Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Mitochondrial physiology

As the knowledge base and importance of mitochondrial physiology to evolution, health and disease expands, the necessity for harmonizing the terminology concerning mitochondrial respiratory states and rates has become increasingly apparent. The chemiosmotic theory establishes the mechanism of energy transformation and coupling in oxidative phosphorylation. The unifying concept of the protonmotive force provides the framework for developing a consistent theoretical foundation of mitochondrial physiology and bioenergetics. We follow the latest SI guidelines and those of the International Union of Pure and Applied Chemistry (IUPAC) on terminology in physical chemistry, extended by considerations of open systems and thermodynamics of irreversible processes. The concept-driven constructive terminology incorporates the meaning of each quantity and aligns concepts and symbols with the nomenclature of classical bioenergetics. We endeavour to provide a balanced view of mitochondrial respiratory control and a critical discussion on reporting data of mitochondrial respiration in terms of metabolic flows and fluxes. Uniform standards for evaluation of respiratory states and rates will ultimately contribute to reproducibility between laboratories and thus support the development of data repositories of mitochondrial respiratory function in species, tissues, and cells. Clarity of concept and consistency of nomenclature facilitate effective transdisciplinary communication, education, and ultimately further discovery

Nucleolin can affect microtubules stability through multiple pathways.

<p>Based on previous studies and our unpublished observations, four hypotheses can be drawn to explain nucleolin’s role on microtubule dynamics, simplified in the current scheme by polymerization and depolymerization arrows (respectively in purple and yellow) at the Minus and plus Ends. The first hypothesis derives from nucleolin’s role on centrosome function (A-centrosome associated function, in blue). Indeed, nucleolin (in red) localizes at the mature centriole, interacting with ninein and γTuRC, where it is involved in microtubule nucleation and anchoring [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157534#pone.0157534.ref015" target="_blank">15</a>]. The second hypothesis is based on the control of RNAP II gene transcription (B- transcriptome associated function, in orange), which is regulated by nucleolin binding to a specific gene regulating element (our unpublished results). The third hypothesis is through binding to microtubule associated proteins or with actin cytoskeleton, known to interact with microtubule (C-Actin cytoskeleton interaction, in green). The fourth hypothesis is that nucleolin could directly interact with microtubules (D- Direct interaction, in red), thereby resulting in slower and longer-lasting polymerizing microtubules.</p

Nucleolin expression affects microtubule catastrophes.

<p>Analysis of catastrophe events in control [black], nucleolin depleted [dark red], nucleolin over expressing [dark blue], B23 depleted [light red] and B23 over expressing cells [light blue]. The asterisks indicate that the mean value differs from the control condition with the Wilcoxon-Mann-Whitney two-sample rank test at different significance levels: 10% (* P<0.1), 5% (** P<0.05), 0,5% (*** P<0.005). (A) Catastrophe frequency (10^-3s^-1) is calculated by dividing the time microtubules spend in growth (B)-(D) Catastrophe parameters are deduced by linking two temporally adjacent growths spatially spaced out by a Bgap (Backward Gap). The mean values of speed (B), life time (C) and length (D) during catastrophes were measured in each cell and reported on the graphs. (E) and (F): 2D graphs showing the repartition of the cells according to depolymerization speed (x-axis) and length (y-axis). Control [black], nucleolin over expressing [dark blue] and nucleolin depleted [dark red] (E) or B23 over expressing [light blue] and B23 depleted [light red] (F) cells are represented by the squares. (A-D) Cells were individually analyzed (control: 17 cells; NCL-siRNA: 24 cells; NCL-GFP: 10 cells; B23-siRNA: 11 cells; B23-GFP: 14 cells)</p

Nucleolin expression affects microtubule growth.

