Sexual Deprivation, Emotion, and Longevity: Neuropeptidergic Regulation of Aging in Drosophila

While researchers often focus on the brain as a victim of aging via neurodegenerative diseases, recent work has demonstrated that the aging process is regulated by neural mechanisms. Thus, we asked which mechanisms and inputs might be important for the brain to regulate aging. We found that in male Drosophila melanogaster, the costs of reproduction on survival are mediated entirely through perception of the opposite sex, and that mating itself is actually beneficial. These effects are mediated through distinct neural circuits, with neuropeptide F (npf, an NPY homolog) required for the negative effects of pheromones and corazonin (crz, a GnRH homolog) driving the beneficial effects of mating. dFoxo, a common mediator of aging, regulates these effects on aging through an insulin-independent mechanism. Investigation of the dynamics of the effects of pheromones on mortality revealed two hypotheses: either population mortality rates reverse as a result of heterogeneity in individual probabilities of death, or the effects of pheromones on mortality rates are reversible in individuals. By combining in vivo and in silico approaches, we revealed that both explanations are correct, with individual reversibility dominating dynamics early in life, and heterogeneity becoming important in middle-age. Using a more global approach, we examined the effects of manipulating 78 distinct subsets of neurons on lifespan, and identified specific brain structures that are of prime importance for modulating aging. One of these structures is home to neurons expressing diuretic hormone 44 (Dh44, a CRH homolog). Dh44 and one of its receptors, Dh44R1, modulate lifespan, likely through insulin-like signaling pathways. Furthermore, this effect of Dh44 on lifespan is independent of diet, a fact obtained in part using the Fly Liquid-food Interaction Counter (FLIC), a novel assay developed to continuously measure feeding behavior in individual flies. The evolutionarily conserved neural circuits identified herein link aging to neural states consistent with primitive emotions in Drosophila, and these mechanisms deserve further exploration for their potential to explain connections between stress, emotions, and health in humans.PHDMol & Integrtv Physiology PhDUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/144128/1/harvanek_1.pd

Friedreich's Ataxia (GAA)n•(TTC)n Repeats Strongly Stimulate Mitotic Crossovers in Saccharomyces cerevisae

Expansions of trinucleotide GAA•TTC tracts are associated with the human disease Friedreich's ataxia, and long GAA•TTC tracts elevate genome instability in yeast. We show that tracts of (GAA)230•(TTC)230 stimulate mitotic crossovers in yeast about 10,000-fold relative to a “normal” DNA sequence; (GAA)n•(TTC)n tracts, however, do not significantly elevate meiotic recombination. Most of the mitotic crossovers are associated with a region of non-reciprocal transfer of information (gene conversion). The major class of recombination events stimulated by (GAA)n•(TTC)n tracts is a tract-associated double-strand break (DSB) that occurs in unreplicated chromosomes, likely in G1 of the cell cycle. These findings indicate that (GAA)n•(TTC)n tracts can be a potent source of loss of heterozygosity in yeast

FLIC: High-Throughput, Continuous Analysis of Feeding Behaviors in <i>Drosophila</i>

<div><p>We present a complete hardware and software system for collecting and quantifying continuous measures of feeding behaviors in the fruit fly, <i>Drosophila melanogaster</i>. The FLIC (<u>F</u>ly <u>L</u>iquid-Food <u>I</u>nteraction <u>C</u>ounter) detects analog electronic signals as brief as 50 µs that occur when a fly makes physical contact with liquid food. Signal characteristics effectively distinguish between different types of behaviors, such as feeding and tasting events. The FLIC system performs as well or better than popular methods for simple assays, and it provides an unprecedented opportunity to study novel components of feeding behavior, such as time-dependent changes in food preference and individual levels of motivation and hunger. Furthermore, FLIC experiments can persist indefinitely without disturbance, and we highlight this ability by establishing a detailed picture of circadian feeding behaviors in the fly. We believe that the FLIC system will work hand-in-hand with modern molecular techniques to facilitate mechanistic studies of feeding behaviors in <i>Drosophila</i> using modern, high-throughput technologies.</p></div

Comparison between traditional food choice assays and the FLIC system.

