Sarcopenia Age-Related Muscle Wasting and Weakness: Mechanisms and Treatments P29 potx

266 K. O’Connell et al.
Name of protein Peptide sequence Accession no.
Isolectric
point (pI)
Molecular
mass (kDa)
Peptides
matched
Mascot
score
% coverage
H
+
-transporting two-
sector ATPase
alpha chain
RLTELLKQ
A35730 7.2 58.9 13 564 31
KLELAQYRE
RVLSIGDGIARV
KAVDSLVPIGRG
RGYLDKLEPSKI
KTSIAIDTIINQKR
KGIRPAINVGLSVSRV
REAYPGDVFYLHSRL
RILGADTSVDLEETGRV
KLKEIVTNFLAGFEP
RTGAIVDVPVGDELLGRV
KQGQYSPMAIEEQVAVIYAGVRG
REVAAFAQFGSDLDAATQQLLSRG
267Proteomic and Biochemical Profiling of Aged Skeletal Muscle

(Piec et al. 2005; Gelfi et al. 2006a; O’Connell et al. 2007; Doran et al. 2008; Feng
et al. 2008; Lombardi et al. 2009). It is, however, important to stress that motor
neurons form an integral part of the physiological units that regulate and maintain
excitation–contraction coupling and muscle relaxation. In contrast to the relatively
stable skeletal muscle genome, the fibre proteome does not exist as a distinct cohort
of biomolecules. For obvious biological reasons, any tissue-specific protein com-
plement is constantly changing and adapting to altered physiological and pathologi-
cal demands. This phenomena is even more pronounced in the case of the muscle
proteome, since skeletal muscles belong to the class of excessively plastic and
adaptable tissues (Pette 2001; Flueck and Hoppeler 2003). The heterogeneous char-
acter of individual muscles and the inescapable influence of neuromuscular activity
on fibre distribution make the proteomic profiling of diseased or aged muscles more
complex as compared to many other tissues. Besides biological considerations,
another major hurdle for the comprehensive cataloging and differential analysis of
muscle proteomes is the concentration range of proteins. It is currently difficult to
accurately determine differences in skeletal muscle protein density.
However, proteomic studies have determined the dynamic range of plasma pro-
tein concentrations and predict that at least nine orders of magnitude separate one of
the most abundant elements of this body fluid, albumin, and the rarest protein in this
body fluid, interleukin-6 (Pieper et al. 2003). The concentration range of plasma
proteins involved in immune defense, coagulation and metabolite transportation has
been estimated from pg/ml-values at the low abundance end to mg/ml-values at the
high abundance end (Anderson and Anderson 2002). A similar dynamic range in
protein concentration probably also exists in contractile tissues. If one takes into
account the fact that the human genome consists of approximate 30,000 genes which
in turn produce several 100,000 individual proteins, it is safe to assume that the
number of protein isoforms in the skeletal muscle proteome exceeds the number of
muscle-specific genes. Therefore, for both technical and biological reasons, the current
mass spectrometric recording of the electrophoretically or chromatographically
separated muscle protein complement can only represent a partial documentation of

