Benchmarking a high throughput single molecule tracking platform

a) Diffusion state probability distributions from three cell lines expressing Histone H2B-Halo, Halo-CaaX, or Halo alone. Shaded bins represent the diffusive states characteristic of each cell line.

b) Example field of view. Equal mixture of H2B-Halo, Halo-CaaX and free Halo cell line single molecule images (top) and reference Hoechst image (bottom). Insets show zoom-ins to individual cells and to sequen-tial frames of individual molecules. Image intensities are equivalently scaled across panels.

c) Single-cell diffusive states extracted from (c), colored based on similarity to the H2B-, CaaX-, or free-Halo dynamics reported in (b).

d) Heatmap representation of 103757 cell nuclei measured from a mixture of Halo-H2B, Halo-CaaX, or Free Halo mixed within each well over 1540 unique wells in five 384-well plates. Each horizontal line represents a nucleus. Cells were clustered using k-means clustering and labels assigned based on the diffusive profiles determined in (b).

e) Ensemble state occupation of all trajectories recovered from a mixture of Halo-H2B, Halo-CaaX, free Halo cells.

Chromatin binding by steroid hormone receptors is affected by compound treatment

a) Distribution of diffusive states for Halo-AR, Halo-ER, Halo-GR, and Halo-PR in U2OS cells before and after stimulation with an activating ligand. The area in the shaded region is fbound. Shaded error bands represent S.D.

b) Selectivity of individual SHRs to their cognate ligand compared with other steroids, as determined by fbound Error bars represent SEM.

Bioactive screen results of change in estrogen receptor fbound for two biological replicates of 5067 compounds.

Select inhibitors are grouped and uniquely colored by pathway or target. Error bars are SEM.

Selective ER modulators and degraders induce DNA binding measurable through htSMT

a) Diffusion state probability distribution for ER treated with 100 nM of exemplified SERMs and SERDs. Shaded regions represent the S.D.

b) Change in fbound as a function of a 12-pt dose titration of fulvestrant (5), 4-OHT (6), GDC-0810 (8), AZD9496 (9), or GDC-0927 (10) with fitted curve. Compounds colored as in (a). Error bars represent the SEM of three replicates.

c) Change in fbound as a function of time after agonist or antagonist addition, fitted with a single exponential. Compounds colored as in (a). Estradiol (1, green) and DMSO added for comparison. Error bars represent SEM.

d) Maximum effect of SERMs and SERDs on fbound . Each box represents quartiles while whiskers denote the 5-95th percentiles of single well measurements, measured over a minimum of four days with at least 8 wells per compound per day.

e) Fluorescence Recovery After Photobleaching of ER-Halo cells, treated either with DMSO alone or with 100 nM SERM/D. Curves are the mean ± SEM for 18-24 cells, colored as in (a). Error bands represent SEM.

f) Quantification of FRAP recovery curves to measure recovery 2 minutes after photobleaching. Whiskers denote the 5-95th percentiles of single cell measurements.

g) Quantification long-lived tracks, each point representing the fraction of trajectories greater than 10 seconds for a single biological replicate consisting of 3-10 wells per condition. Dashed line represents the median fraction of trajectories lasting longer than 10 sec for Histone H2B-Halo, which is the upper limit of measurement sensitivity.

htSMT can be used to determine chemical structure-activity relationships

a) Correlation of potency measured by ER degradation and cell proliferation in MCF7 cells (black) and T47d cells (magenta) for compounds in the GDC-0927 structural series.

b) Change in fbound across a 12-pt dose titration of compounds 11 through 16, colored by structure. Points are the mean ± SEM across three biological replicates.

c) Correlation of potency measured by change in fbound and cell proliferation in MCF7 cells (black) and T47d cells (magenta) for compounds in the GDC-0927 structural series.

