Measuring the quantitative relationship between organismal gene expression and lifespan in Caenorhabditis elegans

El envejecimiento implica un aumento de la fragilidad en función del tiempo que resulta en la aceleración de la mortalidad. Para comprender el papel temporal de varias proteínas en el envejecimiento, utilizamos el sistema de Degradación Inducible por Auxina (DIA) para estudiar los genes que acortan o prolongan la vida útil. Este sistema permite una forma inducible, rápida y reversible de controlar la expresión de proteínas. Usando cepas transgénicas de DIA, demostramos que la vida útil de estos gusanos se puede modular de manera dependiente de la dosis. Para identificar las dianas que causan la alteración de la vida útil, medimos el efecto de la degradación controlada de proteínas en el transcriptoma. Esto nos permitió medir los acoplamientos cuantitativos entre los cambios en la expresión génica y la vida útil para identificar los efectores de diferentes intervenciones que alteran la vida útil y que, al fin y al cabo, influyen en el envejecimiento.Ageing involves a time-dependent increase in fragility that results in the acceleration of mortality. To understand the temporal role of different proteins in ageing, we used the Auxin Inducible Degradation (AID) system to study genes that either shorten or extend lifespan. This system enables an inducible, rapid and reversible way of controlling protein expression. Using transgenic AID strains, we showed that lifespan of these worms can be modulated in a dosage-dependent manner. To identify targets causing alteration of lifespan, we measured the effect of controlled protein degradation on the transcriptome. This allowed us to measure quantitative couplings between changes in gene expression and lifespan to identify effectors of different lifespan–altering interventions that ultimately influence ageing.Programa de Doctorat en Biomedicin

A hierarchical process model links behavioral aging and lifespan in C. elegans

Aging involves a transition from youthful vigor to geriatric infirmity and death. Individuals who remain vigorous longer tend to live longer, and within isogenic populations of C. elegans the timing of age-associated vigorous movement cessation (VMC) is highly correlated with lifespan. Yet, many mutations and interventions in aging alter the proportion of lifespan spent moving vigorously, appearing to "uncouple" youthful vigor from lifespan. To clarify the relationship between vigorous movement cessation, death, and the physical declines that determine their timing, we developed a new version of the imaging platform called "The Lifespan Machine". This technology allows us to compare behavioral aging and lifespan at an unprecedented scale. We find that behavioral aging involves a time-dependent increase in the risk of VMC, reminiscent of the risk of death. Furthermore, we find that VMC times are inversely correlated with remaining lifespan across a wide range of genotypes and environmental conditions. Measuring and modelling a variety of lifespan-altering interventions including a new RNA-polymerase II auxin-inducible degron system, we find that vigorous movement and lifespan are best described as emerging from the interplay between at least two distinct physical declines whose rates co-vary between individuals. In this way, we highlight a crucial limitation of predictors of lifespan like VMC-in organisms experiencing multiple, distinct, age-associated physical declines, correlations between mid-life biomarkers and late-life outcomes can arise from the contextual influence of confounding factors rather than a reporting by the biomarker of a robustly predictive biological age.This project was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 852201), the Spanish Ministry of Economy, Industry and Competitiveness (MEIC) to the EMBL partnership, the Centro de Excelencia Severo Ochoa (CEX2020-001049-S, MCIN/AEI /10.13039/501100011033), the CERCA Programme/Generalitat de Catalunya, the MEIC Excelencia award BFU2017-88615-P, and an award from the Glenn Foundation for Medical Research to NS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Lifespan Machine Technology Update.

A description of the new approaches to image analysis, including detection of death-associated contraction and expansion and partitioning of lifespan into distinct behavioral and morphological stages. (PDF)</p

A hierarchical model of vigorous movement and lifespan.

a. In a simple, null model, the correlation between vigorous movement cessation (VMC) and death times arises because the two events share physiologic determinants (red box) such that VMC and death represent sequential manifestations of a single underlying aging process (red line in the graph). b. However, our data and modelling suggest that VMC and death times are instead determined by distinct sets of physiologic determinants (red and blue boxes) with each set subject to a distinct aging process (red and blue lines in the graph). In this case, a hierarchical organization among processes allows interventions to act directly on each process, or indirectly through an influence on shared upstream factors (green box).</p

An RNA Polymerase II dosage series.