the entire fibre proteome. Even the most sophisticated approaches for the simultane-
ous visualization of the soluble components derived from a specific proteome, such
as fluorescence difference in-gel electrophoresis (Viswanathan et al. 2006), can only
separate a few thousand proteins (Doran et al. 2006). Thus, even proteomic studies
of tissues with a relatively low number of individual classes of proteins and a con-
siderably narrower range of protein concentrations as observed in plasma, can only
determine the near-to-total proteome.
Over the last few years, muscle proteomics has identified the most abundant
components of contractile fibres from various species, including humans and the
most important animal species used for biomedical research. Most studies have
focused on the total soluble protein complement, but more discriminatory
approaches covering low-abundance elements from distinct subcellular fractions
and membrane-associated proteins are emerging. The cataloguing of total muscle
proteomes has included tissues derived from mouse (Raddatz et al. 2008), rat
(Yan et al. 2001), rabbit (Donoghue et al. 2007), chicken (Doherty et al. 2004),
268 K. O’Connell et al.
sheep (Hamelin et al. 2007), pig (Kim et al. 2004), cow (Bouley et al. 2005) and
human (Gelfi et al. 2003). Subproteomic profiles have been reported for the cyto-
solic, microsomal, nuclear and mitochondrial fraction (Forner et al. 2006;
Vitorino et al. 2007). Muscle protein expression levels were determined under
developmental, physiological, pathological and aging conditions. Comparative
studies have included the proteomic characterization of myoblast differentiation
(Kislinger et al. 2005), muscle transformation (Donoghue et al. 2005), the effect
of endurance exercise (Burniston 2008), muscular hypertrophy (Hamelin et al.
2006), disuse fibre atrophy (Isfort et al. 2000), adaptation to hypobaric hypoxia
(Vigano et al. 2008), sepsis-related muscle damage (Duan et al. 2006), hypoxia-
associated metabolic modulations (De Palma et al. 2007), neonatal muscle fibre
necrosis of postural muscles (Le Bihan et al. 2006), denervation–reinnervation
cycles (Sun et al. 2006), x-linked muscular dystrophy (Doran et al. 2006), dysfer-
lionpathy (De Palma et al. 2006) and aging (Doran et al. 2008). Post mortem

changes in the fibre proteome have been profiled for agriculturally important
animal muscles, i.e. bovine and porcine meat (Lametsch and Bendixen 2001; Jia
et al. 2006). Since post-translational modifications (PTM) play a crucial role in
protein function and are responsible for much of the heterogeneity in muscle
proteins, the establishment of proteomic maps based on common PTMs has been
initiated. This includes the identification of critical glycosylation, phosphoryla-
tion, nitration and carbonylation sites and their role in health and disease (Kanski
et al. 2005; Meany et al. 2007; Gannon et al. 2008; O’Connell et al. 2008a; Feng
et al. 2008).
3 Proteomics of Muscle Aging
To better understand aging of the neuromuscular system, numerous proteomic
studies have been carried out over the last few years. Major studies are listed in
Table 2. The usual workflow of gel electrophoresis-based proteomic studies of
muscle aging and the subsequent biochemical and cell biological characterization
of novel mass spectrometry-identified protein markers is illustrated in Fig. 2. The
general trend of altered protein expression patterns agrees with the findings from
previous physiological, biochemical, cell biological and genomic studies (Piec
et al. 2005; Gelfi et al. 2006a; Dencher et al. 2006, 2007; O’Connell et al. 2007;
Doran et al. 2007c, 2008; Lombardi et al. 2009; Capitanio et al. 2009). However,
certain results from transcriptomic analyses of muscle aging do not concur with
proteomic investigations (Welle et al. 2001; Giresi et al. 2005; Dennis et al. 2008).
Several genes that encode mitochondrial enzymes are down-regulated in aged
fibres (Kayo et al. 2001), while the protein ratio between mitochondrial and glyco-
lytic muscle proteins was shown to be increased (Piec et al. 2005; Gelfi et al.
2006a; Doran et al. 2008). Possibly, age-related alterations at the transcriptional
and proteomic level do not correspond for all classes of proteins. Transcriptomic
investigations have demonstrated that the age-related up-regulation of genes
269Proteomic and Biochemical Profiling of Aged Skeletal Muscle
includes factors involved in stress response, apoptosis, inflammation, proteolysis
and neuronal regulation (Roth et al. 2002). In contrast, aging is associated with a

