A novel image-based high-throughput screening assay discovers therapeutic candidates for adult polyglucosan body disease

Abstract

Glycogen storage disorders (GSDs) are caused by excessive accumulation of glycogen. Some GSDs [adult polyglucosan (PG) body disease (APBD), and Tarui and Lafora diseases] are caused by intracellular accumulation of insoluble inclusions, called PG bodies (PBs), which are chiefly composed of malconstructed glycogen. We developed an APBD patient skin fibroblast cell-based assay for PB identification, where the bodies are identified as amylase-resistant periodic acid-Schiff's-stained structures, and quantified. We screened the DIVERSet CL 10 084 compound library using this assay in high-throughput format and discovered 11 dose-dependent and 8 non-dose-dependent PB-reducing hits. Approximately 70% of the hits appear to act through reducing glycogen synthase (GS) activity, which can elongate glycogen chains and presumably promote PB generation. Some of these GS inhibiting hits were also computationally predicted to be similar to drugs interacting with the GS activator protein phosphatase 1. Our work paves the way to discovering medications for the treatment of PB-involving GSD, which are extremely severe or fatal disorders.

Keywords: APBD; glycogen storage disorders; glycogen synthase; image-based high-throughput screening; polyglucosans.

Figure 1. High Throughput Screening for compounds able to reduce PB

(A) Skin fibroblasts from an APBD (left) and control (middle) subjects and APBD subject treated overnight with 1 μM rapamycin (right) were formaldehyde-fixed, amylase digested, stained with Hoechst (blue) and PAS (red), and then imaged by the InCell 2000 High Content Analysis system. (B) Skin fibroblasts from healthy control and APBD patient were co-cultured in respectively 0:1, 1:3, 3:1 and 1:0 ratios. The cells were then stained with PAS and imaged as in (A). Representative images for the different patient cell co-culturing percentages and their quantification based on n=3 experiments are shown. (C) A representative image of cells showing the different stains employed (from left to right, as indicated in the figure, nuclear, PAS, Cell Mask and a merged image). (D) APBD patient derived fibroblasts were cultured for 24h in DMEM (with 5%FBS) and then 10,084 unique compounds from the DiverSet CL library (ChemBridge) were added to each different well at a concentration of 10μM. Following an additional 24h incubation, the cells were fixed, the fixative was neutralized, and the cells were then permeabilized, treated with diastase and stained with Hoechst 33342, Cell Mask Deep Red and PAS. Images were then acquired and analyzed. Each well mean of cell area (based on Cell Mask Deep Red staining) was normalized by z-scores according to the population mean of all the compounds. Compounds showing a toxic effect were discarded by keeping only those showing a z-score higher than −1.5 for their normalized cell area mean and more than 300 cells per well. Once this selection was made, the hits were selected based on the normalized PG mean intensity. Those compounds inducing a well-based PG mean intensity below −1.2 z-score were selected as hits. Thus, from 10,084 compounds screened, 85 were selected as hits. These selected compounds were subjected to the same assay once again employing concentrations of 0, 1, 5, 10 and 50μM. These dose response experiments narrowed down the 85 selected hits to 11 in which a concentration dependent decrease of cell associated PG mean intensity has been demonstrated.

Figure 2. Dose response of PB reducing hits

(A) Box plots depicting for each of the 11 concentration dependent hits discovered the effect of concentration on diastase resistant, cell associated, mean PAS intensity, normalized by z-score. Arrowheads, Median PAS intensity. The yellow boxes delineate upper and lower quartiles from the median, and upper and lower “whiskers” respectively show maximal and minimal mean PAS intensity values. Red dots, denote outliers which are values at least 1.5×(interquartile range (75th percentile – 25th percentile)) above or below the box. (B) PAS staining images taken as in Fig. 1, demonstrating hit toxicity to cells in concentrations above 50 μM. Exemplary images for hits 5 and 7 are shown. (C) Dose-response (DR) curves of the 11 concentration dependent hits discovered. Shown are DR curves of diastase resistant cell associated mean PAS intensities normalized by z-score. The zero concentration is excluded in all curves, as the concentrations are drawn in a log scale. Shown at the bottom are the EC50 and R² data for the 11 hits.

