Ca²⁺ kinetics of single twitches in FDB fibres from WT and <i>Actn3</i> KO mice.

<p><i>A</i> Superimposed representative twitch transients from an <i>Actn3</i> KO and a WT fibre, showing faster [Ca²⁺]_i decay in the KO fibre. Across our sample as a whole, there was no difference between WT and <i>Actn3</i> KO fibres in the time taken to rise from 20% to 80% of peak (<i>B</i>). However, during decay, the rate constant of decay was significantly higher in <i>Actn3</i> KO fibres than in WT fibres, both during the fast phase (<i>C</i>) and slow phase (<i>D</i>). (In <i>B, C</i> and <i>D, n</i> = 36 for WT and <i>n</i> = 31 for KO. In <i>C</i> and <i>D</i>, equivalent time constants, in ms, are: 2.2 ± 0.1 for WT and 1.6 ± 0.1 for KO in fast phase; 25.1 ± 0.9 for WT and 16.0 ± 0.2 for KO in slow phase.)</p

[Ca²⁺]_i changes during fatigue in FDB fibres of WT and <i>Actn3</i> KO mice.

<p><i>A</i> Sample recordings of the progress of [Ca²⁺]_i during the whole fatigue run in a WT fibre and a KO fibre. <i>B</i> Individual transients taken from the time points marked by arrowheads in <i>A. C</i> Time taken for [Ca²⁺]_i to fall to pre-determined percentages of original. In <i>Actn3</i> KO fibres, [Ca²⁺]_i takes longer to fall to each level than in WT fibres. <i>D</i> Rate constants of decay for the tetanic transients at various time points during fatigue. The rate constant declines as fatigue progresses, but this decline was less marked in KO fibres than in WT. (In <i>C</i> and <i>D, n</i> = 4 for WT and <i>n</i> = 4 for KO; one, two and three asterisks denote <i>p</i>-values less than 0.05, 0.01 and 0.001 respectively; 2-way ANOVA with Bonferroni correction for multiple comparisons.)</p

Kinetic correction of rise time and exponential fitting of twitch transient decay.

<p><i>A</i> and <i>B</i> show a sample Ca²⁺ transient elicited by a single action potential in a WT fibre (<i>A</i>, rising portion of transient only, on an expanded time scale; <i>B</i>, whole transient). In <i>A</i>, the black line shows [Ca²⁺]_i as calculated from the raw fura-2 emission signal. The red line shows corrected [Ca²⁺]_i as calculated using <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004862#pgen.1004862.e001" target="_blank">Eqn. 1</a> (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004862#sec004" target="_blank">Methods</a>) to account for the slow binding of fura-2. The dashed lines running horizontally across the graph indicate the 20% to 80% range over which rise times were calculated. In this particular instance, the time taken to rise from 20% to 80% of maximum [Ca²⁺]_i is 40% lower in the corrected data than in the raw data. The extra gradations along the time axis indicate the frequency of sampling (20,000 Hz). In <i>B</i>, a double-exponential curve (red line) has been fitted to the decay phase of the Ca²⁺ transient (black line) using <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004862#pgen.1004862.e002" target="_blank">Eqn. 2</a> (see <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004862#sec004" target="_blank">Methods</a>).</p

Expression of major Ca²⁺-handling proteins in muscles of WT and <i>Actn3</i> KO mice.

<p>Protein expression analysis of the EDL (<i>A</i>), FDB (<i>B</i>) and quadriceps (<i>C</i>) muscles of WT and <i>Actn3</i> KO mice. Representative Western blots are shown with densitometry values normalised to total protein and the average of all WT samples. A significant increase in SERCA1 was observed in the EDL, FDB and quadriceps, along with an increase in calsequestrin (CSQ1) in the EDL and sarcalumenin (SAR) in the FDB and quadriceps. No change in RyR1 and DHPR expression were seen in the EDL and parvalbumin (PARVALB) is unchanged in both the EDL and FDB. A total of 6 WT and 6 <i>Actn3</i> KO EDL, 3 WT and 3 <i>Actn3</i> KO FDB and 4 WT and 4 <i>Actn3</i> KO quadriceps muscles were analysed. Statistical analyses were performed using the Mann-Whitney U non-parametric test (* denotes <i>p</i> < 0.05).</p

Cold acclimatisation and thermogenesis in α-actinin-3-deficient fibres.