down-regulation of genes that encode muscle proteins engaged in fibre remodel-
ing, the regulation of energy metabolism and muscle growth (Dennis et al. 2008).
These results indicate that progressive muscle weakness in the elderly is a highly
complex process. The large-scale proteomic profiling of aging muscles might
throw new light on the multi-factorial etiology of sarcopenia and determine the
pathobiochemical hierarchy in the many pathways that lead to contractile
dysfunction.
Previous biomedical studies have established that the loss in skeletal muscle
mass and function during aging is associated with a large variety of molecular and
cellular abnormalities (Faulkner et al. 2007; Edstrom et al. 2007). This includes a
shift to a slower-twitching fibre population (Prochniewicz et al. 2007), decreased
protein synthesis of myofibrillar components (Balagopal et al. 1997), disturbed ion
handling (Schoneich et al. 1999), a blunted stress response (Kayani et al. 2008),
progressive denervation (Carlson 2004), decreased capillarisation (Degens 1998),
excitation–contraction uncoupling (Delbono et al. 1995), oxidative stress (Squier
and Bigelow 2000), mitochondrial dysfunction (Figueiredo et al. 2008), increased
susceptibility to apoptosis (Dirks and Leeuwenburgh 2002), a metabolic disequilib-
rium (Vandervoort and Symons 2001), progressive decline in energy intake
(Roberts 1995), a reduced regenerative potential (Renault et al. 2002) and inade-
quate levels of essential growth factors and hormones indispensable for the main-
tenance of the excitation–contraction–relaxation cycle (Lee et al. 2007). Proteomics
promises to unearth what primary changes within this complex molecular patho-
genesis cause detrimental down-stream alterations. The large-scale protein bio-
chemical analysis of muscle aging may also elucidate what compensatory
adaptation processes, repair mechanisms and stress responses are initiated to limit
age-dependent fibre degeneration.
Table 2 Proteomic profiling studies of sarcopenia of old age
Mass spectrometry-based proteomic
analysis Species
Skeletal muscle type

or fraction
References
Profiling of total soluble proteome Human Vastus lateralis Gelfi et al. 2006a
Profiling of total soluble proteome Rat Gastrocnemius Piec et al. 2005
O’Connell et al. 2007
Doran et al. 2008
Lombardi et al. 2009
Profiling of motor unit Rat Sciatic nerve and
gastrocnemius
Capitanio et al. 2009
Profiling of small heat shock proteins Rat Gastrocnemius Doran et al. 2007c
PTM analysis of protein glycosylation Rat Gastrocnemius O’Connell et al. 2007
PTM analysis of protein nitration Rat Gastrocnemius Kanski et al. 2005
PTM analysis of protein carbonylation Rat Mitochondria Feng et al. 2008
PTM analysis of protein phosphorylation Rat Gastrocnemius Gannon et al. 2008
Subproteomic analysis Rat Mitochondria Dencher et al. 2006,
2007
270 K. O’Connell et al.
3.1 Remodeling of the Contractile Apparatus during Aging
Major physiological and cell biological differences exist between type-I, type-IIa
and type-IIb fibres. Differences in motor neuron size, capillary density, myoglobin
content, mitochondrial density and metabolite content closely relate to the biochemi-
cal composition of the contractile apparatus (Pette and Staron 1990; Punkt 2002;
Spangenburg and Booth 2003). A major interest in muscle aging research is to
understand what exact changes on the protein level cause a loss of contractile
strength in both slow and fast muscles (Prochniewicz et al. 2007). The proteomic
analysis of aged muscle has revealed a generally perturbed protein expression pat-
tern in senescent muscle (Piec et al. 2005; O’Connell et al. 2007; Doran et al. 2008;
Fig. 2 Proteomic workflow for the identification and characterization of novel biomarkers of
skeletal muscle aging. Shown is the gel-electrophoresis (GE)-based separation of young adult ver-

