MLPCN PGC1a Modulators Measured in Cell-Based System Using Plate Reader - 2139-01_Activator_Dose_CherryPick_Activity_Set6
Keywords: GCN5,flag PGC1a adenovirus, acetyl transferase, SIRT1 deacetylase, Alphascreen, acetylation, inflammation, diabetes ..more
BioActive Compounds: 483
Keywords: GCN5,flag PGC1a adenovirus, acetyl transferase, SIRT1 deacetylase, Alphascreen, acetylation, inflammation, diabetes
Assay Overview: The close relationship between PGC-1a acetylation and metabolic diseases suggests the possibility the discovery of chemical probes that manipulate the acetylation level would introduce new therapeutic applications in those diseases. Our primary goal is to discover chemical compounds that can modulate PGC1a acetylation levels to protect against age-associated diseases including metabolic disorders (Inhibitors) and hyperglycemia associated with Type 2 diabetes (Activators). In this project we use a homogeneous, whole cell lysate, AlphaLISA assay to measure PGC1a acetylation levels. The cell system is infected with flag PGC1a adenovirus and GCN5 acetyl transferase virus. The acetylation state of PGC1a is measured using a rabbit anti-acetylated lysine antibody, anti-rabbit Alpha-LISA donor bead and anti-flag Alpha-LISA acceptor bead. This assay is capable of measuring both increases and decreases in the PGC1a acetylation levels. Decreases in PGC1a acetylation can be the result of inhibiting GCN5 acetyl transferase or stimulating de-acetylation through deacetylases such as SirT1. This mimics the effects of exercise and caloric restriction. These compounds are found in the PGC1a inhibitor screen. Increases in hepatic PGC1a acetylation levels can suppress glucose production and ameliorate the hyperglycemia associated with Type 2 diabetes. These compounds are found in the PGC1a activator screen.
Expected Outcome: The identification of chemical probes capable of mimicking calorie restriction and exercise by reducing PGC-1a acetylation (Inhibitors), with the long-term goal of developing treatments for diseases in which PGC-1a is dysregulated, including diabetes, other metabolic disorders, neuromuscular diseases and sarcopenia. Identification of chemical probes that increase PGC1a acetylation levels (Activators) are expected to be long-term treatments for improving hyperglycemia associated with type 2 diabetes. An increase in signal with this assay represents a PGC1a activator which results in increased acetylation. A decrease in signal with this assay represents an inhibitor of PGC1a acetylation. Additional counter screens will be performed to remove Alpha-LISA artifacts and cytotoxic compounds.
1.Thaw 6 vials U2OS cells into 4 triple flasks with growth media. Grow for 48hrs. Harvest and seed 4 Hyper flasks @ 15-20M cells ea. Grow 4-5 days until near/at confluence.
2.Change to assay media and infect with flag PGC1a adenovirus and GCN5 viruses . Incubate 4hrs. Replace media with Phenol Red free medium and incubate overnight.
3.Harvest , count, and plate cells @7000 cell/well in 50 uL assay media in 384 well plates.
4.Incubate @ 37 degrees c 4-8 hrs for cells to adhere.
5.Pin 100nl compound, continue incubation overnight.
6.Aspirate media and add 6ul of Lysis buffer,* incubate 1hr @ r.t.
7.Add 6ul of anti-acetyl Lysine Ab, incubate 1hr @ r.t.
8.Add 6ul of Alpha Acceptor beads, incubate 1hr @ r.t.
9.Add 6ul of Alpha Donor beads, incubate 1hr @ r.t
10.Read on Envision using ALPHA protocol.
PRESENCE OF CONTROLS: Neutral control wells (NC) and positive control wells (PC) were included on every plate.
EXPECTED OUTCOME: Active compounds result in increasing readout signal.
