High-throughput screening: update on practices and success

High-throughput screening (HTS) has become an important part of drug discovery at most pharmaceutical and many biotechnology companies worldwide, and use of HTS technologies is expanding into new areas. Target validation, assay development, secondary screening, ADME/Tox, and lead optimization are among the areas in which there is an increasing use of HTS technologies. It is becoming fully integrated within drug discovery, both upstream and downstream, which includes increasing use of cell-based assays and high-content screening (HCS) technologies to achieve more physiologically relevant results and to find higher quality leads. In addition, HTS laboratories are continually evaluating new technologies as they struggle to increase their success rate for finding drug candidates. The material in this article is based on a 900-page HTS industry report involving 54 HTS directors representing 58 HTS laboratories and 34 suppliers.     

The future of high-throughput screening

High-throughput screening (HTS) is a well-established process in lead discovery for pharma and biotech companies and is now also being set up for basic and applied research in academia and some research hospitals. Since its first advent in the early to mid-1990s, the field of HTS has seen not only a continuous change in technology and processes but also an adaptation to various needs in lead discovery. HTS has now evolved into a quite mature discipline of modern drug discovery. Whereas in previous years, much emphasis has been put toward a steady increase in capacity ("quantitative increase") via various strategies in the fields of automation and miniaturization, the past years have seen a steady shift toward higher content and quality ("quality increase") for these biological test systems. Today, many experts in the field see HTS at the crossroads with the need to decide either toward further increase in throughput or more focus toward relevance of biological data. In this article, the authors describe the development of HTS over the past decade and point out their own ideas for future directions of HTS in biomedical research. They predict that the trend toward further miniaturization will slow down with the implementation of 384-well, 1536-well, and 384 low-volume-well plates. The authors predict that, ultimately, each hit-finding strategy will be much more project related, tailor-made, and better integrated into the broader drug discovery efforts.     

Aptamers as reagents for high-throughput screening

The identification of new drug candidates from chemical libraries is a major component of discovery research in many pharmaceutical companies. Given the large size of many conventional and combinatorial libraries and the rapid increase in the number of possible therapeutic targets, the speed with which efficient high-throughput screening (HTS) assays can be developed can be a rate-limiting step in the discovery process. We show here that aptamers, nucleic acids that bind other molecules with high affinity, can be used as versatile reagents in competition binding HTS assays to identify and optimize small-molecule ligands to protein targets. To illustrate this application, we have used labeled aptamers to platelet-derived growth factor B-chain and wheat germ agglutinin to screen two sets of potential small-molecule ligands. In both cases, binding affinities of all ligands tested (small molecules and aptamers) were strongly correlated with their inhibitory potencies in functional assays. The major advantages of using aptamers in HTS assays are speed of aptamer identification, high affinity of aptamers for protein targets, relatively large aptamer-protein interaction surfaces, and compatibility with various labeling/detection strategies. Aptamers may be particularly useful in HTS assays with protein targets that have no known binding partners such as orphan receptors. Since aptamers that bind to proteins are often specific and potent antagonists of protein function, the use of aptamers for target validation can be coupled with their subsequent use in HTS.     

High-throughput screening in academia: the Harvard experience

To identify small-molecule modulators of biologic systems, academic scientists are beginning to use high-throughput screening (HTS) approaches that have traditionally been used only in industry. The HTS laboratories that are being established in universities, while differing in details of staffing, equipment, and size, have all been created to attain 1 or more of 3 principal goals: drug discovery, chemical genetics, or training. This article will examine the role that these activities play in 4 HTS laboratories that have been created within the academic community of Harvard Medical School and its affiliated institutions. First, the 3 activities will be defined with special attention paid to describing the impact they are having on how academic biologic science is conducted today. Next, the histories and operations of the 4 Harvard laboratories are reviewed. In the course of these summaries, emphasis is placed on understanding the motivational role that the 3 activities initially played in the creation of the 4 Harvard facilities and the roles that the activities continue to play in their day-to-day operations. Finally, several concerns are identified that must be attended to for the successful establishment and operation of an academic biologic science that has yet to be fully determined. HTS has the ability to provide the tools to test previously untestable hypotheses and can thereby allow the discovery of the unanticipated and the truly novel.     