<p>(A)-(C): Box and whisker plots represent tracks for growth speed (A), growth life time (B) and growth displacement (C). For each condition (control [black], nucleolin depletion [dark red], nucleolin over expression [dark blue], B23 depletion [light red] and B23 over expression [light blue]), cells were individually analyzed (control: 18 cells; NCL-siRNA: 24 cells; NCL-GFP: 16 cells; B23-siRNA: 11 cells; B23-GFP: 15 cells). The mean value of the parameters was individually calculated in each cell. For each condition, the mean value of the parameters was obtained by averaging the value calculated for each cell. On the graphs, boxes indicate 25 and 75% quartiles and the whiskers extend to 1.5 times of the interquartile range. Outlier cells are not shown. The asterisks indicate that the mean values differ from the control condition with the Wilcoxon-Mann-Whitney two-sample rank test at different significance levels: 10% (* P<0.1), 5% (** P<0.05), 0,5% (*** P<0.005). (D) Kymographs of a single microtubule segment from the time-lapse series for each condition. (E)-(F) 2D graphs showing the repartition of the cells according to growth speed (x-axis) and growth life time (y-axis). Control [black], nucleolin over expressing [dark blue] and nucleolin depleted [dark red] or B23 over expressing [light blue] and B23 depleted [light red]. Cells are represented by the squares. Entire cell area were individually analyzed for each condition [control: 18 cells / NCL-siRNA: 24 cells / NCL-GFP: 16 cells / B23-siRNA: 11 cells / B23-GFP: 15 cells]. In all, thousands of microtubules were analyzed for each condition [control: 16262 microtubules / NCL-siRNA: 42737 microtubules / NCL-GFP: 10215 microtubules / B23-siRNA: 15915 microtubules / B23-GFP: 12664 microtubules]. The mean values of growth parameters are shown [speed (μm/min) / life time (s) / displacement (μm)]. σ is the standard deviation.</p

Loss of cold-resistant acetylated microtubules in nucleolin silenced cells.

<p>(A) Inhibition of nucleolin expression by siRNA. Western-blot analysis of whole cell extracts from untransfected control, mock transfected, control siRNA and nucleolin siRNA (siRNA concentration 2nM or 20nM) transfected cells. Cells were harvested four days after transfection and protein extracts were analyzed by western-blot using an anti- nucleolin polyclonal antibody (secondary antibody coupled to IRdye800) and acetylated tubulin (ac-tubulin) and β-actin monoclonal antibodies (secondary antibody coupled to Alexa680). (B) Quantifications of the fluorescent western blots, displayed in (A), expressed as a ratio of ac-tubulin over β-actin. The normalized expression level of acetylated tubulin was set to 100% in control cells (NCL siRNA 94.22% / NCL-GFP: 78.75% and 89.32%). (C) Microtubule regrowth after cold induced depolymerization in untransfected control and nucleolin siRNA transfected U2OS-centrin-1-GFP cells. Co-visualization of acetylated tubulin (ac-tub), centrin-1-GFP (C1G) and nuclear counterstain (DAPI) shown as 3-color merged image and black and white images of acetylated tubulin (inverted dynamics), before depolymerization first row), and immediately after depolymerization (second row). Centrin-1-GFP detection was enhanced with a GFP booster [green], acetylated tubulin was detected with a monoclonal antibody (secondary antibody coupled to Alexa555) [red on the 3-color merged images and black on black and white images]. Scale bars represent 10μm. (D) Quantification of the percentage of cells incubated in cold for 3h (C2, C6) exhibiting microtubules resistant to depolymerization. These cell classes are displayed for untransfected control cells (Cont.), control siRNA transfected cells (Cont. siRNA) and nucleolin siRNA transfected cells (NCL-siRNA). The values are expressed as percentages of the total number n of the cells studied. Error bars represent the standard deviation from two independent experiments (standard deviation of Bernoulli experiments = ).</p

Nucleolin expression affects all microtubule subpopulations.

