Key Strategies for Optimizing NGS Workflows
Automation technologies can maximize the precision and efficiency of next-generation genomic sequencing research.

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Next-generation sequencing (NGS) has transformed biomedical research, offering unprecedented insights into diseases ranging from cancer to rare genetic disorders. The rapid sequencing of tumors and entire genomes provides researchers with vast data, facilitating the development of novel therapies.
Recent advancements in laboratory technologies have enabled the customization of NGS workflows to meet specific project requirements, including size, scope and desired outcomes. Integrating automation into various stages of the research process can significantly enhance efficiency and accuracy. However, selecting appropriate tools and determining the optimal level of automation requires careful consideration.
That’s why it’s essential for researchers to develop an automation plan at the start of each project. Working with an NGS equipment supplier can help establish a workflow that optimizes tools, protocols and reagents in ways that will enhance efficiency and cut costs. It will also ensure the workflow is flexible so it can be easily adjusted when research discoveries change the direction of the project. Automation in DNA and RNA extraction workflows for NGS applications is equally critical for achieving high-quality results.
Tailoring hardware to sample demands
Selecting the appropriate hardware for NGS workflows requires careful consideration of the specific characteristics of the samples being analyzed. The extraction and processing requirements for RNA differ significantly from those for DNA, necessitating distinct approaches. RNA extraction presents unique challenges, as yields can vary widely based on the type of tissue being processed.
For instance, fibrous tissues may require prolonged lysis times to achieve effective RNA release. Optimizing lysis protocols and using RNA stabilizers are critical to prevent rapid RNA degradation and to ensure the quality of RNA for downstream applications.
Similarly, DNA extraction must be customized based on the biological source. Extracting DNA involves breaking down tissue, cellular membranes and nuclear envelopes, with each tissue type presenting unique challenges. For example, DNA extraction from blood requires the effective disruption of multiple components – such as red blood cells, serum and clotting factors – that can act as inhibitors. Automated pipetting and mixing technologies can be used to efficiently handle complex blood samples, aiding in the dissolution of clots and enhancing the yield and purity of extracted DNA.
Different types of DNA, such as circulating cell-free DNA (cfDNA) and high molecular weight (HMW) DNA, also present distinct extraction challenges. cfDNA, which is often found in low concentrations in plasma, requires highly sensitive extraction methods to maximize recovery while minimizing contamination.
Extraction of HMW DNA, on the other hand, requires gentle handling to prevent shearing and to maintain the integrity of large DNA fragments, which are crucial for certain long-read sequencing applications. Optimizing extraction protocols for these DNA types is essential to ensure high-quality results in downstream NGS workflows.
Automation plays a pivotal role in optimizing both RNA and DNA extraction from tissue samples, either FFPE (formalin fixed paraffin embedded) or fresh frozen, ensuring consistency and reproducibility. The key here is the precise lysis and nucleic acid isolation process handling during the extraction process, employing sophisticated shaking and incubation protocols to achieve optimal results.
Beyond extraction, automation can be seamlessly integrated into subsequent steps of the NGS workflow, including library preparation, sequencing and data analysis, thereby streamlining the entire process and improving the overall efficiency of the laboratory workflow.
Choosing optimal consumables
Customizing NGS workflows also requires a thorough understanding of the desired output, the characteristics of the labware and the volume and compatibility of consumables. Selecting the correct consumables helps establish a cost-effective and efficient strategy that supports the entire NGS process.
One common challenge in NGS workflows is ensuring compatibility between consumables and liquid reagents. For instance, plastic 96-well plates may contain residues from manufacturing, such as mold-release agents or other contaminants, which can interfere with enzymatic reactions – particularly when polymerase enzymes are involved, as these enzymes can be sensitive to even trace contaminants. Such incompatibility can compromise the efficiency and success of the reaction, leading to reduced yield or failed experiments.
