High-throughput screening (HTS) refers to the various technologies which rapidly sequence DNA or RNA, allowing for large-scale whole genome sequencing. Because of this, various fields have benefited from research in genomics, transcriptomics, and bioinformatics, in addition to healthcare and biotechnological progress.
In transcriptomics, for example, HTS is a useful alternative to microarray techniques. This is because microarrays require designs before measuring, which means it is more difficult to test non-model organisms, unlike HTS.1 In healthcare, HTS approaches have been added into electronic health records to generate patient reports associated with genomic variants and disease phenotypes.2
Applications of High-Throughput Screening
In the field of genomics, HTS provides researchers with the ability to sequence entire genomes quickly and efficiently. This has assisted in the discovery of genetic variations associated with diseases, drug responses, and individual phenotypic differences. Previously, whole-genome sequencing was a labor-intensive and costly process, but with HTS, vast amounts of genetic information can be generated in a fraction of the time. This enables biotech companies and research institutions to identify new drug targets or develop gene therapies more rapidly.
In transcriptomics, HTS can be an alternative to traditional microarray techniques. Microarrays, while useful, require predefined probe designs, limiting their flexibility when it comes to non-model organisms or unexpected genetic variations. HTS, on the other hand, offers the advantage of not requiring such designs, making it more adaptable for studying organisms with limited genetic information available. Researchers can analyze the entire transcriptome—the complete set of RNA transcripts produced by a cell—allowing for a deeper understanding of gene expression patterns and regulatory mechanisms.
The vast amount of data generated by HTS has also caused growth in bioinformatics, a field that combines biology, computer science, and statistics. Managing and analyzing the complex datasets produced by HTS requires computational tools to identify patterns, genetic mutations, and gene expression changes. These data-driven approaches are critical for the development of new biological products, such as engineered antibodies, enzymes, or gene therapies, with optimization being particularly important in drug discovery.
Related: Harnessing Big Data: Databases in Antibody Engineering
Implications for Antibody Discovery and Therapeutics
HTS technologies are also driving innovation in antibody discovery and therapeutic development. Traditional methods of antibody discovery often involved labor-intensive screening processes that limited the speed at which new antibodies could be identified and validated. However, with HTS, large libraries of antibody candidates can be rapidly screened, allowing for the identification of promising candidates that bind specifically to disease-related targets.
Related: How Therapeutic Antibodies Are Produced: Screening and Selection
The use of HTS in antibody discovery is especially promising in the development of bispecific antibodies, which are engineered to bind to two different antigens simultaneously. One example is the development of a single-cell-based platform for HTS of bispecific antibody variants from large, unbiased libraries. Using droplet microfluidics, individual BsAb-producing cells are screened by co-encapsulating them with reporter cells, detecting functional clones via fluorescence. The platform demonstrated higher throughput than conventional methods and successfully isolated rare functional clones.3
Another exciting application of HTS is in the area of drug repurposing.4 By screening existing drugs against large panels of genomic data or disease models, researchers can identify new therapeutic uses for drugs that are already approved for other conditions. This approach not only reduces the time and cost associated with drug development but also opens up new avenues for treating diseases that currently lack effective therapies.
HTS can identify potential off-target effects of drugs that may be beneficial in other disease contexts. For instance, a drug initially developed for cardiovascular disease may be found to have anticancer properties when screened against cancer-related genomic data. This ability to uncover hidden therapeutic potential in existing compounds makes HTS a valuable tool in expanding the repertoire of available treatments, particularly in the areas of oncology and infectious diseases.
Future Trends in HTS and Biotech
As HTS technologies continue to advance, their applications in biotechnology are expected to expand even further. The advent of single-cell sequencing is one such innovation, allowing researchers to study the genetic and transcriptomic profiles of individual cells. This has profound implications for understanding cell differentiation, immune responses, and disease progression at a level of detail previously unattainable.
References:
Y.-h. Taguchi, Comparative Transcriptomics Analysis, Editor(s): Shoba Ranganathan, Michael Gribskov, Kenta Nakai, Christian Schönbach, Encyclopedia of Bioinformatics and Computational Biology, Academic Press, 2019, Pages 814-818, ISBN 9780128114322, https://doi.org/10.1016/B978-0-12-809633-8.20163-5
Dibyabhaba Pradhan, Amit Kumar, Harpreet Singh, Usha Agrawal, Chapter 4 - High-throughput sequencing, Editor(s): Gauri Misra, Data Processing Handbook for Complex Biological Data Sources, Academic Press, 2019, Pages 39-52, ISBN 9780128165485, https://doi.org/10.1016/B978-0-12-816548-5.00004-6
Segaliny, A. I., Jayaraman, J., Chen, X., Chong, J., Luxon, R., Fung, A., Fu, Q., Jiang, X., Rivera, R., Ma, X., Ren, C., Zimak, J., Hedde, P. N., Shang, Y., Wu, G., & Zhao, W. (2023). A high throughput bispecific antibody discovery pipeline. Communications Biology, 6(1), 1-14. https://doi.org/10.1038/s42003-023-04746-w
Bonaventura, G. D., Lupetti, V., Giulio, A. D., Muzzi, M., Piccirilli, A., Cariani, L., & Pompilio, A. (2023). Repurposing High-Throughput Screening Identifies Unconventional Drugs with Antibacterial and Antibiofilm Activities against Pseudomonas aeruginosa under Experimental Conditions Relevant to Cystic Fibrosis. Microbiology Spectrum, 11(4). https://doi.org/10.1128/spectrum.00352-23
Szymański, P., Markowicz, M., & Mikiciuk-Olasik, E. (2012). Adaptation of High-Throughput Screening in Drug Discovery—Toxicological Screening Tests. International Journal of Molecular Sciences, 13(1), 427-452. https://doi.org/10.3390/ijms13010427