<p>(A) Quadrant scatter plot showing the classification of microtubule growth tracks according to their growth speed (x-axis) and life time (y-axis). Example of microtubule growth tracks (849 tracks) detected in a single control cell. Microtubule growth tracks are represented by the filled circles. They are classified in four categories: N1 “slow and short lived” [red], N2 “slow and long lived” [green], N3 “fast and short lived” [yellow] and N4 “fast and long lived” [blue]. The fast and slow groups as well as the short-lived versus long-lived groups were spilt using the mean growth parameters of control cells [speed: 10.97μm/min and life time: 7.2s]. (B) Effect of nucleolin on the proportion of microtubules growth tracks in each subpopulation depicted in A. For each condition, the number of microtubules in each subpopulation was added for all the cells and the percentage was then calculated. The same color code serves to represent the four populations as in (A). The asterisks indicate a different repartition from the control condition (* P<0.05; χ² test). (C)-(E): Box and whisker plots represent tracks for growth speed (C), growth life time (D) and polymerization length (E) in the center and periphery of the cells (“c” and “p” respectively). For each condition (control, nucleolin depletion and nucleolin over expression), cells were individually analyzed (control: 18 cells; NCL-siRNA: 24 cells; NCL-GFP: 16 cells), in two ROI corresponding to the center and the periphery of the cells. The mean value of the parameters was individually calculated in each cell. For each condition, the mean value of the parameters was obtained by averaging the value calculated for each cell. On the graphs, boxes indicate 25 and 75% quartiles and the whiskers extend to 1.5 times of the interquartile range. The asterisks indicate that the mean values differ from the control condition (in the corresponding region: center vs periphery of the cell) with the Wilcoxon-Mann-Whitney two-sample rank test at different significance levels: 5% (* P<0.05), 1% (*** P<0.01). (F)-(H): Box and whisker plots represent the ratio for growth speed (F), growth life time (G) and polymerization length (F) of the center over the periphery of the cell. The ratio of the parameters was individually calculated in each cell. For each condition, the mean value of the parameters was obtained by averaging the value calculated for each cell. On the graphs, boxes indicate 25 and 75% quartiles and the whiskers extend to 1.5 times of the interquartile range. (I): Microtubule growth tracks are color coded by speed (left panel), life time (middle panel) or polymerization length (right panel) in the center (upper panels) or in the periphery (lower panels) of the cell displayed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157534#pone.0157534.g001" target="_blank">Fig 1A</a>.</p

Microtubule growth parameters.

<p>Microtubule growth parameters.</p

Microtubule dynamics analysis using the EB3-tagRFP plus-end tracking protein.

<p>(A) Still frames from time-lapse experiments show EB3-tagRFP signals. Upper left image represents EB3-tagRFP signal at t = 0s. On the right of the image, enlarged images of an EB3-tagRFP comet evolution (displayed on the full size image) are shown (upper enlarged panels from t = 0s to t = 19.2s). The plusTipTracker software package detects and tracks all the microtubule growing ends as exemplified on the enlarged images (lower enlarged panels). Lower image represents a temporal color code image of the EB3-tagRFP signal evolution from t = 0s to t = 19.2s. The color code scale is presented on the right. Scale bars represent 10μm. (B) Schematic representation of EB3-tagRFP tracking using the plusTipTracker software. Microtubule growing ends are schematized with the red circles. Transparent red circles represent temporarily comet disappearance. After comet detection and tracking, the software classifies the sub-tracks in three groups: polymerization, pause and catastrophe. For more details see [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157534#pone.0157534.ref025" target="_blank">25</a>][<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157534#pone.0157534.ref027" target="_blank">27</a>–<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0157534#pone.0157534.ref030" target="_blank">30</a>]. (C) Inhibition of nucleolin or B23 expression by siRNA. Western-blot analysis of whole cell extracts from untransfected control, mock transfected, control siRNA, nucleolin siRNA (siRNA concentration 2nM or 20nM) and B23 siRNA transfected cells. Cells were harvested four days after transfection and protein extracts were analyzed by western-blot using a nucleolin polyclonal antibody (detected with a secondary antibody coupled to IRdye800) and B23, α-tubulin and β-actin monoclonal antibodies (detected with secondary antibody coupled to Alexa680). (D) Quantifications of the fluorescent western blots, displayed in (C), expressed as a ratio of nucleolin over β-actin (left) or B23 over β-actin (right). The normalized expression level of nucleolin or B23 proteins was set to 100% in control cells (NCL siRNA 22.60% and B23 siRNA 20.59%). (E) Nucleolin over expression by transient transfection of a NCL-GFP construct. On the upper left image, the GFP channel is presented [black and white]. Arrows show nucleoli (nucleolin-GFP signal) and the centrosomes (C1G: Centrin-1-GFP signal) and cell outlines are shown. Lower image represents a temporal color code image of the EB3-tagRFP signal evolution for 40s. The color code scale is presented on the right of the image. Upper right image merge image of the GFP channel and the temporal color code image of the EB3-tagRFP signal is presented. Scale bars represent 10μm.</p

Pause and frequency parameters.

<p>Pause and frequency parameters.</p