Location of temperature-dependent accessible residues.

<p>(A) Sequence alignment of pore domains of rat TRPV1 and mouse TRPV3. Predicted structural domains are indicated above. Residues with temperature-independent accessibility are highlighted in cyan and residues with temperature-dependent accessibility are in pink. (B) Homology models of pore domains. Same color coding was used as the above.</p

Single Residues in the Outer Pore of TRPV1 and TRPV3 Have Temperature-Dependent Conformations

<div><p>Thermosensation is mediated by ion channels that are highly temperature-sensitive. Several members of the family of transient receptor potential (TRP) ion channels are activated by cold or hot temperatures and have been shown to function as temperature sensors in vivo. The molecular mechanism of temperature-sensitivity of these ion channels is not understood. A number of domains or even single amino acids that regulate temperature-sensitivity have been identified in several TRP channels. However, it is unclear what precise conformational changes occur upon temperature activation. Here, we used the cysteine accessibility method to probe temperature-dependent conformations of single amino acids in TRP channels. We screened over 50 amino acids in the predicted outer pore domains of the heat-activated ion channels TRPV1 and TRPV3. In both ion channels we found residues that have temperature-dependent accessibilities to the extracellular solvent. The identified residues are located within the second predicted extracellular pore loop. These residues are identical or proximal to residues that were shown to be specifically required for temperature-activation, but not chemical activation. Our data precisely locate conformational changes upon temperature-activation within the outer pore domain. Collectively, this suggests that these specific residues and the second predicted pore loop in general are crucial for the temperature-activation mechanism of these heat-activated thermoTRPs.</p> </div

Temperature-dependent labeling in TRPV3.

<p>(A) Temperature as a function of time during FLIPR temperature-activation assay. (B) Representative examples of fluorescence responses upon temperature stimulation of TRPV3 I652C. n>8 wells. Error bars are mean ±2x s.e. (C) Average basal fluorescence change of TRPV3 I652C after incubation of MTSET at 20°C and 40°C. For each experiment, the basal fluorescence is an average of fluorescence between 0 and 20 sec. Fluorescence change is the difference of MTSET incubation and buffer incubation basal fluorescence. Numbers of independent experiments are shown in the bar graph and n>8 wells per experiment. Error bars are mean ± s.e. Two-tailed t-test, ***p<0.0001. (D) Representative examples of fluorescence responses upon temperature stimulation of L655, n>8 wells, Error bars are mean ±2× s.e. (E) Average basal fluorescence change of TRPV3 L655C after incubation of MTSET at 20°C and 40°C. Number of experiments is shown in the bar graph and n>8 wells per experiment. Error bars are mean ± s.e. Two-tailed t-test, **p = 0.0062. (F) The basal fluorescence change of TRPV3 L655C after incubation of MTSET at 20°C and 40°C as a function of MTSET concentration. The incubation time was 10 min. n>5 wells. Error bars are mean ± s.d. Straight lines are exponential fits to the data.</p

Temperature-dependent labeling in TRPV1.

<p>(A) Temperature as a function of time during FLIPR temperature-activation assay. (B–D) Representative examples of fluorescence responses upon temperature stimulation of TRPV1 N652C (B), A657C (C) and Y53C (D) after incubation of MTSET at 20°C (blue) and 42°C (red). For both temperatures, buffer as a negative control is colored gray; n>8 wells. Error bars are 2× s.e. (E) Average basal fluorescence change of TRPV1 Y653C after incubation of MTSET at 20°C and 42°C. The basal fluorescence is averaged fluorescence level between 0 to 20 sec. For each experiment, the increase of basal fluorescence was obtained by subtracting buffer control from MTSET incubation. Five independent experiments were performed for 20°C and three for 40°C with n>5 wells per experiment. Two-tailed t-test, *p = 0.036. Error bars are mean ± s.e.</p

Electrophysiological characterization of temperature-dependent MTSET accessibility of TRPV1 Y653C.

<p>(A) Above: Temperature profile for a whole-cell voltage-step protocol. Middle: Voltage-step protocols were applied before (I) and after (II) MTSET application at 20°C or 40°C. Bottom: Example of current traces of Y653C before and after 2 mM MTSET at 20°C. (B) Average change of plateau current (+100 mV) upon application of MTSET at 20°C or 40°C. Data are averages from five patches. Two-tailed t-test, **p = 0.00034. (C) Current-voltage (IV) curves from whole-cell measurement. Error bars are mean ± s.e.</p

Deciphering Kinetic Information from Single-Molecule FRET Data That Show Slow Transitions

