Synthetic biology, also known as SynBio, focuses on the application of engineering principles to redesign, repurpose, or develop new biological systems, cells, or materials for useful purposes or to solve complex problems1.
Synthetic biology has a broad range of applications that span the fields of healthcare. SynBio is used for developing cell-based therapies, diagnostic strategies, and new antimicrobials, and industry, where biofuels, biomaterials, and chemical manufacturing processes are designed using SynBio principles. Moreover, synthetic biology is applied to environmental problems such as biosensing and remediation and developing new research tools and technologies2.
The broad array of SynBio applications requires an equally diverse suite of technologies, encompassing DNA synthesis and assembly, mathematical modeling, computer-aided design, and omics technologies2. Crafting robust synthetic biology assays necessitates a systematic and strategic approach through every phase – from design and development to optimization and validation.
Here, we explore the essential principles of an effective synthetic biology assay development pipeline, highlight vital considerations, and investigate cutting-edge assay development technologies.
The synthetic biology development process typically adheres to the design-build-test-learn (DBTL) pipeline3.
In the initial design phase, researchers leverage their expertise to design experiments and pathways, selecting the most appropriate biological components for their project’s goals.
Subsequently, the build phase involves the actual assembly of the system, utilizing techniques like genome editing, DNA assembly (Fig. 1), and sequencing to bring the selected elements together.
Figure 1. The build phase of the synthetic biology assay development pipeline involves the synthesis of genetic constructs through DNA assembly techniques.
After construction, the system undergoes rigorous testing. Various assay development technologies, including microfluidics, flow cytometry, automation, and next-generation sequencing, may be employed to evaluate the system’s accuracy, precision, reproducibility, and overall robustness.
In this critical phase, data analysis leads to the development of optimization strategies through modeling, simulation, and redesign. The advent of assay development technologies like artificial intelligence (AI) and machine learning (ML) has significantly augmented this phase, enabling more streamlined analysis and predictive improvements.
The cycle then revisits the design phase, continually refining and optimizing the system. This iterative process continues until a fully optimized, validated system can be applied to its intended purpose.
In addition to applying a systematic design of experiments (DoE) approach and integrating advanced assay development technology, researchers need to consider some key factors that are fundamental to the success of synthetic biology projects. By incorporating these principles, researchers can design and develop biological systems with unprecedented precision and efficiency to solve complex problems.
Given the multi-stage process of synthetic biology development, researchers must leverage the most advanced assay development technologies available. This can help streamline assay development, enhance precision, and accelerate the journey to groundbreaking SynBio discoveries.
AI plays a transformative role in synthetic biology assay development and validation. AI and ML tools can accelerate the identification of optimal conditions and configurations for synthetic biology systems through predictive analytics and modeling. They can also streamline experimental design, risk assessment, and data analysis, thus enhancing the efficiency of the development process9.
Microfluidic devices are useful for testing synthetic biological systems under precisely controlled environments that simulate physiological conditions and are essential for studying, mimicking, and manipulating systems' behavior over extended periods10. Additionally, microfluidic technologies support the miniaturization of assays, enhancing throughput while reducing the volume of samples needed11.
Automated liquid handling technologies further enhance the synthetic biology assay development pipeline. By increasing throughput, these systems allow researchers to achieve higher productivity, facilitating assay miniaturization and improving the precision and accuracy of assays12. Reducing manual pipetting steps also lowers the likelihood of human error, ensuring more consistent and reliable assay results.
One such assay development technology is the I.DOT Liquid Handler (Fig. 2). With the I.DOT Non-Contact Dispenser, researchers can easily create gradients of concentrations and volumes of assay components, allowing them to systematically explore the impact of different variables on assay outcomes.
Figure 2. The I.DOT Non-Contact Dispenser enables SynBio researchers to streamline their assay development processes for rapid, reproducible, and accurate workflows.
This automated dispenser streamlines the assay development process by providing reliable and consistent dispensing, facilitating the optimization of experimental conditions, and enhancing the efficiency and reproducibility of synthetic biology assays. Book your personalized demo with a DISPENDIX representative today!