The compounds were assayed in multiple independent instances using an identical protocol; each instance is called a 'test'. For each test, the following analysis was applied:
ACTIVE CONCENTRATION LIMIT:
For each sample, the highest valid tested concentration (Max_Concentration) was determined and the active concentration limit (AC_limit) was set to equal Max_Concentration.
The raw signals of the plate wells were normalized using the 'Neutral Controls Minus Inhibitors' method in Genedata Assay Analyzer (v10.0.2):
The median raw signal of the intraplate neutral control wells was set to a normalized activity value of 0.
The median raw signal of the intraplate positive control wells was set to a normalized activity value of -100.
Experimental wells values were scaled to this range.
PATTERN CORRECTION: No plate pattern correction algorithm from Genedata Condoseo (v.10.0.2) was applied.
MEASUREMENT USED TO DETERMINE ACTIVE CONCENTRATION (AC): absACnn, the concentration at which the curve crosses threshold 40
AC values were calculated using the curve fitting strategies in Genedata Screener Condoseo (7.0.3).
AC values were calculated up to the active concentration limit described for each sample.
pAC was set to equal -1*log10(AC)
Activity_Outcome = 1 (inactive) when:
a) compound shows activity but in a direction opposite to the expected outcome
in these cases, values describing curve fitting parameters (Sinf, S0, Hill Slope, log_AC50, log_AC50_SE) are set to null
b) curve fit is constant where activity is > -30% and < 30% at all tested concentrations, or
c) AC > AC_limit
Activity_Outcome = 2 (active) when:
AC <= AC_limit
Activity_Outcome = 3 (inconclusive) when:
a) Curve fitting strategy resulted in a constant fit with activity >= 30% but <= 70%, or
b) The fit was deemed not valid due to poor fit quality.
If PUBCHEM_ACTIVITY_OUTCOME = 1 (inactive) or 3 (inconclusive),
then PUBCHEM_ACTIVITY_SCORE = 0
If PUBCHEM_ACTIVITY_OUTCOME = 2 (active)
then PUBCHEM_ACTIVITY_SCORE = (10)(pAC)
Scores relate to AC in this manner:
120 = 1 pM
90 = 1 nM
60 = 1 uM
30 = 1 mM
0 = 1 M
When the active concentration (AC) is calculated to be greater than the highest valid tested concentration (Max_Concentration), the PUBCHEM_ACTIVITY_SCORE is calculated using Max_Concentration as the basis.
When the active concentration (AC) is calculated to be less than the lowest tested concentration, the PUBCHEM_ACTIVITY_SCORE is calculated using the lowest tested concentration as the basis.
Once the data for each test was processed, the test number was appended to all column headers in that test's data set. The individual test results were then aggregated as follows:
1. The final PUBCHEM_ACTIVITY_OUTCOME was set to:
a. '2' (active) when all test outcomes were '2' (active), or
b. '1' (inactive) when all test outcomes were '1' (inactive), or
c. '3' (inconclusive) when the test outcomes were mixed.
2. The final ACTIVE_CONCENTRATION (AC) was set as follows:
a. If the final PUBCHEM_ACTIVITY_OUTCOME = 2, AC was set as the mean of the constituent test active concentrations;
b. If the final PUBCHEM_ACTIVITY_OUTCOME = 1 or 3, AC was left empty.
3. The final PUBCHEM_ACTIVITY_SCORE was calculated based on the aggregated ACTIVE_CONCENTRATION, using the same logic described above for individual test scores.
The individual dose data point columns ('Activity_at_xxuM') reported here represent the median of valid (unmasked) replicate observations at each concentration. These values are the inputs to a curve fitting algorithm.
All other data columns represent values which are derived during the curve fitting algorithm; this may sometimes include automatic further masking of some replicate data points.
Occasionally this results in perceived inconsistencies: for example, between the derived 'Maximal_Activity' and the apparent most active data point.
Categorized Comment - additional comments and annotations
* Activity Concentration. ** Test Concentration.
Data Table (Concise)