sus senescent muscle extracts. Two-dimensional gels were stained with colloidal Coomassie Blue
(CCB) dye (O’Connell et al. 2007). Difference in-gel electrophoresis (DIGE) is routinely used for
the fluorescent tagging and separation of muscle proteomes and mass spectrometric technology is
usually employed to unequivocally identify proteins that exhibit a changed abundance during fibre
aging. Potential alterations in the biological activity, oligomeric status, expression level, subcellular
localization and/or post-translational modifications of newly identified skeletal muscle proteins are
then determined by standard biochemical and cell biological methods
271Proteomic and Biochemical Profiling of Aged Skeletal Muscle
Lombardi et al. 2009; Capitanio et al. 2009), including many of the proteins belonging
to the contractile apparatus that makes up approximately 50% of the total muscle
protein complement. The supramolecular protein assemblies forming the thick and
thin filaments of the basic contractile units exist in a great variety of fibre type-
specific isoforms (Pette and Staron 1990). In the presence of ATP, a highly complex
and cyclic coupling process between actin filaments and myosin head structures
provides the molecular basis for the sliding of thin filaments past thick filaments
causing distinct increments of sarcomere shortening (Gordon et al. 2000; Fitts
2008). The contractile status is controlled by the cytoplasmic Ca
2+
-concentration
whereby the troponin complex and tropomyosin strands directly regulate and enable
actomyosin interactions for force generation (Swartz et al. 2006; Kreutziger et al.
2007). In skeletal muscles, a close relationship exists between isoform expression
patterns of contractile proteins and metabolic fibre properties (Pette and Staron
2001). Thus, to understand the molecular mechanisms that underlie age-related fibre
type shifting, a special interest focuses on potential alterations in the isoforms of
myosin, actin, troponin or tropomyosin. Myosins consist of a hexameric structure
consisting of 2 MHC heavy chains and various MLC light chains (Clark et al. 2002;
Bozzo et al. 2005). A recent study by Capitanio et al. (2009) has shown a clear age-
dependent transformation process within the pool of myosin heavy chain isoforms,
i.e. a transition from fast MHC-IIb to MHC-IIa to slow MHC-I in 8-month versus

22-month old rat gastrocnemius muscle. This pattern of MHC changes is in line with
observed adaptive processes in chronic electro-stimulated fast muscle (Pette 2001)
and exercised muscles (Sullivan et al. 1995).
Fast-to-slow transformation is evidently associated with a shift to more oxidative
metabolism and a concomitant change in the aged contractile apparatus to slower
kinetics. The proteomic profiling of fast muscles following chronic low-frequency
stimulation has shown that light and heavy chains of myosin undergo a stepwise
replacement from fast to slow isoforms (Donoghue et al. 2005, 2007). Previous
biochemical studies have shown similar effects of the neuromuscular activity on the
expression of individual subunits of troponin (Pette and Staron 2001). In analogy,
a comparable process appears to occur during muscle aging causing a drastic
increase in the abundance of slow isoforms of key contractile elements in senescent
fibres (Gelfi et al. 2006a; Doran et al. 2008; Capitanio et al. 2009). A comprehen-
sive proteomic study of rat muscle aging, using the highly discriminatory fluores-
cent difference in-gel electrophoresis technique, has identified the slow myosin
light chain isoform MLC-2 as one of the most drastically altered muscle proteins in
this animal model of sarcopenia (Doran et al. 2008). Thus, both myosin light chains
and heavy chains seem to shift towards slower isoforms. Application of the phos-
pho-specific fluorescent dye ProQ-Diamond demonstrated that the abundance of
the slow MLC-2 protein is not only drastically increased, but that its phosphoryla-
tion levels are even more enhanced in senescent gastrocnemius fibres (Gannon
et al. 2008). This supports the idea of an age-related shift to a slower-twitching fibre
population and suggests changed expression levels and altered post-translational
modifications in myosin components as novel candidates for establishing a biomarker
signature of muscle aging.
272 K. O’Connell et al.
3.2 Metabolic Adaptations in Aged Skeletal Muscle
Findings from the proteomic analysis of bioenergetic adaptations in aged muscle
agree with previous physiological and biochemical studies of fibre aging. The
results from different proteomic studies of muscle aging have demonstrated that a

