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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.

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

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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