Robustness of Massively Parallel Sequencing Platforms

The improvements in high throughput sequencing technologies (HTS) made clinical sequencing projects such as ClinSeq and Genomics England feasible. Although there are significant improvements in accuracy and reproducibility of HTS based analyses, the usability of these types of data for diagnostic and prognostic applications necessitates a near perfect data generation. To assess the usability of a widely used HTS platform for accurate and reproducible clinical applications in terms of robustness, we generated whole genome shotgun (WGS) sequence data from the genomes of two human individuals in two different genome sequencing centers. After analyzing the data to characterize SNPs and indels using the same tools (BWA, SAMtools, and GATK), we observed significant number of discrepancies in the call sets. As expected, the most of the disagreements between the call sets were found within genomic regions containing common repeats and segmental duplications, albeit only a small fraction of the discordant variants were within the exons and other functionally relevant regions such as promoters. We conclude that although HTS platforms are sufficiently powerful for providing data for first-pass clinical tests, the variant predictions still need to be confirmed using orthogonal methods before using in clinical applications.     

Prevention,diagnosis and treatment of high‐throughput sequencing data pathologies

High‐throughput sequencing (HTS) technologies generate millions of sequence reads from DNA/RNA molecules rapidly and cost‐effectively, enabling single investigator laboratories to address a variety of ‘omics’ questions in nonmodel organisms, fundamentally changing the way genomic approaches are used to advance biological research. One major challenge posed by HTS is the complexity and difficulty of data quality control (QC). While QC issues associated with sample isolation, library preparation and sequencing are well known and protocols for their handling are widely available, the QC of the actual sequence reads generated by HTS is often overlooked. HTS‐generated sequence reads can contain various errors, biases and artefacts whose identification and amelioration can greatly impact subsequent data analysis. However, a systematic survey on QC procedures for HTS data is still lacking. In this review, we begin by presenting standard ‘health check‐up’ QC procedures recommended for HTS data sets and establishing what ‘healthy’ HTS data look like. We next proceed by classifying errors, biases and artefacts present in HTS data into three major types of ‘pathologies’, discussing their causes and symptoms and illustrating with examples their diagnosis and impact on downstream analyses. We conclude this review by offering examples of successful ‘treatment’ protocols and recommendations on standard practices and treatment options. Notwithstanding the speed with which HTS technologies – and consequently their pathologies – change, we argue that careful QC of HTS data is an important – yet often neglected – aspect of their application in molecular ecology, and lay the groundwork for developing a HTS data QC ‘best practices’ guide.     

High‐Temperature Shock Enabled Nanomanufacturing for Energy‐Related Applications

Functional nanomaterials are playing a crucial role in the emerging field of energy‐related devices. Recently, as a novel synthesis method, high‐temperature shock (HTS), which is rapid, low cost, eco‐friendly, universal, scalable, and controllable, has provided a promising option for the rational design and synthesis of various high‐quality nanomaterials. In this report, the HTS technique, including the equipment setup and operating principle, is systematically introduced, and recent progress in the synthesis of nanomaterials for energy storage and conversion applications using this HTS method is summarized. The growth mechanisms of nanoparticles and carbonaceous nanomaterials are thoroughly discussed, followed by the summary of the characteristic advantages of the HTS strategy. A series of nanomaterials prepared by the HTS method, including carbon‐based films, metal nanoparticles and compound nanoparticles, show high performance in the diverse applications of storage energy batteries, highly active catalysts, and smart energy devices. Finally, the future perspectives and directions of HTS in nanomanufacturing for broader applications are presented.     

TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets

Background

Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups.

Results

We have developed Screensaver, a free, open source, web-based lab information management system (LIMS), to address the informatics needs of our small molecule and RNAi screening facility. Screensaver supports the storage and comparison of screening data sets, as well as the management of information about screens, screeners, libraries, and laboratory work requests. To our knowledge, Screensaver is one of the first applications to support the storage and analysis of data from both genome-scale RNAi screening projects and small molecule screening projects.

Conclusions

The informatics and administrative needs of an HTS facility may be best managed by a single, integrated, web-accessible application such as Screensaver. Screensaver has proven useful in meeting the requirements of the ICCB-Longwood/NSRB Screening Facility at Harvard Medical School, and has provided similar benefits to other HTS facilities.     