general shift occurs in major metabolic pathways towards a more oxidative muscle
metabolism (Doran et al. 2009a). However, species-specific differences appear to
exist with respect to the degree of modifications in distinct rate-limiting enzymes
and metabolite transporters, as well as in the complexity of these changes in par-
ticular pathways (Piec et al. 2005; Gelfi et al. 2006a; Doran et al. 2008). When
studying the effects of physiological or pathological factors on contractile function,
it is crucial to take into account the influence of patterns of innervation and activity
on the metabolic and bioenergetic properties of skeletal muscles. In the case of
diseased and aged muscles, it has clearly been documented that long-term inactivity
inevitably results in disuse atrophy which results in a drastic reduction in tissue
mass and contractile strength (Kandarian and Jackman 2006). Proteomic studies
have to take into account the heterogeneity of skeletal muscles and build on the
previous biochemical and physiological knowledge on fibre type characteristics and
how they relate to specific marker proteins. Distinct protein expression signatures
can be conveniently employed to differentiate between type I and type II fibres. The
abundance and or isform expression pattern of many metabolic enzymes, excita-
tion–contraction coupling elements, ion-handling proteins and contractile compo-
nents can be used to determine fibre type distributions. The proteomic profiling of
fast-twitching fibres agrees with a predominantly glycolytic metabolism, a high
recruitment frequency, an easily fatigable phenotype and a high maximum power
output (Okumura et al. 2005; Gelfi et al. 2006b). On the other hand, the protein
complement of slower fibres is perfectly adapted to oxidative metabolism, a low
recruitment frequency, resistance to fatigue and a low maximum power output
(Okumura et al. 2005; Gelfi et al. 2006b). Especially striking is the difference in the
density of myosin isoforms, glycolytic enzymes, citric acid cycle enzymes, oxida-
tive phosphorylation elements, the oxygen carrier myoglobin and the fatty acid
binding protein FABP. In addition, the abundance of Ca
2+
-dependent binding pro-
teins, pumps, channels and exchangers differs considerably between fast and slow

muscles (Froemming et al. 2000). These established fibre type-specific markers
could now be used for the interpretation of proteomic profiles generated by mass
spectrometry-based muscle aging studies.
Major age-dependent alterations in the expression of catabolic enzymes and
rate-limiting transporter molecules have been demonstrated by proteomics (Piec
et al. 2005; Doran et al. 2008). As an example, Fig. 3 illustrates the age-related
increase in the enzyme adenylate kinase. The expression of the soluble AK1 iso-
form was shown to be increased using both fluorescent difference in-gel electro-
phoresis and two-dimensional immunoblotting. Adenylate kinase, in conjunction
with creatine kinase, maintaines a major nucleotide pathway in skeletal muscle.
Increased levels of the AK1 isoform suggest adaptive processes that regulate
273Proteomic and Biochemical Profiling of Aged Skeletal Muscle
nucleotide ratios in aging fibres. Other skeletal muscle proteins that exhibit an
age-related change in concentration are involved in the transportation of oxygen,
the provision of fatty acids and the removal of carbon dioxide, as well as the
maintenance of glycolysis, the citric acid cycle and oxidative phosphorylation
(Piec et al. 2005; Gelfi et al. 2006a; Doran et al. 2008). Muscle aging is associated
with a reduced glycolytic flux due to a drastic reduction in key glycolytic enzymes,
such as pyruvate kinase, phosphofructokinase and enolase. The reduction of the
key regulatory enzyme pyruvate kinase was shown by Deep Purple staining
(O’Connell et al. 2007), a DIGE-based study (Doran et al. 2008) and PTM analysis
(O’Connell et al. 2008a). Pyruvate kinase facilitates the final oxidoreduction-
phosphorylation reaction during glycolysis that converts phosphoenolpyruvate to
29.7
67
pH
Adult muscle
a
cd e
b