<p>The diagram shows the mechanisms by which a loss of α-actinin-3 from fast glycolytic muscle fibres could promote adaptation to cold environments. The increased Ca²⁺ leak (3), increased mitochondrial enzyme activity (4) and increased fatigue resistance (5) are all features of muscle fibres from mice exposed to prolonged cold, and hence α-actinin-3 deficiency can be said to “pre-acclimatise” muscles to cold environments. In addition, the increased pumping by the SERCA1 Ca²⁺-ATPase consumes ATP and generates heat (9), providing a thermogenic mechanism which would also enhance cold survival.</p

Speed of shortening in FDB fibres of WT and <i>Actn3</i> KO mice.

<p><i>A</i> Image processing results in a representative WT FDB fibre recorded during electrical stimulation of a single twitch with a repetition frame rate of 422 μs (≈4.1 kfps). The left panel shows the original microscope image along with the processed segmented image for analysis of shortening parameters. The upper and lower border are visualised as straight lines in all images and can be easily followed during the online movie sequence for smoothness of shortening. The right panel shows the created output image containing the <i>l</i>(<i>t</i>), <i>l</i>(<i>t</i>)/<i>L</i>₀, vel(abs), vel(rel), fibre diameters and minimum shortening length calculated from the image processing algorithm. (Note that in the right panel, the text has been overtyped to improve legibility, as the original screenshot could not be obtained at a higher resolution.) <i>B</i> Biomechanical data for WT and <i>Actn3</i> KO fibres showing maximum shortening during the twitch and maximum shortening velocities in 17 WT and 20 <i>Actn3</i> KO fibres. <i>C</i> Velocity-diameter dependence of single fibres.</p

SR pump function in FDB fibres of WT and <i>Actn3</i> KO mice.

<p><i>A</i> Relationship between [Ca²⁺]_i and −d[Ca²⁺]_i /dt (rate of [Ca²⁺]_i decline) at selected time points during the slow phase of decay in twitch transients. Each point represents the mean ± S.E.M. across all twitch transients analysed in WT and KO fibres. The continuous lines are the SR pump function curves fitted to the points using the equation shown. <i>B</i> The parameter <i>A</i>, which reflects the rate of Ca²⁺ uptake by the SR pump, was significantly higher in fibres of KO mice. <i>C</i> The parameter <i>L</i>, which represents the rate of Ca²⁺ leak from the SR, was significantly higher in fibres of KO mice. (In all figures, <i>n</i> = 9 for WT and <i>n</i> = 9 for KO.)</p

Evidence Based Selection of Commonly Used RT-qPCR Reference Genes for the Analysis of Mouse Skeletal Muscle

<div><p>The ability to obtain accurate and reproducible data using quantitative real-time Polymerase Chain Reaction (RT-qPCR) is limited by the process of data normalization. The use of ‘housekeeping’ or ‘reference’ genes is the most common technique used to normalize RT-qPCR data. However, commonly used reference genes are often poorly validated and may change as a result of genetic background, environment and experimental intervention. Here we present an analysis of 10 reference genes in mouse skeletal muscle (<i>Actb, Aldoa, Gapdh, Hprt1, Ppia, Rer1, Rn18s, Rpl27, Rpl41 and Rpl7L1</i>), which were identified as stable either by microarray or in the literature. Using the MIQE guidelines we compared wild-type (WT) mice across three genetic backgrounds (R129, C57BL/6j and C57BL/10) as well as analyzing the α-actinin-3 knockout (<i>Actn3</i> KO) mouse, which is a model of the common null polymorphism (R577X) in human <i>ACTN3</i>. Comparing WT mice across three genetic backgrounds, we found that different genes were more tightly regulated in each strain. We have developed a ranked profile of the top performing reference genes in skeletal muscle across these common mouse strains. Interestingly the commonly used reference genes; <i>Gapdh, Rn18s</i>, <i>Hprt1</i> and <i>Actb</i> were not the most stable. Analysis of our experimental variant (<i>Actn3</i> KO) also resulted in an altered ranking of reference gene suitability. Furthermore we demonstrate that a poor reference gene results in increased variability in the normalized expression of a gene of interest, and can result in loss of significance. Our data demonstrate that reference genes need to be validated prior to use. For the most accurate normalization, it is important to test several genes and use the geometric mean of at least three of the most stably expressed genes. In the analysis of mouse skeletal muscle, strain and intervention played an important role in selecting the most stable reference genes.</p></div

RNA quality control.

<p>A) Bioanalyser output of total RNA extracted from mouse skeletal muscle. (L) Ladder, (1 – 3) representative muscle samples. B) Example of Bioanalyser electropherogram of RNA, (M) marker, 18S and 28S ribosomal RNA peaks.</p

RT-qPCR primers.

<p>Forward and reverse oligonucleotide sequences 5′ – 3′, product size and annealing temperature.</p