<p>(A) The analog signals from feeding (left) and tasting (right) behaviors have distinct characteristics. (B) When presented with identical food in both food wells, male and female flies do not exhibit a preference, which rules out systematic bias in the FLIC system (open symbol, male; closed symbol, female; pooled paired randomization test, P = 0.97). (C) Flies exhibited strong preference in favor of 10% sucrose over 100 µM denatonium when measured using both two-dye and FLIC assays (Box charts represent mean, standard error of mean, and 10–90% quantile whiskers). (D) Flies demonstrated strong preference toward 10% sucrose over 1% sucrose when measured using both the CAFE and FLIC assays (Box charts represent mean, standard error of mean, and 10–90% quantile whiskers). (E) Estimates of food consumption using the CAFE and FLIC assays. Longer starvation resulted in increased food consumption as well as total feeding time (linear regression, P<1×10⁻⁵ for both assays). Changes in food volume in the capillary tubes was undetectable when fully fed flies were used, and only FLIC data are presented for that treatment. *P≤0.05; **P≤0.01; ***P≤0.001.</p

New types of behavioral inference from the FLIC system.

<p>(A) Flies spent 10% of their time in behaviors we categorized as tasting two foods prior to making their first meal choice. Fraction of time is calculated based on “total time spent tasting/time until the first meal”. (B) A greater fraction of tasting events were directed toward the food the flies choose to consume (mean Tasting PI = 0.35). A Tasting PI = 1 implies a fly tasted a single food before ultimately consuming that food. A Tasting PI = −1 implies that a fly tasted a single food before ultimately consuming the opposite food. (C) While a cumulative preference index (left panel) is effective at portraying overall feeding tendencies, time-dependent preference indices (right panel) reveal subtle differences in behavioral choices as the experiment progresses. Flies exhibited a strong preference toward 10% sucrose in the first 30 min, which was attenuated in later time periods then returned to a strong preference (N = 34; the size of the symbol is proportional to the sample size contributed to calculate PI in a given period). (D) Flies with increased feeding motivation (through longer periods of starvation) experienced their first meal earlier than control flies. Flies starved for increasing periods (0 hr, 24 hr, or 48 hr) exhibited reduced latencies until their first feeding event. Latency curves were found to be significantly different via log-rank test. (E) Flies with increased hunger (through longer periods of starvation) exhibited meals that were of significantly longer duration than control flies (One-way ANOVA followed by post-hoc test using a Bonferroni correction). (F) Taste input plays a role in motivation by decreasing latency to the first meal. Flies with loss of function in the trehalose receptor, <i>ΔGr5a</i>, were significantly delayed in their first meal of a liquid trehalose food compared with control animals (log-rank test). **P≤0.01; ***P≤0.001</p

Illustration of the FLIC system.

<p>(A) Cartoon of the <i>Drosophila</i> Feeding Monitor (DFM) from the top- and side-view along with a flowchart of data collection and processing. Analog signals from all DFMs are collected by the Master Control Unit (MCU), which relays the information to the PC where the signals are visualized and recorded by the real-time monitoring software. (B) Representative signals from each of two feeding wells within a single feeding arena taken from a 90 min subset of a 24-hour feeding measurement. Close-up signal patterns representative of two distinct classes of feeding behavior events are presented as insets. (C) Histograms representing the distribution of durations for individual feeding behavior events (an event is a set of contiguous signals above baseline) over a 24 hr measurement period. Each plot represents values from a single fly, and distributions for three flies are presented. N represents the number of behavior events observed. (D) Histograms representing the size of the intervals between successive feeding behaviors over a 24 hr measurement period. Each plot represents values from a single fly, and distributions for the same three flies as in panel C are presented. (E) Among-fly variability in the average feeding duration and average time between feeding events. Each point represents the average value over a 24 hr period (N = 21). (F) Event-time distribution that represents the fraction of the population that has experienced at least one feeding at a given elapsed time from a randomized point between 12pm-2pm (N = 21). It took roughly 197 min for 50% of the population to feed at least once during this time of the day.</p

