Cell-based assays are indispensable tools in biological research, offering insights into cell behavior, gene function, and drug activity. Techniques like high-throughput screening for drug discovery and advanced technologies like organ-on-chip and single-cell analyses give researchers unprecedented insights to drive progress in biomedicine. However, challenges such as operator-to-operator variability, contamination and increased need for data points highlight the need for automation to improve the throughput, the reliability and efficiency of cell-based assays.
This article explores the applications of cell-based assays, the opportunities for automation and how it supports scientists and clinicians delivering high quality results, consistently, and within expected timelines and budget.
Applications of Cell-based Assays
High-throughput Screening
Drug discovery efforts rely on screening large compound libraries quickly and accurately in cellular systems. Cell-based assays in this context often include specific reporter assays that detect and measure a compound’s ability to bind a molecular target and elicit the desired effect, such as inhibition of enzyme activity (Best et al., 2024).
Functional Genomics
Functional genomics assays aim to determine how various genetic modifications, such as gene knockdown or knockout, affect cellular functions. CRISPR screening assays are a specific type of cell-based assay that introduce these genetic changes into cells and measure particular outcomes (Zhou et al., 2014). These outcomes can include cell proliferation, viability, and specific molecular signals detected using reporter cells.
Toxicology
Toxicology is a critical parameter assessed during therapy development. Performing cell-based toxicology screening is vital for evaluating drug safety, identifying potential cytotoxicities, and ensuring the efficacy of compounds while minimizing adverse effects (Szymański et al., 2012). Accurate toxicology studies using cell-based assays help to ensure that only safe and effective therapies are brought forward for further clinical evaluation.
Emerging Technologies
Technological advancements continuously enhance high-throughput cell-based assays, enabling researchers to gain deeper insights into cell behavior under various conditions.
High-content Screening
High-content screening involves using multiple analytical methods simultaneously to monitor cells and obtain comprehensive insights from a single experiment (Nierode et al., 2016). This approach can include toxicology, genomic screening, and cytotoxicity assays, as well as imaging of cellular structures, quantifying subcellular features, tracking dynamic processes like cell migration and signaling, and analyzing complex phenotypic changes in high resolution (Fig. 1).
Single-cell Analysis
The analysis of single cells allows for the characterization of important but less abundant cell types without their impact being drowned out by noise from other cells. It helps reveal rare subpopulations from complex mixtures and elucidates specific mechanisms of gene expression and molecular signaling (Sagar et al., 2018).
Microfluidics & Organ-on-Chip
Microfluidics allows cell-based assays to be performed at incredibly small scales (Duncombe et al., 2015). This decreases the volume required for expensive reagents such as cell culture media, test compounds, and gene-editing tools like CRISPR.
Related to advances in microfluidics is the concept of organ-on-chip. Organ-on-chip technology involves culturing living cells in micro-engineered devices that replicate the structure and function of human organs. These systems mimic organ-level processes like blood flow and nutrient delivery, enabling precise drug testing, disease modeling, and toxicity assessments (Ingber, 2022).
Challenges
Cell-based assays can be affected by many variables that prevent researchers from deriving meaningful and accurate results.
Cell Detachment
Cell-based assays often require multiple washing steps or media changes, repeatedly exposing cells to forces that may cause them to detach from the test plate. Mechanical stress can cause cellular stress death, a reduction in signal that is unrelated to the intended test conditions, or cell detachment and loss together with the washing buffer, leading to confounding, misleading results.
Variability Due to Manual Pipetting
Manual pipetting methods for cell-based assays can introduce variability in several ways (Lippi et al., 2017). They increase the chances of incorrect dispensing, leading to the wrong reagents being added to wells. Furthermore, incomplete, inefficient or slow washing due to manual pipetting can mean heterogeneity in cell treatment across the wells of a same plate, leading to some cells are exposed to reagents or test compounds longer than others, increasing variability and standard deviation potentially impacting results quality and interpretation when unaccounted for.