Development, validation and implementation of immobilized metal affinity for phosphochemicals (IMAP)-based high-throughput screening assays for low-molecular-weight compound libraries

This protocol describes assay development, validation and implementation of automated immobilized metal affinity for phosphochemicals (IMAP)-based fluorescence polarization (FP) and time-resolved fluorescence resonance energy transfer (TR-FRET) high-throughput screening (HTS) assays for identification of low-molecular-weight kinase inhibitors. Both procedures are performed in miniaturized kinase reaction volumes and involve the stepwise addition of test or control compounds, enzyme and substrate/ATP. Kinase reactions are stopped by subsequent addition of IMAP-binding buffer. Assay attributes of the IMAP FP and TR-FRET methodologies are described. HTS assays developed using these procedures should result in Z-factors and low assay variability necessary for robust HTS assays. Providing that the required reagents and equipment are available, one scientist should be able to develop a 384-well, miniaturized HTS assay in approximately 6-8 weeks. Specific automated HTS assay conditions will determine the number of assay plates processed in a screening session, but two scientists should expect to process between 100 and 150 assay plates in one 8-h screening day.     

The design and development of an integrated natural products screening database

We designed and developed NEXUS--a new natural products screening database and related suite of software applications--to utilize the spectacular increases in assay capacity of the modern high throughput screening (HTS) environment. NEXUS not only supports seamless integration with separate HTS systems, but supports user-customized integration with external laboratory automation, particularly sample preparation systems. Designed and developed based on a detailed process model for natural products drug discovery, NEXUS comprises two integrated parts: (1) a single schema of Oracle tables and callable procedures and functions, and (2) software "front-ends" to the database developed using Microsoft Excel and Oracle Discovery/2000. Many of the back-end processing functions were written in Programming Language/Structured Query Language (PL/SQL) to provide an Application Programmer's Interface, which allows end users to create custom applications with little input from information technology professionals.     

An efficient method for the detection and elimination of systematic error in high-throughput screening

MOTIVATION: High-throughput screening (HTS) is an early-stage process in drug discovery which allows thousands of chemical compounds to be tested in a single study. We report a method for correcting HTS data prior to the hit selection process (i.e. selection of active compounds). The proposed correction minimizes the impact of systematic errors which may affect the hit selection in HTS. The introduced method, called a well correction, proceeds by correcting the distribution of measurements within wells of a given HTS assay. We use simulated and experimental data to illustrate the advantages of the new method compared to other widely-used methods of data correction and hit selection in HTS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

High-throughput siRNA-based functional target validation

The drug discovery process pursued by major pharmaceutical companies for many years starts with target identification followed by high-throughput screening (HTS) with the goal of identifying lead compounds. To accomplish this goal, significant resources are invested into automation of the screening process or HTS. Robotic systems capable of handling thousands of data points per day are implemented across the pharmaceutical sector. Many of these systems are amenable to handling cell-based screening protocols as well. On the other hand, as companies strive to develop innovative products based on novel mechanisms of action(s), one of the current bottlenecks of the industry is the target validation process. Traditionally, bioinformatics and HTS groups operate separately at different stages of the drug discovery process. The authors describe the convergence and integration of HTS and bioinformatics to perform high-throughput target functional identification and validation. As an example of this approach, they initiated a project with a functional cell-based screen for a biological process of interest using libraries of small interfering RNA (siRNA) molecules. In this protocol, siRNAs function as potent gene-specific inhibitors. siRNA-mediated knockdown of the target genes is confirmed by TaqMan analysis, and genes with impacts on biological functions of interest are selected for further analysis. Once the genes are confirmed and further validated, they may be used for HTS to yield lead compounds.     

HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data

MOTIVATION: High-throughput screening (HTS) plays a central role in modern drug discovery, allowing for testing of >100,000 compounds per screen. The aim of our work was to develop and implement methods for minimizing the impact of systematic error in the analysis of HTS data. To the best of our knowledge, two new data correction methods included in HTS-Corrector are not available in any existing commercial software or freeware. RESULTS: This paper describes HTS-Corrector, a software application for the analysis of HTS data, detection and visualization of systematic error, and corresponding correction of HTS signals. Three new methods for the statistical analysis and correction of raw HTS data are included in HTS-Corrector: background evaluation, well correction and hit-sigma distribution procedures intended to minimize the impact of systematic errors. We discuss the main features of HTS-Corrector and demonstrate the benefits of the algorithms.     

