12,387.24 2.3.3 Conexión eléctrica

Ageing leads to a decline in function of most physiological characteristics, including reflexes, mobility, behaviour and ability to withstand stress. Stress responses do not make good biomarkers, since the easiest way to measure them is to measure time until death or incapacitation when subjected to the particular stressor. Other measures of functional ageing however, can often be measured with little disturbance to the subjects, since they are measures of normal behaviour. This is especially useful in Drosophila, since molecular biomarkers cannot be simply measured without the death of the subject.

Functional ageing can also be characterised by molecular changes, for instance the energy storage, protein synthesis and molecular damage accumulation can all have direct impacts on function at the organism level.

20.1

Mobility and Behaviour

One of the easiest functional measures of Drosophila ageing is their mobility. This includes their speed and reflexes and is a measure of muscular and peripheral nervous system degradation. One such measure of mobility is negative geotaxis. This is the innate response of Drosophila to climb upwards after being knocked down off a surface, thought to be an escape mechanism. Whether negative geotaxis is a measure of behaviour or simply muscular ability is debateable, however it serves as a solid biomarker of ageing, with long-lived indy and chico mutants showing a reduced decline in the behaviour compared to controls (Gargano et al., 2005). Flight ability can also be measured in Drosophila, releasing the flies in a flight chamber and recording their flight path. Wingbeat frequency can also be measured by tethering the flies and measuring with an optical tachometer. The ability of Drosophila to fly decreases with age, eventually losing all flight ability, accompanied by a modest reduction in wingbeat frequency, also eventually losing all capability in old age (Miller et al., 2008). Further, longevity selected lines have been shown to fly for longer, and with more frequency, than their controls at all but the youngest of tested ages (Graves, Luckinbill and Nichols, 1988).

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Closely related to mobility is behaviour. Measurable behaviours include sleeping, exploratory and feeding behaviours. Sleeping behaviour, as well as activity, can be simply measured using

Drosophila activity monitors and assuming prolonged inactivity is due to sleeping. These monitors measure the frequency of movement of a single fly across a chamber and can be used to measure a large number of individuals simultaneously (Pfeiffenberger et al., 2010). As in humans, Drosophila activity and sleep decreases and becomes more fragmented with age (Koh et al., 2006), making sleep a useful biomarker for age. Furthermore, sleep related genetic alterations can affect lifespan. Overexpressing glutamate-cysteine ligase in the mushroom body (the area of the brain which regulates sleep) causes lifespan extension (Luchak et al., 2007), while short lived mutants may show an older sleeping pattern, for instance shaker (Cirelli et al., 2005). There is evidence however, that activity decline is not always associated with old age in the patterns that are expected, with diet being shown to have no effect on activity except at very advanced ages (Bross, Rogina and Helfand, 2005).

Exploratory walking is another behaviour that shows age related decline. Individual flies can be recorded as they walk around an arena, and their movements tracked for analysis (Martin, 2004). Unlike negative geotaxis which is a reflex, exploratory walking is largely regulated by the central nervous system, the central complex and mushroom bodies (Serway et al., 2009). This means that tracking the deterioration of walking patterns can be a good biomarker for brain ageing for instance, older flies are less likely to move from the release point in the arena and will move less far if they do move (Grotewiel et al., 2005).

Although not necessarily a biomarker, feeding behaviour is potentially linked to some lifespan extension mechanisms. For instance, the gene takeout regulates feeding behaviour, possibly by regulating taste neurons. Knockout flies show less control over their feeding behaviour and overfeed in normal conditions (Meunier, Belgacem and Martin, 2007), while overexpression of takeout is associated with several lifespan extending conditions (Bauer et al., 2010). Otherwise, feeding behaviour is interesting as a corollary to other lifespan extension mechanisms, to show that they are not achieved through dietary restriction caused by reduced feeding.

20.2

Molecular Ageing

While physiological and behavioural measures are useful for assessing the health of an organism and predicting the mechanism of lifespan extension, molecular measures can also provide significant insight. These biomarkers may be able to help predict biological age, or they may be indicative of other processes involved in lifespan extension and are especially useful for quantifying molecular damage.

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One measure that changes with age in Drosophila is total protein content. Protein synthesis is highly reduced with age (Webster and Webster, 1979), likely due to a reduction in translational elongation factors (Webster and Webster, 1983). Thus, it may be expected that long lived flies would have increased protein synthesis and total protein content. Aside from the measure of total protein, protein damage is a useful biomarker of ageing.

Carbonylation of protein is a common form of oxidative damage, which accumulates with age and is associated with numerous ageing related diseases. This makes carbonylation a good biomarker for age related oxidative stress (Dalle-Donne et al., 2003).It can be measured in numerous ways, but most revolve around its derivatization by 2,4-dinitrophenylhydrazine (DNPH). Reacting DNPH with the carbonylated protein allows it to be quantified with a spectrophotometer by measuring the bound DNPH at 375nm (Levine et al., 2000; Wehr and Levine, 2012). This method has been used to develop further DNP based methods using antibodies for greater sensitivity. Consequently, the accumulation of carbonyl with ageing has been studied, for instance showing an increase of carbonyl groups in mitochondrial proteins (Toroser, Orr and Sohal, 2007). Additionally, carbonyl content is a useful measure of intervention success in reducing oxidative damage, for instance it has been used to corroborate the alleviation of oxidative damage by curcumin treatment of Drosophila (Seong et al., 2015). Longevity selected flies of the Wayne State lines have been shown to have a clearly lower level of protein carbonylation compared to their controls, rising to the same levels only in later life (Arking et al., 2000).

Two related molecular measures of ageing are lipid and glycogen content. In flies, lipids are stored in order to cope with low food availability (and as such are intrinsically linked with starvation

resistance) while glycogen is stored and for use directly as fuel for locomotion, as well as coping with desiccation. A large study of these characteristics in the Irvine lines found an increase in both lipid and glycogen content in the long-lived lines, accompanied by a corresponding increase in starvation, desiccation and ethanol resistance. The long lived lines were also more functionally capable, able to fly for longer periods before exhaustion (Graves et al., 1992).

Another key reason to study lipid stores is that they are the key source of energy used for

reproduction and fecundity. Indeed, one theory is that lifespan extension in selected flies is achieved through the increase of lipid storage and the reduction in this energy sources allocation to

reproduction (Graves et al., 1992), a theory apparently borne out by the Irvine lines which had both lower fecundity and higher lipid content (Service, 1987). Interestingly, in one of the rare delayed fecundity selection experiments where the long lived lines also had a higher early fecundity, there was a negative correlation between longevity and storage lipid content (Moghadam et al., 2015).

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Consequently, the relationship between energy stores and longevity phenotypes is not clear-cut but suggests a more complex relationship.