To address these issues, manufacturers have begun labeling consumables with specific designations, such as "DNase/RNAse Free" or "endotoxin-free." Researchers and developers must understand these labels to choose consumables that best suit their specific reagents and experimental requirements. Careful selection of consumables based on compatibility and intended use is crucial to ensure reliable and reproducible results in NGS workflows.
To fully leverage automation, researchers should develop a comprehensive automation strategy at the project's outset. Choosing the right consumables is a key aspect of achieving automation goals, as compatibility between labware, reagents and equipment directly impacts the efficiency and reliability of automated workflows. Additionally, a well-planned workflow should be adaptable, allowing modifications as new findings emerge and research objectives evolve.
Planning ahead
Before establishing an NGS workflow, it is crucial to consider how future research priorities might shift. For instance, a workflow designed to process 96 samples per day may need to be scaled up to accommodate higher throughput or down to handle fewer samples.
Additionally, changes in chemistry, such as switching between different NGS library preparation kits, or even switching technology vendors, may become necessary. For example, a project might start with a PCR-based library prep kit for targeted panels but later transition to a transposase-based kit for broader genomic applications. Making like-for-like comparisons based on panel type, such as targeted sequencing versus whole-genome sequencing, is essential to ensure that workflow changes meet the intended research goals. Such flexibility is vital, as evolving project needs often require adjustments to workflows, equipment or protocols.
To prepare for such uncertainties, it is advisable to select systems that are vendor-agnostic and designed with flexibility in mind. Many automated platforms allow for easy changes in vendor kit chemistry, enabling researchers to adapt to different reagent requirements as needed.
Some systems provide more extensive modular upgrades, including the ability to integrate additional hardware features, such as heating or cooling capabilities. For instance, if a project reaches a point where it becomes necessary to measure sample concentrations, these instruments can be upgraded to incorporate a reader. Such modular options enable flexibility to be built into NGS platforms, providing adaptability as requirements change throughout the project.
Additionally, cloud-based systems are contributing to flexible NGS research by enabling remote access to data, scalability and efficient data management. One of the challenges of NGS workflows is the large volume of data generated, which can create bottlenecks in data storage, processing and analysis. Cloud-based systems help address these challenges by providing scalable storage solutions, high-performance computing resources, and efficient data-sharing capabilities.
Compact, desktop-friendly equipment allows researchers to perform library preparation using kits from various vendors while benefiting from automated processing that reduces error rates. Cloud-driven software updates also ensure that laboratories, regardless of size, can access the latest features without needing to overhaul entire workflows, allowing them to stay up-to-date with technological advancements and improve workflow efficiency.
The ultimate impact of optimizing NGS workflows is the ability to make more precise and individualized discoveries. For instance, the use of NGS helps oncologists monitor tumor mutations in real-time, enabling personalized treatment strategies based on specific genetic alterations, such as identifying actionable mutations in genes like KRAS, BRAF and ALK. Additionally, NGS has been instrumental in understanding the diversity of the HLA (human leukocyte antigen) region, which plays a critical role in immune response and transplant compatibility.
Large-scale initiatives like the 100,000 Genomes Project in the United Kingdom, which aims to sequence whole genomes of patients in England, and The Cancer Genome Atlas (TCGA), which has cataloged key mutations across various cancer types, exemplify how efficient NGS methods can generate insights into the genetic basis of rare diseases and cancer.
Moreover, NGS has contributed to identifying genetic variations in genes like CFTR, which is linked to cystic fibrosis, and mutations in MYD88, which are associated with certain lymphomas. Furthermore, discoveries involving the HLA gene region have improved the understanding of transplant compatibility and immune-related diseases, while other findings, such as TP53 mutations, have provided critical insights into cancer progression and prognosis.
With more effective approaches to unlocking genomic data, medical researchers are not just generating data, they are saving lives. These insights allow for timely, precise and personalized treatments, giving hope to patients facing serious diseases like cancer and rare genetic disorders. By optimizing workflows and leveraging the power of NGS, researchers are transforming patient outcomes, ensuring that each discovery directly translates to better care, more effective treatments and improved quality of life for countless individuals worldwide.