Bioactive molecules targeting pathways associated with ER affect its dynamics

a) Bioactive screen results with select inhibitors grouped and uniquely colored by pathway. Change in fbound across a 12-pt dose titration of three representative compounds targeting each of HSP90, mTOR, CDK9 and the proteasome. Individual molecules are denoted by specific shapes. Error bars represent SEM.

b) Change in fbound as a function of time after compound addition. Estradiol treatment (black) is compared to ganetespib (blue circles) and HSP990 (blue squares). Points are bins of 4 minutes. Error bars represent SEM.

c) Change in fboundas a function of time after compound addition. Estradiol treatment (black) is compared to HSP90 inhibitors ganetespib (blue circles) and HSP990 (blue squares); proteasome inhibitors bortezomib (red circles) and carfilzomib (red squares). Points are bins of 7.5 minutes of htSMT data, marking the mean ± SEM. The shaded region denotes the window of time used during htSMT screening.

d) Track length survival curve of ER-Halo cells treated either with DMSO alone, with estradiol stimulation, or with 100 nM HSP90 or proteasome inhibition. Track survival is plotted as the 1-CDF of the track length distribution; faster decay means shorter binding times.

e) Quantification of the number of long-lived trajectories as a function of treatment condition. All conditions were normalized to the median number of trajectories in DMSO.

f) Diagram summarizing pathway interactions based on htSMT results for ER, AR, and PR.

Characterization of htSMT system performance.

a) Distribution of localization error measured across multiple independent wells using Histone H2B-Halo cells. Median localization error of 39 nm.

b) Number of measurable nuclei in a 94 by 94 µm FOV. Each box plot is the distribution over wells in one 384-well plate.

c) Cumulative number of trajectories as a function of imaging time for each individual cell type for cells labeled with 10 pM JF549. Shaded error bars are 1 S.D.

Activation of steroid hormone receptors changes free diffusion and impacts downstream gene expression.

a) Cartoon illustration of SHR function. Under basal conditions, SHRs are sequestered in complex with HSP90 and other cofactors. Upon ligand binding, the receptor dissociates from the inactive complex, dimerizes, and binds to DNA.

b) mRNA transcript levels in log(FPKM) of AR, ESR1, PR, and NR3C1 for the engineered U2OS cell lines compared to the parental U2OS line as well as three reference breast cancer cell lines.

c) Distribution of diffusive states for Halo-AR, Halo-ER, Halo-GR, and Halo-PR in U2OS cells before and after stimulation with an activating ligand. Arrows indicate the mean Dfree. Shaded error bands represent 1 S.D.

d) Selectivity of individual SHRs to their cognate ligand compared with other steroids, as determined by Dfree. Error bars represent SEM.

e) Reference gene sets induced after 24 hrs of stimulation with 25 nM estradiol. The top five induced gene sets for Halo-ER ectopic expression increases were not significantly induced in the parental U2OS line.

f) Bar plot showing the -log(q value) from the top 50 most significantly induced gene sets after estradiol stimulation. Gene sets characteristic of ESR1 or the estrogen response are colored green.

Screen of bioactive molecules produces robust data with good assay performance.

a) Cumulative number of trajectories as a function of imaging time for DMSO-treated cells labeled with 20 pM JF549. Shaded error bars are 1 S.D.

b) Change in fbound repeatability of screening results assessed over two biological replicates. Compounds in magenta were identified as active if their magnitude of change in fbound when averaged across both replicates was greater than 0.05. Of the expected 30 positive control compounds, 26 significantly increased fbound in both replicates (gray outline). Three compounds increased fbound but were only present in one replicate after filtering. Exemplified positive controls including the agonist estradiol (1) and the antagonists fulvestrant (5), 4-OHT (6) and bazedoxifene (7) are exemplified. A linear regression was fit to the magenta compounds to determine slope and correlation.

c) Z’-factor analysis for the bioactive screen. Each point represents the Z’-factor of a single 384-well plate, measuring the difference between DMSO and 25 nM estradiol treatment. Plates with very low Z’-factors were removed from further analysis.

d) Dose titration of estradiol for each plate in the bioactive molecules screen fit with a logistic regression to determine potency.

e) EC50 values extracted from each curve fit in (c). Shaded region is a three-fold range in potency.

f) Distribution of change in fbound for control DMSO wells.

g) Boxplot showing the number of cell nuclei measured for each compound tested. Whiskers are the 1st and 99th percentiles.

h) Change in fbound for 30 known ER-interaction molecules circled in (b), ordered by the magnitude of effect. Error bars are the SEM.

