Dose Response of TOR pathway GFP-fusion proteins in Saccharomyes cerevisiae specifically LAP4 based on MLPCN hits
kinase evolutionarily conserved from yeast to man [Wullschleger, et al. 2006]. TOR functions in two distinct protein complexes, TOR complex 1 (TORC1) and TORC2 [Cafferkey, et al. 1993; Stan, et al. 1994]. Curiously, only TOR in TORC1 is bound and inhibited by the lipophilic macrolide rapamycin [Kunz, et al. 1993; Helliwell, et al. 1998; Zhang, et al. 2006]. Although the signaling events up- and more ..
BioActive Compounds: 204
University of New Mexico Assay Overview:
Assay Support: 1R03 MH086450-01
Project Title: Chemical Screen of TOR pathway GFP fusion proteins in S. cerevisiae
PI: Maggie Werner-Washburn
Center PI: Larry Sklar
Assay Implementation: Jun Chen, Chris Allen, Susan Young, Anna Waller, Mark Carter
Assay Background and Significance:
The target of rapamycin, TOR, is a ser/thr protein
kinase evolutionarily conserved from yeast to man [Wullschleger, et al. 2006]. TOR functions in two distinct protein complexes, TOR complex 1 (TORC1) and TORC2 [Cafferkey, et al. 1993; Stan, et al. 1994]. Curiously, only TOR in TORC1 is bound and inhibited by the lipophilic macrolide rapamycin [Kunz, et al. 1993; Helliwell, et al. 1998; Zhang, et al. 2006]. Although the signaling events up- and downstream of TORC2 (which regulates spatial aspects of growth) have yet to be elucidated in detail, it is well established that TORC1 is a central hub of a signaling network that couples cues from hormones and growth factors (in mammalian cells), energy and stresses, and the abundance of nutrients, to cell growth and proliferation. Very recent work has elucidated many details of the signaling events upstream of TORC1 as well as downstream targets of TORC1. Importantly, in this context, most negative regulators of mammalian TORC1 (mTORC1)have been previously identified as tumor suppressor gene products, while many positive regulators of mTORC1 have been identified as proto-oncoproteins and/or are found at elevated levels in tumor-derived cell lines [De Virgilio, et al. 2006a; De Virgilio, et al. 2006b].
The purpose of this HTS screen is to identify small molecule modulators of protein targets in the pathway containing the target of rapamycin (TOR), a multi-protein complex (TORC1 and TORC2) that is highly conserved from yeast to man. The screen will detect structurally distinct, but functionally rapamycin-like compounds (rapalogs) by probing four major TOR pathways using the following targets in a multiplex format:
- RPL 19A: YAK kinase branch
- LAP4: MSN4 branch
- MEP2 and AGP1: GLN3 branch
- CIT2: RTG branch
Each of these target proteins (RPL 19A, LAP4, MEP2, AGP1, CIT2) are GFP (Green Fluorescent Protein) tagged, thus the expression of the proteins can be tracked by monitoring the GFP fluorescence.
Here we are reporting the results of dose response confirmation of the compounds found via primary screening.
The yeast cell-based multiplex assay is constructed using 5 strains from the Yeast-GFP Collection (Invitrogen, USA), representing 4 distinct branches of the TOR pathway: YAK Kinase, MSN4, GLN3 and RTG. Data were collected in single plex mode, meaning data from each individual strain were collected separately.
Similar to the primary screening campaign, the assay is performed in a total volume of 10.1 microliters in 384-well microtiter plates. The strains are grown separately overnight in synthetic complete liquid media in a shaking incubator at 30 degrees C. Then each individual yeast strain was diluted into fresh media at 0.2 OD600. Aliquots of the yeast are transferred into 384-well microtiter plates and hit compounds found from primary screen are added in dose response concentrations ranging from 0.001 to 33 microM, final concentration. The cells are incubated for 3 hours at 30 degrees C with end-over-end rotation. Control wells contain the yeast strain treated for 3 hours with 400nanogram/milliliter Rapamycin as a positive control and the yeast strain with an equal volume of DMSO as a solvent control. The cells are interrogated for GFP expression levels using established high-throughput flow cytometric methodologies at the UNMCMD. Sample analysis is conducted with the HyperCyt(R) (Intellicyt, USA) high throughput flow cytometry platform. The HyperCyt system interfaces a flow cytometer and autosampler for high-throughput microliter-volume sampling from 384-well microtiter plates [Kuckuck, et al. 2001]. Flow cytometric data are collected on a Cyan Flow Cytometer (Dako, USA).
Data analysis of the original flow cytometric data was done using HyperView (R) (Intellicyt, USA) software. The data are gated on forward scatter versus side scatter to distinguish the single yeast population. HyperView applies this gate and parses the time-resolved data file to produce annotated fluorescence summary data for each well, which are merges with compound worklist files generated by HyperSip(R) (Intellicyt, USA) software. The parsed data are then processed through an Excel (R) (Microsoft, USA) and Prism (R) (GraphPad, USA) template file constructed specifically for the assay to calculate the percent response.
Due to potential innate compound fluorescence, background fluorescence was collected by adding the compounds to the parental strain, s288c.
Calibration beads were used to convert the measured raw median channel fluorescence (MCF) to Molecules of Equivalent Soluble Fluorophores (MESF) by first assessing the linear correlation of the 5 different calibration bead levels of known MESF, then by using the following equation to convert the measured MCF:
kMESFSample = SlopeCalibration * RawMCFSample
where kMESFSample is kilo (1000) MESF from Sample and SlopeCalibration is the slope from linear fit of kMESF versus MCF of the calibration beads, and RawMCFSample is the raw MCF of the sample. By making the measurements standardized by the calibration beads, values of MCF collected from different machines could be compared.
To eliminate potential background fluorescence of the compound, the calculated kMESF from the parental, non-GFP expressing, strain, s288c, subtracted from the kMESFSample by the following equation:
SubkMESF = kMESFSample - kMESFs288c
These values of SubkMESF of the sample at different test concentrations were fitted by Prism(R) software (GraphPad Software, Inc., San Diego, CA) using nonlinear least-squares regression in a sigmoidal dose response model with variable slope, also known as the four parameter logistic equation:
SubkMESF = Min_SubkMESF + (Max_SubkMESF - Min_SubkMESF)/(1+10^((LogEC50 - LogConc)*Hillslope))
where LogConc is the log of the test compound concentration, and Min_ and Max_SubkMESF are the fitted estimates of minimum and maximum SubkMESF observed over the dose response. The fit statistics were used to determine the concentration of added test compound that effected GFP expression by 50 percent (EC50, microM) with 95% confidence intervals of the estimated EC50 value, Hillslope, and the correlation coefficient (r squared) indicative of goodness-of-fit.
PUBCHEM_ACTIVITY_SCORE were calculated based on an EC50 cutoff of 34 microM, by using the following equations:
SCORE = 100*(1-EC50/34)
And compounds were demeaned active if the EC50 is equal to or less than 33 microM.
* Activity Concentration. ** Test Concentration.
Data Table (Concise)