Cross Contamination
Cross-contamination is particularly problematic when screening using high-throughput cell-based assays, as it can mean that different compounds or concentrations are inappropriately mixed or added to the wrong wells. Cross-contamination can either relate to cells of a type contaminating another, or compounds getting in contact with unintended samples. The higher the reliance on manual work and the more conditions or samples being tested in a single experiment, the greater the risk of cross-contamination.
High Background Noise
Background noise makes it difficult for researchers to distinguish the test signal from signals caused by contaminants or leftover reagents. This issue often arises from insufficient removal of reagents during washing steps.
Automation
Automation adoption is a natural development for labs scaling-up and professionalizing cell-based assays. Automation allows researchers to repeat precise experimental conditions without introducing operator variables.
Let’s address the elephant in the room, state-of-the-art automation requires a sensible upfront investment before being able to reap its benefits over time. So do how do you get your money back?
- Automation increases your lab output: it fosters the generation of reliable and reproducible results at scale, without increasing laboratories head counts
- It relieves existing lab personal of error-prone repetitive and tedious tasks, this means more robust and trustworthy results, significantly reducing the need for repeat experiments. (Holland & Davies, 2020).
- Gains in precision and accuracy enables scaling down the reaction volumes of cell-based assays, reducing the costs associated with expensive reagents.
- Finally, some types of consumables reduces the use of standard lab consumables such as plasticware, saving costs but also contributing in decreasing the environmental impact of lab operations.
The C.WASH PLUS from CYTENA has emerged as an essential tool for various applications, including cell-based assays. Thanks to its design and centrifugal washing principle, the C.WASH+ ensures <0.1 μL residual volume per well for 96-, 384- and 1536-well plate formats, and its gentle evacuation steps virtually eliminate cell detachment issues (Fig. 2).
The C.WASH+ also comes in handy its dispensing capability, taking care or dispense-rinse wash cycles autonomously, especially when integrated in an automated workflow, thanks to its integration-friendly design.
Contact-free dispensing in 96-, 384- and 1536-well plate formats means that the C.WASH PLUS doesn’t require any plastic tips at all. This saving accounts for the instrument very rapid return on investment.
Conclusions and Future Directions
Contact CYTENA today to learn how the C.WASH PLUS can fit seamlessly into your existing cell-based assay workflow.
References
- Best, A. J., Braunschweig, U., Wu, M., Farhangmehr, S., Pasculescu, A., Lim, J. J., Comsa, L. C., Jen, M., Wang, J., Datti, A., Wrana, J. L., Cordes, S. P., Al-awar, R., Han, H., & Blencowe, B. J. (2024). High-throughput sensitive screening of small molecule modulators of microexon alternative splicing using dual Nano and Firefly luciferase reporters. Nature Communications, 15(1), 6328.
- Duncombe, T. A., Tentori, A. M., & Herr, A. E. (2015). Microfluidics: Reframing biological enquiry. Nature Reviews. Molecular Cell Biology, 16(9), 554–567.
- Holland, I., & Davies, J. A. (2020). Automation in the Life Science Research Laboratory. Front Bioeng Biotechnol, 8(571777).
- Ingber, D. E. (2022). Human organs-on-chips for disease modelling, drug development and personalized medicine. Nature Reviews Genetics, 23(8), 467–491.
- Lippi, G., Lima-Oliveira, G., Brocco, G., Bassi, A., & Salvagno, G. L. (2017). Estimating the intra- and inter-individual imprecision of manual pipetting. Clinical Chemistry and Laboratory Medicine (CCLM), 55(7).
- Nierode, G., Kwon, P. S., Dordick, J. S., & Kwon, S.-J. (2016). Cell-Based Assay Design for High-Content Screening of Drug Candidates. Journal of Microbiology and Biotechnology, 26(2), 213–225.
- 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.
- Zhou, Y., Zhu, S., Cai, C., Yuan, P., Li, C., Huang, Y., & Wei, W. (2014). High-throughput screening of a CRISPR/Cas9 library for functional genomics in human cells. Nature, 509(7501), 487–491.