Single-molecule FRET is one of the most powerful and widely used biophysical techniques in biological sciences. It, however, often suffers from limitations such as weak signal and limited measurement time intrinsic to single-molecule fluorescence measurements. Despite several ameliorative measures taken to increase measurement time, it is nearly impossible to acquire meaningful kinetic information on a molecule if conformational transitions of the molecule are ultraslow such that transition times (⟨τ⟩_orig) are comparable to or longer than measurement times (<i>δt</i>) limited by the finite lifetime of fluorescent dye. Here, to extract a reliable and accurate mean transition time from a series of short time traces with ultraslow kinetics, we suggest a scheme called sHaRPer (serialized Handshaking Repeated Permutation with end removal) that concatenates multiple time traces. Because data acquisition frequency <i>f</i> and measurement time (<i>δt</i>) affect the estimation of mean transition time (⟨τ⟩), we provide mathematical criteria that <i>f</i>, <i>δt</i>, and ⟨τ⟩ should satisfy to make ⟨τ⟩ close enough to ⟨τ⟩_orig. Although application of the sHaRPer method has a potential risk of distorting the time constants of individual kinetic phases if the data are described with kinetic partitioning, we also provide criteria to avoid such distortion. Our sHaRPer method is a useful way to handle single-molecule data with slow transition kinetics. This study provides a practical guide to use sHaRPer

V-ATPase and osmotic imbalances activate endolysosomal LC3 lipidation

<div><p>Recently a noncanonical activity of autophagy proteins has been discovered that targets lipidation of microtubule-associated protein 1 light chain 3 (LC3) onto macroendocytic vacuoles, including macropinosomes, phagosomes, and entotic vacuoles. While this pathway is distinct from canonical autophagy, the mechanism of how these nonautophagic membranes are targeted for LC3 lipidation remains unclear. Here we present evidence that this pathway requires activity of the vacuolar-type H⁺-ATPase (V-ATPase) and is induced by osmotic imbalances within endolysosomal compartments. LC3 lipidation by this mechanism is induced by treatment of cells with the lysosomotropic agent chloroquine, and through exposure to the <i>Heliobacter pylori</i> pore-forming toxin VacA. These data add novel mechanistic insights into the regulation of noncanonical LC3 lipidation and its associated processes, including LC3-associated phagocytosis (LAP), and demonstrate that the widely and therapeutically used drug chloroquine, which is conventionally used to inhibit autophagy flux, is an inducer of LC3 lipidation.</p></div

Concentrations of different osteogenesis-related growth factors in AME and CME.

<p>(A) A table showing the relative concentrations of growth factors in AME and CME (picogram of growth factor/milligram of AME or CME). (B) Histograms showing the distribution of growth factor concentrations in the two membrane extracts from the 3 donors. Data are presented as the mean ± SD of 2 repeated experiments; *<i>p</i>< 0.05, Student’s t-test, indicates statistical significance.</p

Comparison of the osteogenic effect of different growth factors with that of CME.

<p>(A) MG-63 cells grown in OIM with or without various concentrations (1, 5 and 20 ng/mL) of bFGF, TGF β-1, EGF alone or their combination and CME (100–800 μg/mL). On day 9, Calcium concentration was compared by performing the calcium assay: F+T: bFGF + TGFβ-1, F+T+E: bFGF + TGFβ-1+ EGF. (B) MG-63 cells were cultured in OIM with or without high concentration of BMP2 (50–500 ng/mL), bFGF (50–500 ng/mL), and TGFβ-1 (50–500 ng/mL) alone or their combinations (bFGF + TGFβ-1 and bFGF + TGFβ-1+ BMP2) and CME (100–800 μg/mL). The cells were treated with the indicated concentrations of the growth factors and CME every 2–3 days and were cultured for 18 days. ECM mineralization was determined by performing Alizarin red S staining and by measuring the absorbance of solubilized Alizarin red S at 570 nm: F+T: bFGF + TGFβ-1, F+T+B: bFGF + TGFβ-1+ BMP2. Scale bars represent 100 μm. (C) Human MSCs were cultured in OIM with or without various concentrations (1 and 10 ng/mL) of bFGF, TGFβ-1, BMP2 and CME (100–400 μg/mL). ALP activity was measured at day 7. Data are presented as the mean ± SD of multiple repeated experiments; **<i>p</i>< 0.01 and ^#<i>p</i>< 0.001 versus OIM, indicates statistical significance.</p

EGF strongly suppressed the osteogenic effects of CME.

<p>(A) MG-63 cells were cultured in OIM with CME (400 μg/mL) and various concentrations of EGF (0.1–100 ng/mL). Calcium assay was performed after 7 days. *<i>p</i>< 0.05, **<i>p</i>< 0.01, and ^#<i>p</i>< 0.001 versus only CME. (B) MG-63 cells were cultured in OIM containing different concentrations of CME (100–800 μμg/mL) in the presence or absence of EGF (100 ng/mL). Mineralization rate was determined by performing Alizarin red S staining. **<i>p</i>< 0.01, Student’s t-test. (C) MG-63 cells were cultured in OIM containing 400 μg/mL CME with or without EGF (10 ng/mL). After 9 days, the cells were stained with Alizarin red S to determine mineralization. Scale bars represent 500 μm. Data are represented as mean ± SD of multiple repeated experiments.</p