Antagonists of ER (a), PR (b), AR (c) and GR(d) show distinct effects on target protein dynamics.

Change in fbound after addition of 1 µM antagonist either in the absence or presence of the cognate agonist.

SERMs and SERDs decrease free diffusion and increase fbound rapidly after addition.

a) Normalized occupation of diffusive states (diffusion coefficient 0.2 – 100 µm2/sec) for 100 nM SERD or SERM-treated samples compared with DMSO. Histograms are normalized to integrate to 1. Shaded regions represent bin-wise standard deviations. Curves are the average of 3-4 biological replicates, with 8 well replicates per condition (>1200 cells total)

b) Results from a single-exponential association fit to the data in Figure 4C.

c) Change in diffusive state distribution as a function of time after compound addition for estradiol and fulvestrant. Each curve represents the mean of three biological replicates. Shaded regions are the bin-wise standard deviation.

d) Change in fbound of selective AR or GR antagonists from the bioactive screening set.

e) Track length survival curve of ER-Halo cells treated either with DMSO alone or with SERM/D. Track survival is plotted as the 1-CDF of the trajectory length distribution; faster decay means shorter binding times.

f) Table of results of the slow decay rate constant (kslow) from residence time SMT curve fits. Fits were performed on the aggregate of three biological replicates. Taken together with the fbound determined in 4D, an upper limit of the inferred kon can be calculated from the equation assuming all bound molecules will have k* = kslow. Cells marked with an asterisk are ones in which kslow could not reliably be distinguished from photobleaching.

GDC-0927 structural variants characterized by ER degradation or cell proliferation assays.

a) Western blot of the ER-expressing breast cancer cell lines MCF7 and T47d compared to ER expression in ER-null lines SK-BR-3 or U2OS. Samples were treated with fulvestrant for 24 hours prior to lysis. Fulvestrant treatment leads to the degradation of ER, even when fused to HaloTag.

b) Example of GDC-0927 induced degradation of ER in different cell lines measured by immunofluorescence against ER. Cells were exposed to compound for 24 hours prior to fixation. Image pixel intensities are equivalently scaled.

c) Example compound dose titrations showing change in mean nuclear intensity as a function of compound concentration.

d) Example compound dose titrations measuring cell proliferation, normalized to DMSO-treated cells, of cells treated with analogs of GDC-0927.

Deeper investigation of bioactive screening data identifies cutoff for active molecules.

a) Examples of compound effects on ER fbound from a dose titration experiment. 92 compounds from the primary screen are ranked based on the magnitude of their effect. Compounds colored in black repeatably showed dose-dependent changes; magenta compounds were inactive in a dose titration.

b) Example dose titration of compounds of increasing overall change in ER fbound.

c) Two replicates of the bioactive screen as in Figure 3. Active compounds are colored based on structural scaffold.

d) A quantification of the number of compounds associated with any given cluster. Singletons (cluster 21) represent the majority of active compounds.

Some pathway inhibitors modulating ER dynamics are specific to ER.

a) Change in fbound of ER following treatment with inhibitors of HSP90, the proteasome, mTOR, and CDK from the initial bioactive screen. CDK inhibitors were further stratified into CDK4/6 inhibitors, CDK9 inhibitors, or inhibitors without strong selectivity for a particular family (pan-CDK). Line represents the median for each target.

b) Change in fbound of ER for 97 bioactive molecules, colored by their pathway annotation. Compounds are plotted in their rank order based on their effect in ER. Error bars are the SEM of three biological replicates.

c) Change in fbound of AR for the same molecules from (b). Compounds are plotted in their rank order based on their effect in ER. Error bars are the SEM of three biological replicates.

d) Change in fbound of PR for the same molecules from (b). Compounds are plotted in their rank order based on their effect in ER. Error bars are the SEM of three biological replicates.

Dose titration plots of ER(S104A/S106A/S118A) with mTOR and CDK9 compounds.

Each point represents the mean and SEM of three biological replicates.