Role of PCSKs in inhibin subunit cleavage.

<p>(A) Expression of the wild type inhibin α-subunit (RARR) or the α-subunit with modified cleavage recognition sites (RARA and RAAA) in HEK 293 cells. Culture media were examined by immunoblot analysis under reducing conditions using an anti-inhibin α-subunit antibody. Processing of the inhibin β_B-subunit (B) and inhibin α-subunit (C) by proconvertases. LoVo cells were transiently transfected with expression plasmids for furin, PC5/6A, PC5/6B, Pace4 and PC7. Media from cells was TCA-precipitated, separated by SDS-PAGE under reducing conditions and examined by immunoblot analysis. The corresponding % of band intensities were deduced from the ratio of (β_B)/(pro-β_B+β_B) for the β_B-subunit; or (αC)/(pro-αN-αC+αC) for the α-subunit. Results are representative of two independent experiments.</p

Expression levels of inhibin subunits and PCSKs in primary cultures of mouse granulosa cells and GRM02 cells.

<p>Following RNA extraction from both cell types, real time PCR analysis was performed using specific primers to the inhibin subunits (A) and the PCSK enzymes (B). Results are shown in the bar graph and are expressed as a ratio relative to the GAPDH control gene. Data are shown as mean ± SEM of three independent experiments. (C) Proconvertase enzymes are necessary for processing of inhibin subunits. GRMO2 cells were cultured for 48 h in the presence of the proconvertase inhibitor dec-RVRK-CMK (CMK). TCA-precipitated media was separated by SDS-PAGE under reducing conditions and imunoblotted using an anti-inhibin β_A-subunit antibody, (D) anti-inhibin β_B-subunit antibody or (E) anti-inhibin α-subunit antibody. The results are representative of three independent experiments.</p

Expression levels of PCSKs in mechanically isolated mouse follicles.

<p>The mRNA levels of furin (A), PCSK5 (B), PCSK6 (C) and PCSK7 (D) subunits were measured using real-time RT-PCR and are shown as a ratio over the 50–100 micron follicle levels. The bars labeled with different letters indicate statistically significant differences, as determined by Tukey's multiple comparison test (p<0.05).</p

mRNA transcript levels of inhibin subunits and PCSKs in activin-treated <i>in vitro</i> cultured mouse follicles.

<p>Secondary follicles (100–130 microns) were mechanically isolated and cultured in alginate supplemented with activin A or activin B (50 ng/ml) for 4 days. (A) mRNA levels of the inhibin α-, β_A- and β_B-subunits. (B) Follicle diameter was measured in each treatment group after the 4-day culture period. A statistically significant difference in follicle diameter was noted in the presence of activin A, but not activin B. (C) mRNA levels of the PCSKs in each treatment group. Bars labeled with different letters indicate statistically significant differences, as determined by Tukey's multiple comparison test (p<0.05). *, PSCK7 mRNA transcripts could not be detected by real-time RT-PCR.</p

Expression of inhibin α-, β_A- and β_B-subunits in the postnatal mouse ovary.

<p>Basal expression levels of inhibin α- (A), β_A- (B) and β_B- (C) subunits in developing mouse ovaries were determined by real-time RT-PCR. The mRNA levels of the subunits are shown as a ratio over the day 2 ovary mRNA levels (control). Detection of the inhibin α- (D), β_A- (E) and β_B- (F) subunit protein in ovarian lysates from day 6, day 10 and day 19 ovaries. Ovarian lysates were collected, separated under reducing conditions; each subunit was detected by immunoblotting with the corresponding rabbit polyclonal antibody. Forty µg of protein was loaded per lane. Equal loading of lysates was confirmed with an anti-actin antibody.</p

Expression levels of inhibin α-, β_A- and β_B-subunits in mechanically isolated mouse follicles.

<p>Follicles were dissected and grouped by size as described in the <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0017348#s2" target="_blank">Materials and Methods</a>. The mRNA levels of the α- (A), β_A- (B) and β_B- (C) subunits were measured using real-time RT-PCR and are shown as a ratio over the 50–100 micron follicle group levels (control). The bars labeled with different letters indicate statistically significant differences, as determined by Tukey's multiple comparison test (p<0.05).</p

Virtual High-Throughput Screening To Identify Novel Activin Antagonists

Activin belongs to the TGFβ superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin βA subunits and was used for a virtual high-throughput in silico screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSHβ transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex’s binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGFβ superfamily member myostatin (GDF8). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonists. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGFβ receptor superfamily members. in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases

Virtual High-Throughput Screening To Identify Novel Activin Antagonists

Activin belongs to the TGFβ superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin βA subunits and was used for a virtual high-throughput in silico screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSHβ transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex’s binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGFβ superfamily member myostatin (GDF8). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonists. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGFβ receptor superfamily members. in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases

Career lengths of faculty members.

<p>Career length distribution of female (red) and male (blue) current faculty members for a selected set of U.S. universities (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051332#pone-0051332-t001" target="_blank">Table 1</a>). Data is binned into two year intervals. Currently, females hold about 16% of faculty positions in chemistry and in material science departments, and about 25% of faculty positions in molecular biology departments.</p

Lower publication rates of female faculty is correlated with higher requirements for research resources.

<p>Effects of the magnitude of the resource requirements on the difference in publication rates between genders. Ecology is not included as we could not obtain data for resource requirements. The difference in publication rates is measured by the average z-score of number of publications by females in each year, and the error bars indicate the standard errors. The resource requirements is defined as the average annual research expenditure per principal investigator in the departments studied (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051332#pone-0051332-t002" target="_blank">Table 2</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0051332#pone.0051332-National1" target="_blank">[40]</a>). The trend line (black dashed line) indicates a negative correlation (coefficient of determination ). These data suggest that higher resource requirements lead to greater differences in the publication rates between females and their male peers.</p