A robotic platform for quantitative high-throughput screening

Abstract

High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1,536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently developed quantitative HTS (qHTS) paradigm, which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay. The practical implementation of qHTS for cell-based and biochemical assays across libraries of > 100,000 compounds (e.g., between 700,000 and 2,000,000 sample wells tested) requires maximal efficiency and miniaturization and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully integrated and automated screening system for qHTS at the National Institutes of Health's Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has led to the generation of over 6 million CRCs from > 120 assays in the last 3 years and is a technology that can be widely implemented to increase efficiency of screening and lead generation.

FIG. 1.

NCGC assay portfolio during the 2005–2007 period. Breakdown charts include (A) disease areas represented, (B) target types screened, and (C) the detection methods utilized. GPCR, G-protein coupled receptor; PPI, protein-protein interaction.

FIG. 2.

(A) System components and (B) controls. I/O, input/output; DB, database; LIMS, Library Information Management System.

FIG. 3.

(Right panels) Plate (A) lid and (B) gripper. (Left panels) Highlighted from U.S. Patents 6,534,014 and 6,592,324, respectively, are the plate lid and its flexible rubber seal and the plate gripper with its special groove designed for secure plate grasping and transport.

FIG. 4.

Examples of validation data. (A) Plate activity heatmaps of an eight-concentration LOPAC screen repeated three times. Concentrations are shown from lowest to highest. Each plate contains an intra-plate control titration. (B) Activity of validation run shows samples identified as inhibitors (blue), activators (red), or inactives (gray); control titration (green) presents as near-overlapping curves indicating excellent assay stability and reproducibility (control 50% inhibitory concentration = 2 μM, control MSR = 1.9). (C) An example of three different compounds showing excellent triplicate CRC reproducibility: samples A(1) (▪), A(2) (▴), A(3) (▾), B(1) (♦), B(2) (•), B(3) (□), C(1) (▵), C(2) (▿), and C(3) (◊).

FIG. 5.

Implementation of kinetic assay (▪). In enzyme assays associated with minimal or noisy signal changes (due to dim fluorophore or otherwise unfavorable assay chemistry or enzymology), the end-point method (▴) may simply preclude the use of these assays in HTS (concentration–response plot using raw signals in [A]). The boost in S:B afforded by performing kinetic measurement and computing the activity using the change in signal (concentration–response plot using normalized signals in [B]) transforms many of these weak signal systems into screenable assays. RFU, relative fluorescent units.

FIG. 6.

“Busy screen.” The multiple dispense, incubation, and read steps are indicated on the Spotfire (TIBCO Software, Somerville, MA) plots: Dispense (), Incubate (), Read (), Read2 (), Read3 (), and Transfer (). The order and timing of all protocol steps remained stable throughout the screen, as evidenced from the near-identical snapshots obtained from six (A) early and (B) late screening plates.

FIG. 7.

Use of the Kalypsys angled-head dispenser. (Left panel) The array of eight tip dispensers for the straight head (1) and the angled head (2). (Right panels) Images from the whole-well scan of a 1,536-well plate obtained on the Acumen Explorer using GeneBLAzer M1 receptor/nuclear factor of activated T-cells-β-lactamase expressed in Jurkat cells, a cell line grown in suspension. Reagents were dispensed with either (top panel) a straight head or (bottom panel) the angled head. Cells were plated at a density of 750 cells per well. Cell clumps are shown in dark gray, while individual cells included in the cell population are light blue or green depending on the level of β-lactamase expression. (Top panel) Reagent addition to wells at 90° by the Bio-RAPTR FRD causes suspension cells to move to the sides of the well and clump together. High content data analysis that relies on defining individual cells thus becomes difficult, as fewer individual cells are counted. (Bottom panel) Addition of reagents with the Kalypsys angled-head dispenser does not cause significant movement of suspension cells within the well, as reagent is dispensed at an angle at which fluid hits the side of the well and runs down to the bottom. Cells, therefore, remain dispersed throughout the well volume and show significantly less clumping, providing a significantly higher number of individual cells to be analyzed and counted.

FIG. 8.

Effect of cytometer scan resolution on CRC determination. A 1,536-well plate assay for glucocorticoid receptor nuclear translocation was performed by fixing U2OS cells and staining nuclei with propidium iodide. The amount of GFP signal within the nucleus was then measured on the Acumen laser cytometer. Representative images of untreated U2OS cells stained for nuclei (left panels) (red is the propidium iodide channel) or cells (middle panels) (green is the GFP channel; red is the propidium iodide channel) are shown with CRC data (right panels) obtained when scanned at either (A) 1 × 0.5 μm or (B) 1 × 8 μm resolution.

FIG. 9.

Reproducibility of the qHTS process on the Kalypsys robotic system. (Left panel) 3D-scatter plot with CRC fits shown for samples assayed in the pyruvate kinase-luciferase coupled assay. CRCs are annotated by curve fit quality as described in Inglese et al. (Right panel) Bland-Altman plot comparing the pAC₅₀ values from a pyruvate kinase-luciferase-coupled biochemical assay performed in September 2005 and again in March 2007. Separate copies of the chemical library were obtained, titrated, and stored on the robotic system in each screen. Both the 2005 and 2007 qHTS runs were performed with freshly titrated copies of the library (less than 2 weeks). The pAC₅₀ values derived from the high-quality CRCs from each dataset are plotted (MSR = 1.24, n = 3,260 samples). The 95% limits of agreement are shown as dotted lines.

FIG. 9.

Reproducibility of the qHTS process on the Kalypsys robotic system. (Left panel) 3D-scatter plot with CRC fits shown for samples assayed in the pyruvate kinase-luciferase coupled assay. CRCs are annotated by curve fit quality as described in Inglese et al. (Right panel) Bland-Altman plot comparing the pAC₅₀ values from a pyruvate kinase-luciferase-coupled biochemical assay performed in September 2005 and again in March 2007. Separate copies of the chemical library were obtained, titrated, and stored on the robotic system in each screen. Both the 2005 and 2007 qHTS runs were performed with freshly titrated copies of the library (less than 2 weeks). The pAC₅₀ values derived from the high-quality CRCs from each dataset are plotted (MSR = 1.24, n = 3,260 samples). The 95% limits of agreement are shown as dotted lines.

FIG. 10.

Enhancement of the Dispatcher by the LabHTTI Application. LabHTTI communicates with the Dispatcher automation server via an ActiveX component. The assay objects are defined as the mother plates and their associated daughter plates, with “N” representing a single object. Multiple assay objects can be running in parallel as needed, with the Dispatcher handling the scheduling aspects. LabHTTI connects to the Dispatcher and then launches an assay. As the Dispatcher performs various functions, LabHTTI captures all events generated by the Dispatcher and handles them as required.