Figure 2. Dose response of PB reducing hits

(A) Box plots depicting for each of the 11 concentration dependent hits discovered the effect of concentration on diastase resistant, cell associated, mean PAS intensity, normalized by z-score. Arrowheads, Median PAS intensity. The yellow boxes delineate upper and lower quartiles from the median, and upper and lower “whiskers” respectively show maximal and minimal mean PAS intensity values. Red dots, denote outliers which are values at least 1.5×(interquartile range (75th percentile – 25th percentile)) above or below the box. (B) PAS staining images taken as in Fig. 1, demonstrating hit toxicity to cells in concentrations above 50 μM. Exemplary images for hits 5 and 7 are shown. (C) Dose-response (DR) curves of the 11 concentration dependent hits discovered. Shown are DR curves of diastase resistant cell associated mean PAS intensities normalized by z-score. The zero concentration is excluded in all curves, as the concentrations are drawn in a log scale. Shown at the bottom are the EC50 and R² data for the 11 hits.

Figure 3. Non dose-responding PB reducing hits

(A) and (C) Data for hits which lowered mean normalized PAS intensity in a non-dose responding manner are presented as in Fig. 2 (A) and (C) respectively. (B) Demonstration of toxicity above 50 μM, as in Fig. 2(B), for representative hit number 14.

Figure 3. Non dose-responding PB reducing hits

(A) and (C) Data for hits which lowered mean normalized PAS intensity in a non-dose responding manner are presented as in Fig. 2 (A) and (C) respectively. (B) Demonstration of toxicity above 50 μM, as in Fig. 2(B), for representative hit number 14.

Figure 4. Hit effect on GS activity

(A) An in vitro GS enzyme activity assay (see Materials and Methods) was performed in order to test the effect of the 19 hits discovered on GS activity. Each hit compound was used at a final concentration of 50 μM. UDP serves as a positive control for reduction of GS activity. All hits, except for #10, have significantly changed GS activity with #6, 7, 8, 12, 18 and 19 increasing and the rest decreasing it (n = 3 experiments, p < 0.05, one-way ANOVA with Dunnett post-hoc test). See Table 1 for compounds names and molecular structures. (B) Dose response curves of the effect of the compounds on GS activity. Compound concentrations used are 3.125, 6.25, 12.5, 25, 50, 100, 200, 400, and 800 μM. Shown are also goodness of fit (R-square) and estimated EC50 values.

Figure 4. Hit effect on GS activity

(A) An in vitro GS enzyme activity assay (see Materials and Methods) was performed in order to test the effect of the 19 hits discovered on GS activity. Each hit compound was used at a final concentration of 50 μM. UDP serves as a positive control for reduction of GS activity. All hits, except for #10, have significantly changed GS activity with #6, 7, 8, 12, 18 and 19 increasing and the rest decreasing it (n = 3 experiments, p < 0.05, one-way ANOVA with Dunnett post-hoc test). See Table 1 for compounds names and molecular structures. (B) Dose response curves of the effect of the compounds on GS activity. Compound concentrations used are 3.125, 6.25, 12.5, 25, 50, 100, 200, 400, and 800 μM. Shown are also goodness of fit (R-square) and estimated EC50 values.

Figure 5. Protein targets of the hits

(A) An interactome of the predicted protein targets of the 36 discovered hits (including tautomers and protonation states). Small yellow circles, hit protein targets; large yellow circles, hit interacting proteins which serve as hubs for protein interaction; red circles, protein targets of the hits known to interact with drugs; blue lines, protein-protein interactions; red arrows, regulatory interactions. See http://www.unihi.org/ for names and descriptions of gene symbols shown (B) An interactome of the subsection of hit-protein targets known to bind drugs and predicted to bind carbohydrate derivatives (red circles in (A)).

Figure 5. Protein targets of the hits

(A) An interactome of the predicted protein targets of the 36 discovered hits (including tautomers and protonation states). Small yellow circles, hit protein targets; large yellow circles, hit interacting proteins which serve as hubs for protein interaction; red circles, protein targets of the hits known to interact with drugs; blue lines, protein-protein interactions; red arrows, regulatory interactions. See http://www.unihi.org/ for names and descriptions of gene symbols shown (B) An interactome of the subsection of hit-protein targets known to bind drugs and predicted to bind carbohydrate derivatives (red circles in (A)).

Figure 6. Effect on PB of known drugs clustered with the hits

Skin fibroblasts from an APBD subject were treated overnight with 1 μM DMSO, Pimecrolimus, or Tacrolimus as indicated, formaldehyde-fixed, amylase digested, stained with Hoechst (blue) and PAS (red), and then imaged.