adult dietary conditions. In females, larval diet modulated the relative expression levels of reproduction versus non-reproduction related genes, while in males a large portion of the transcriptome was unaffected by dietary conditions, suggesting a lesser role for both larval and adult diet in affecting gene expression. The modules affected by diet in males related primarily to nutrient sensing and metabolism and showed no evidence of the reproduction and cell-cycle related processes identified in females, however, their expression in external tissue specific data sets suggested a role for the gut and fat body in mediating the effects of diet in males, potentially through the carry over of the larval versions of these tissues into adulthood. Overall, these results suggested that there is scope for long-term effects of developmental diet on gene expression, which is necessary for all hypothesised mechanisms that link developmental conditions to late-life health and disease. Chapter 4 combines phenotypic and transcriptomic approaches to look at the longer term effects of developmental diet in adulthood. Using the same full factorial approach applied in Chapter 3 , I assessed virgin and mated lifespan and fecundity as well as gene expression at middle and old age. I found that for the most part larval and adult diet exerted independent effects on the phenotype and on gene expression, and thus there was no evidence for Predictive Adaptive Responses (described in Chapter 1 ) operating in Drosophila melanogaster. Rather, the responses followed the silver spoon hypothesis which predicts that the effect of developmental conditions will be similar across adult conditions. Furthermore, in contrast to the beginning of life ( Chapter 3 ), adult diet explained considerably more variation in gene expression and phenotypes than larval diet, showing that flies retain extensive plasticity into adulthood, and suggesting that the long-term effects of developmental diet likely reflect the inability or lack of incentive to erase such effects, rather than an adaptive response. I did identify some genes that retain a legacy of developmental diet in their expression into middle and old-age. Many of these genes show no linear correlation with the observed phenotypic responses, however, in both sexes, I identified a cluster of genes whose expression was negatively correlated with the observed lifespan differences and that were enriched with terms related to transcription and translation, particularly with respect to ribosomes. Given several recent studies which show that the down-regulation of ribosomes and other aspects of transcriptional and translational machinery increases lifespan these genes provide promising candidates for mediating the long-term effects of larval diet on lifespan. As these processes are highly conserved across the tree of life our results may be relevant for other species as well, including for humans. In Chapter 5 , I address the evolutionary, rather than the plastic response to developmental diet by evolving flies on the three different larval diets in combination with selection for early or late age-at-reproduction in a full factorial design. This approach addresses how life histories evolve under different levels of larval acquisition, as well as how individuals cope with potentially competing selection pressures experienced at two different life stages. I found that the two life stages do not act independently but rather interact to determine both developmental time and lifespan. Across all evolutionary developmental diets, selection for later age-at-reproduction increased lifespan, however, the magnitude of the response was dependent on the sex, the evolutionary diet, and the experimental assay conditions. Developmental time from egg-to-adult also showed a similar dependency on both evolutionary diet levels and selection on age-at-reproduction. Given that multiple selection pressures are likely the norm rather than the exception in nature, this finding argues that trade-offs should be considered not only between traits within an organism, but also between adaptive responses to differing selection pressures. Furthermore, because variation in available nutrition is so frequent in natural environments, we argue that this can play a large role in shaping the evolution and diversity of life histories in nature. In the discussion in Chapter 6 I synthesise the findings across the experimental chapters, and address how they relate to each other. I also discuss some more general points that emerged, such as the potential importance of allometry or tissue specific effects in mediating effects of larval diet, and the difficulty of linking life history phenotypes to variation in gene expression. Finally, I point out future directions suggested by this thesis, as well as the potential insights that can be gained from this work in the context of theories linking developmental conditions to late life health in humans.
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