kDa
CA3
AK - Cy3
AK1
AK1
Adult
Aged
AK - Cy5 AK - IB
CA3
AK1
AK1
Cy3 Cy5
Aged muscle
pH
8 678
22.8
21.6
Fig. 3 Proteomic profiling of adenylate kinase isoform AK1 in senescent skeletal muscle. Shown
is an expanded view of fluorescently tagged two-dimensional gels of the young adult muscle
proteome versus the aged muscle proteome. Preparations from differently aged rat gastrocnemius
muscles were labelled with the CyDyes Cy3 (a) and Cy5 (b). In panels (c) and (d) are shown the
comparative graphic representation of the AK1 spot in young adult versus aged fibres, respec-
tively. A major two-dimensional protein spot of approximately 30 kDa represents the abundant
muscle enzyme carbonic anhydrase (CA3). The portion of the two-dimensional gel illustrated
covers the range of approximately pH 7 to pH 8 in the first dimension and a molecular mass range
of approximately 20–30 kDa in the second dimension. While the CA3 spot exhibits comparable
levels between adult and aged muscle, the AK1 protein is clearly increased in aged muscle. The
elevated expression level of adenylate kinase was confirmed by two-dimensional immunoblot (IB)
analysis (e). Standard methods were employed for fluorescent difference in-gel electrophoresis
and immunoblotting (Doran et al. 2006)

274 K. O’Connell et al.
ATP and pyruvate (Munoz and Ponce 2003). The decreased expression of the
PK-M1 isoform of pyruvate kinase agrees with a shift to more aerobic-oxidative
metabolism in senescent muscle. Although pyruvate kinase levels are reduced
during aging, the remaining cohort of this glycolytic enzyme exhibits drastically
increased levels of both N-glycosylation (O’Connell et al. 2008a) and tyrosine
nitration (Kanski et al. 2005). Abnormal post-translational modifications in meta-
bolic enzymes are believed to negatively affect the biological activity of glycolytic
enzymes, which was shown to be true in the case of the PK-M1 isoform. Senescent
muscle are characterized by a reduced pyruvate kinase activity (O’Connell et al.
2008a). Enhanced N-glycosylation probably influences protein stability, cellular
targeting, inter- and intra-molecular interactions, and coupling efficiency between
substrates and active site of this enzyme, causing a diminished glycolytic flux rate
in aged fibres. In addition, the expression of pyruvate dehydrogenase, the metabolic
linker between glycolysis and the citric acid cycle, is lower in aged fibres (Doran
et al. 2008). Consequently, the transformation of pyruvate into acetyl-CoA is
reduced in sarcopenia. The proteomic analysis of the phosphoprotein cohort of
aged muscle showed increased phosphorylation for lactate dehydrogenase, albumin
and aconitase, and decreased phosphorylation in cytochrome-c-oxidase, creatine
kinase and enolase (Gannon et al. 2008). Hence, age-related changes in the muscle
phosphoproteome are associated with metabolic enzymes from the cytosolic and
mitochondrial compartment. This agrees with the idea that sarcopenia is a highly
complex muscle disease that causes drastic alterations in the expression and molec-
ular structure of important metabolic regulators.
The biochemical analysis of the fast-to-slow transformation process in chronic
electro-stimulated fast muscles strongly suggests that the two most crucial limiting
factors of oxidative metabolism are represented by the availability of oxygen and
the rate of fatty acid transportation (Kaufmann et al. 1989). Since in senescent
muscles an up-regulation of both the fatty acid transporter FABP and the oxygen-
carrier myoglobin has been demonstrated by proteomic analysis (Doran et al.