a. On the second day of adulthood, animals living on HT115 at 25°C were transferred from empty vector to rpb-2 RNAi and the Kaplan-Meier survival curve was estimated. b. rpb-2(+);peft-3::TIR1 populations were exposed to either 0 and 8 mM α-Naphthaleneacetic acid (NA) starting on day 2 of adulthood. Lifespan is shown as Kaplan-Meier survival estimates c. In a separate biological replicate, the effects of NA on rpb-2(+); peft-3::TIR1 (circles) and rpb-2::AID; peft-3::TIR1 (squares) were compared, via the AFT-regression parameters estimated for VMC and lifespan remaining after VMC.. 6d. Error bars indicate 95% confidence intervals. d. At each NA concentration, Rf and Δμs were calculated to quantify the magnitude of disproportionate and proportionate changes, respectively, of NA on VMC and lifespan (S5 Text), for rpb-2(+);peft-3::TIR1 (circles) and rpb-2::AID;peft-3::TIR1 (squares) populations. Error bars indicate 95% confidence intervals. (PDF)</p

Automated, high-throughput phenotyping.

a. Using hand-annotated trajectories for 830 wild-type animals whose lifespan exposed to variety of environmental conditions, we built a Hidden Markov Chain Model that estimates probability of all possible transitions among states. Shown are the state transition probabilities for an individual after six hours spent in the current state. b. The results of a six-fold cross-validation scheme—the same data as in Fig 1D and 1E but plotted as Kaplan-Meier survival curves separately for each independent biological replicate, with by-hand (black) and automated results (red) compared. c. The error for each death time in these survival curves, plotted as a cumulative distribution function for each replicate. d. For the population of wild-type animals considered in Fig 1B and 1C, the cumulative distribution function describing the time spent non-moving prior to death and e. the fraction of lifespan spent non-moving. (PDF)</p

The relative effects of mutations and interventions on vigorous movement and lifespan.

a. The proportional and disproportionate effects of each intervention and mutations shown in Fig 5 were estimated (S5 Text), with Δμs quantifying the proportional action and Rf quantifying the disproportionate action of each intervention on VMC and death times. (PDF)</p

Relating vigorous movement and lifespan in wild-type populations.

a. The "clock-reset" hazard function showing the risk of death as a function of time after weak movement cessation (WMC). b. The absolute value of the residuals from the regression model di = vi+ εi, with the LOESS regression line (red) and 95 confidence bands for that interval (pink) and the mean residual value (blue). The White test statistic had a value of 28, showing a significant deviation from homoscedasticity at p = .015. c. the absolute value of the residuals from the regression model di = vi+ εi, with the LOESS and mean residual data shown as before. The White test statistic has a value of 233, larger than before, showing a deviation from homoscedasticity at p -10. d. The relationship between VMC and death times for each of 10 biological replicates of wild-type lifespan experiments, with linear regression lines (red) and LOESS regression line (green) overlaid. e. The same analysis, but comparing VMC to the lifespan remaining after VMC.f. The slope of the linear regression line, βv, relating VMC to lifespan as shown in panel d, compared across all replicates, grouped by food source (left) or environmental temperature (right).g. The same analysis as main text Fig 2C, comparing VMC and death times, in a single population of wild-type animals at 20°C, but here excluding individuals with the top and bottom 5th percentiles (gray dotted lines) of death times (left), of VMC times(middle) or of both VMC and death times (right). (PDF)</p

The effect of interventions on vigorous movement and lifespan.

a. In a population of 919 wild-type (purple) and 906 daf-2(e1368) (black) individuals, we estimated the risk of vigorous movement cessation (VMC) (solid) and the risk of death (dashed). b. In the same population, we estimated the "clock-reset" risk of an individual’s death after VMC for wild-type populations (light red) and daf-2(e1368) populations (dark red). c. For 1441 wild-type individuals housed at 20°C (black) and 2346 individuals housed at 25°C (purple), we estimated the same risks, for VMC (solid) and death (dashed). d. the “clock-reset” risk of death for the same populations as c. e. The relationship between each individual’s death and VMC times in a daf-2(e1368) population, with the linear regression line (red) and unit line y = x (black) overlaid. f. The same analysis but for a wild-type population housed at 25°C. g. The relationship between VMC times and lifespan remaining after VMC for the daf-2(e1368) population, with the linear regression line (red) and LOESS regression line (green) overlaid. h. The same analysis but for wild-type animals housed at 25°C. i. The relationship between VMC and lifespan for wild-type populations exposed to 3 mM t-BuOOH j. The relationship between VMC and remaining lifespan for the same population.</p

The effect of interventions and mutations on the slope of the linear model relating VMC and death times.

Parameter estimates of βv and the p-value testing the hypothesis (1-βv)! = 0. Confidence intervals and p-values were obtained via bootstrapping.</p