Greater stress and trauma mediate race-related differences in epigenetic age between Black and White young adults in a community sample

Black Americans suffer lower life expectancy and show signs of accelerated aging compared to other Americans. While previous studies observe these differences in children and populations with chronic illness, whether these pathologic processes exist or how these pathologic processes progress has yet to be explored prior to the onset of significant chronic illness, within a young adult population. Therefore, we investigated race-related differences in epigenetic age in a cross-sectional sample of young putatively healthy adults and assessed whether lifetime stress and/or trauma mediate those differences. Biological and psychological data were collected from self-reported healthy adult volunteers within the local New Haven area (399 volunteers, 19.8% Black, mean age: 29.28). Stress and trauma data was collected using the Cumulative Adversity Inventory (CAI) interview, which assessed specific types of stressors, including major life events, traumatic events, work, financial, relationship and chronic stressors cumulatively over time. GrimAge Acceleration (GAA), determined from whole blood collected from participants, measured epigenetic age. In order to understand the impact of stress and trauma on GAA, exploratory mediation analyses were then used. We found cumulative stressors across all types of events (mean difference of 6.9 p = 2.14e-4) and GAA (β = 2.29 years [1.57–3.01, p = 9.70e-10] for race, partial η2 = 0.091, model adjusted R2 = 0.242) were significantly greater in Black compared to White participants. Critically, CAI total score (proportion mediated: 0.185 [0.073–0.34, p = 6e-4]) significantly mediated the relationship between race and GAA. Further analysis attributed this difference to more traumatic events, particularly assaultive traumas and death of loved ones. Our results suggest that, prior to development of significant chronic disease, Black individuals have increased epigenetic age compared to White participants and that increased cumulative stress and traumatic events may contribute significantly to this epigenetic aging difference

The Cutting Edge of Epigenetic Clocks: In Search of Mechanisms Linking Aging and Mental Health

Individuals with psychiatric disorders are at increased risk of age-related diseases and early mortality. Recent studies demonstrate that this link between mental health and aging is reflected in epigenetic clocks, aging biomarkers based on DNA methylation. The reported relationships between epigenetic clocks and mental health are mostly correlational, and the mechanisms are poorly understood. Here, we review recent progress concerning the molecular and cellular processes underlying epigenetic clocks as well as novel technologies enabling further studies of the causes and consequences of epigenetic aging. We then review the current literature on how epigenetic clocks relate to specific aspects of mental health, such as stress, medications, substance use, health behaviors, and symptom clusters. We propose an integrated framework where mental health and epigenetic aging are each broken down into multiple distinct processes, which are then linked to each other, using stress and schizophrenia as examples. This framework incorporates the heterogeneity and complexity of both mental health conditions and aging, may help reconcile conflicting results, and provides a basis for further hypothesis-driven research in humans and model systems to investigate potentially causal mechanisms linking aging and mental health

Do developmental temperatures affect redox level and lifespan in C. elegans through upregulation of peroxiredoxin?

Lifespan in poikilothermic organisms, such as Caenorhabditis elegans, can be substantially increased simply by decreasing growth temperature. To gain insights into the mechanistic underpinnings of this effect, we investigated the effects of temperature in development and adulthood on C. elegans lifespan. We found that worms exposed to 25 °C during development and shifted to 15 °C in adulthood exhibited an even longer lifespan than animals constantly kept at 15 °C. Analysis of the in vivo redox status demonstrated that at 25 °C, C. elegans larvae have a more reduced redox state and higher Prdx-2 expression levels than animals raised at 15 °C. Worms lacking prdx-2 fail to show the additional lifespan extension upon shift from 25 °C to 15 °C and reveal a lifespan similar to prdx-2 worms always kept at 15 °C. These results suggest that transiently altering the in vivo redox state during development can have highly beneficial long-term consequences for organisms. Keywords: Aging, Temperature, C. elegans, Oxidants, Peroxiredoxi