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OPTiAGE

The trade-off between longevity and reproduction: optimal control of aging

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 OPTiAGE project word cloud

Explore the words cloud of the OPTiAGE project. It provides you a very rough idea of what is the project "OPTiAGE" about.

kinetic    extension    labelling    maintenance    line    isotope    longer    animals    function    restriction    partitioning    genetic    lifespan    self    genetically    principles    organismal    developmental    optimality    postulates    modulate    nematode    depending    repair    model    monkeys    environment    reproduction    fitness    varies    limitation    examine    exposed    shaped    trade    organisms    unavailable    disposable    genetics    accumulation    food    competitive    evolutionary    depends    nutrient    thereby    employing    experiment    diverse    environments    dictated    advantage    age    optimal    allocation    poor    scarce    damage    dst    nematodes    shorter    rhesus    combining    adapt    predicted    directed    theory    identical    inverse    living    elegans    plentiful    proposes    nutrients    alleles    mutation    conditions    maximize    aging    pave    continuous    delayed    assay    off    resource    quantify    worms    environmental    longevity    rate    mathematical    ultimately    combination    soma   

Project "OPTiAGE" data sheet

The following table provides information about the project.

Coordinator
FRIEDRICH MIESCHER INSTITUTE FOR BIOMEDICAL RESEARCH FONDATION 

Organization address
address: MAULBEERSTRASSE 66
city: BASEL
postcode: 4058
website: www.fmi.ch

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Project website http://www.towbinlab.org
 Total cost 187˙419 €
 EC max contribution 187˙419 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2018
 Duration (year-month-day) from 2018-09-01   to  2020-08-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    FRIEDRICH MIESCHER INSTITUTE FOR BIOMEDICAL RESEARCH FONDATION CH (BASEL) coordinator 187˙419.00

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 Project objective

The lifespan of genetically identical organisms varies depending on the environment they are exposed to. A well-known example is the extension of lifespan by nutrient restriction, as observed in animals as diverse as nematodes and rhesus monkeys. Why does the lifespan of animals change with environmental conditions? Is there an advantage to living longer when food is poor, and to living shorter when food is plentiful? Evolutionary theory, known as the disposable soma theory (DST), proposes that organisms age due to the accumulation of damage. According to theory, aging can be delayed by continuous damage repair, but such repair requires resources which are then unavailable for other tasks, such as reproduction. The DST therefore postulates a trade-off between longevity and reproduction dictated by the limitation of available resources. The optimal allocation of resources to self-maintenance depends on the environment. In particular, increased allocation to self-maintenance is predicted to maximize fitness when nutrients are scarce. Combining theory and experiment, I will investigate how the optimal allocation of resources to self-maintenance depends on nutrient availability using the nematode C. elegans as a model system. I will quantify the partitioning of resources between self-maintenance and reproduction using isotope labelling and kinetic modelling, and modulate resource allocation using available genetic alleles and directed mutation. Employing a competitive growth assay, I will test if fitness depends on resource allocation by an inverse U-shaped function, as predicted by theory and examine how the optimal resource allocation depends on nutrient availability. I will thereby assess if worms adapt their rate of aging to maximize their fitness in different environments. Ultimately, the proposed combination of mathematical modelling and developmental genetics will pave the way for a new line of research using optimality principles to study organismal development.

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