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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.

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

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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