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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.

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

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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