2008), these alterations in biomarkers suggest that senescent fibres switch to a more
aerobic-oxidative metabolism. In agreement with this major metabolic adaptation
is the increased expression of citric acid cycle enzymes such as succinate dehydro-
genase, isocitrate dehydrogenase and malate dehydrogenase in senescent muscles
(Piec et al. 2005; Gelfi et al. 2006a; Doran et al. 2008). Recently Lombardi et al.
(2009) have determined both the transcriptomic and proteomic profile of aged rat
muscle employing a combination of DNA array and native blue PAGE technology.
Aging seems to differentially affect the abundance, supramolecular organization
and activity of the various mitochondrial complexes associated with the oxidative
phosphorylation pathway. Although aging is generally associated with a shift to
more oxidative muscle metabolism, senescent human muscles showed a more pro-
nounced transition from predominantly glycolytic to mitochondrial energy genera-
tion (Gelfi et al. 2006a) as compared to small mammalians such as rats (Piec et al.
2005). These species-specific differences should be taken into account in animal
model studies. The extrapolation of results from aging rat muscle to the human
aging process should be undertaken with caution.
275Proteomic and Biochemical Profiling of Aged Skeletal Muscle
3.3 Cellular Stress Response in Aged Skeletal Muscle
The fast and efficient up-regulation of stress proteins is an essential cellular survival
mechanism that prevents excess protein degradation and deleterious protein aggre-
gation during tissue injury (Ellis and van der Vies 1991). In healthy adult muscle
fibres, the natural response to stressful conditions involves a diverse array of
molecular chaperones, mostly belonging to the very large family of heat shock
proteins. During fibre adaptation or cellular regeneration phases, molecular chaper-
ones stabilize denatured muscle proteins and facilitate the correct folding and con-
formational maturation in nascent peptides (McArdle and Jackson 2000). Muscle
chaperones protect fibres during extensive contractile activity, traumatic injury,
hyperthermia, hypoxic insult, ischemic damage and neuromuscular pathology
(Nishimura and Sharp 2005). A common feature of chaperoning heat shock pro-
teins is a promotor region that contains a consensus-binding sequence for HSF1

(Amin et al. 1988), the heat shock transcription factor that is associated with the
response of cells following exposure to acute stressors (Anckar and Sistonen 2007).
Heat shock proteins are classified according to their relative molecular mass.
Besides the widely distributed Hsp60s, Hsp70s, Hsp90s and Hsp100s, some low-
molecular-mass heat shock proteins are specifically induced during muscle injury
(Golenhofen et al. 2004). These small members of the cytoprotective chaperone
complement of skeletal muscles are characterized by a a-crystallin domain, a con-
served 90-residue carboxy-terminal sequence (van Montfort et al. 2001). A major
function of muscle-specific small heat shock proteins is the prevention of deleteri-
ous protein aggregation, and they are especially involved in the modulation of
intermediate filament assembly (Nicholl and Quinlan 1994).
Heat shock proteins are relatively soluble and abundant, making them ideal can-
didates for proteomic investigations. Over the last few years, a large number of
proteomic studies have identified cellular chaperones in muscle tissues. Most mass
spectrometry-based analyses showed increased levels of heat shock proteins in the
neuromuscular system following exposure to physiological or pathological stressors.
This included the large-scale screening of fibre transformation following chronic
electro-stimulation (Donoghue et al. 2005, 2007), moderate intensity endurance
exercise (Burniston 2008), myoblast differentiation (Gonnet et al. 2008; Tannu et al.
2004), muscular hypertrophy (Hamelin et al. 2006), nerve crush-induced denerva-
tion (Sun et al. 2006), experimental muscular atrophy following hindlimb suspen-
sion (Seo et al. 2006), dystrophinopathy-associated necrosis (Doran et al. 2006),
experimental exon-skipping therapy of muscular dystrophy (Doran et al. 2009b),
dysferlin-related myopathy (De Palma et al. 2006), burn sepsis-induced stress (Duan
et al. 2006), hypoxia-related stress (Bosworth et al. 2005) and post mortem changes
in muscle fibres (Jia et al. 2006), as well as age-dependent muscle degeneration
(Piec et al. 2005; O’Connell et al. 2007; Doran et al. 2007c; Feng et al. 2008;
Lombardi et al. 2009; Capitanio et al. 2009). Interestingly, mass spectrometry-based
proteomics of aged muscles has shown increased levels of distinct small chaperones,
especially the cardiovascular heat shock protein cvHsp (Doran et al. 2007c).