The use of 3-D cultures for high-throughput screening: the multicellular spheroid model

Over the past few years, establishment and adaptation of cell-based assays for drug development and testing has become an important topic in high-throughput screening (HTS). Most new assays are designed to rapidly detect specific cellular effects reflecting action at various targets. However, although more complex than cell-free biochemical test systems, HTS assays using monolayer or suspension cultures still reflect a highly artificial cellular environment and may thus have limited predictive value for the clinical efficacy of a compound. Today's strategies for drug discovery and development, be they hypothesis free or mechanism based, require facile, HTS-amenable test systems that mimic the human tissue environment with increasing accuracy in order to optimize preclinical and preanimal selection of the most active molecules from a large pool of potential effectors, for example, against solid tumors. Indeed, it is recognized that 3-dimensional cell culture systems better reflect the in vivo behavior of most cell types. However, these 3-D test systems have not yet been incorporated into mainstream drug development operations. This article addresses the relevance and potential of 3-D in vitro systems for drug development, with a focus on screening for novel antitumor drugs. Examples of 3-D cell models used in cancer research are given, and the advantages and limitations of these systems of intermediate complexity are discussed in comparison with both 2-D culture and in vivo models. The most commonly used 3-D cell culture systems, multicellular spheroids, are emphasized due to their advantages and potential for rapid development as HTS systems. Thus, multicellular tumor spheroids are an ideal basis for the next step in creating HTS assays, which are predictive of in vivo antitumor efficacy.     

Integrating experimental and analytic approaches to improve data quality in genome-wide RNAi screens

RNA interference (RNAi) not only plays an important role in drug discovery but can also be developed directly into drugs. RNAi high-throughput screening (HTS) biotechnology allows us to conduct genome-wide RNAi research. A central challenge in genome-wide RNAi research is to integrate both experimental and computational approaches to obtain high quality RNAi HTS assays. Based on our daily practice in RNAi HTS experiments, we propose the implementation of 3 experimental and analytic processes to improve the quality of data from RNAi HTS biotechnology: (1) select effective biological controls; (2) adopt appropriate plate designs to display and/or adjust for systematic errors of measurement; and (3) use effective analytic metrics to assess data quality. The applications in 5 real RNAi HTS experiments demonstrate the effectiveness of integrating these processes to improve data quality. Due to the effectiveness in improving data quality in RNAi HTS experiments, the methods and guidelines contained in the 3 experimental and analytic processes are likely to have broad utility in genome-wide RNAi research.     

metaBIT,an integrative and automated metagenomic pipeline for analysing microbial profiles from high‐throughput sequencing shotgun data

Micro‐organisms account for most of the Earth's biodiversity and yet remain largely unknown. The complexity and diversity of microbial communities present in clinical and environmental samples can now be robustly investigated in record times and prices thanks to recent advances in high‐throughput DNA sequencing (HTS). Here, we develop metaBIT, an open‐source computational pipeline automatizing routine microbial profiling of shotgun HTS data. Customizable by the user at different stringency levels, it performs robust taxonomy‐based assignment and relative abundance calculation of microbial taxa, as well as cross‐sample statistical analyses of microbial diversity distributions. We demonstrate the versatility of metaBIT within a range of published HTS data sets sampled from the environment (soil and seawater) and the human body (skin and gut), but also from archaeological specimens. We present the diversity of outputs provided by the pipeline for the visualization of microbial profiles (barplots, heatmaps) and for their characterization and comparison (diversity indices, hierarchical clustering and principal coordinates analyses). We show that metaBIT allows an automatic, fast and user‐friendly profiling of the microbial DNA present in HTS shotgun data sets. The applications of metaBIT are vast, from monitoring of laboratory errors and contaminations, to the reconstruction of past and present microbiota, and the detection of candidate species, including pathogens.     

Statistical analysis of systematic errors in high-throughput screening

High-throughput screening (HTS) is an efficient technology for drug discovery. It allows for screening of more than 100,000 compounds a day per screen and requires effective procedures for quality control. The authors have developed a method for evaluating a background surface of an HTS assay; it can be used to correct raw HTS data. This correction is necessary to take into account systematic errors that may affect the procedure of hit selection. The described method allows one to analyze experimental HTS data and determine trends and local fluctuations of the corresponding background surfaces. For an assay with a large number of plates, the deviations of the background surface from a plane are caused by systematic errors. Their influence can be minimized by the subtraction of the systematic background from the raw data. Two experimental HTS assays from the ChemBank database are examined in this article. The systematic error present in these data was estimated and removed from them. It enabled the authors to correct the hit selection procedure for both assays.     

Improved statistical methods for hit selection in high-throughput screening

High-throughput screening (HTS) plays a central role in modern drug discovery, allowing the rapid screening of large compound collections against a variety of putative drug targets. HTS is an industrial-scale process, relying on sophisticated automation, control, and state-of-the art detection technologies to organize, test, and measure hundreds of thousands to millions of compounds in nano- to microliter volumes. Despite this high technology, hit selection for HTS is still typically done using simple data analysis and basic statistical methods. The authors discuss in this article some shortcomings of these methods and present alternatives based on modern methods of statistical data analysis. Most important, they describe and show numerous real examples from the biologist-friendly Stat Server HTS application (SHS), a custom-developed software tool built on the commercially available S-PLUS and StatServer statistical analysis and server software. This system remotely processes HTS data using powerful and sophisticated statistical methodology but insulates users from the technical details by outputting results in a variety of readily interpretable graphs and tables.     

Development of a high-throughput screening method for LIM kinase 1 using a luciferase-based assay of ATP consumption

Kinases are attractive drug targets because of the central roles they play in signal transduction pathways and human diseases. Their well-formed adenosine triphosphate (ATP)-binding pockets make ideal targets for small-molecule inhibitors. For drug discovery purposes, many peptide-based kinase assays have been developed that measure substrate phosphorylation using fluorescence-based readouts. However, for some kinases these assays may not be appropriate. In the case of the LIM kinases (LIMK), an inability to phosphorylate peptide substrates resulted in previous high-throughput screens (HTS) using radioactive labeling of recombinant cofilin protein as the readout. We describe the development of an HTS-compatible assay that measures relative ATP levels using luciferase-generated luminescence as a function of LIMK activity. The assay was inexpensive to perform, and proof-of-principle screening of kinase inhibitors demonstrated that compound potency against LIMK could be determined; ultimately, the assay was used for successful prosecution of automated HTS. Following HTS, the secondary assay format was changed to obtain more accurate measures of potency and mechanism of action using more complex (and expensive) assays. The luciferase assay nonetheless provides an inexpensive and reliable primary assay for HTS that allowed for the identification of LIMK inhibitors to initiate discovery programs for the eventual treatment of human diseases.     

A fluorometric assay for high-throughput screening targeting nicotinamide phosphoribosyltransferase

Nicotinamide adenine dinucleotide (NAD) plays a crucial role in many cellular processes. As the rate-limiting enzyme of the predominant NAD biosynthesis pathway in mammals, nicotinamide phosphoribosyltransferase (Nampt) regulates the cellular NAD level. Tumor cells are more sensitive to the NAD levels, making them more susceptible to Nampt inhibition than their nontumorigenic counterparts. Experimental evidence has indicated that Nampt might have proangiogenic activity and supports the growth of some tumors, so Nampt inhibitors may be promising as antitumor agents. However, only four Nampt inhibitors have been reported, and no high-throughput screening (HTS) strategy for Nampt has been proposed to date, largely limiting the drug discovery targeting Nampt. Therefore, the development of a robust HTS strategy for Nampt is both imperative and significant. Here we developed a fluorometric method for a Nampt activity assay by measuring the fluorescence of nicotinamide mononucleotide (NMN) derivative resulting from the enzymatic product NMN through simple chemical reactions. Then we set up an HTS system after thorough optimizations of this method and validated that it is feasible and effective through a pilot screening on a small library. This HTS system should expedite the discovery of Nampt inhibitors as antitumor drug candidates.