Offering greater speed, lower cost, and higher throughput than first-generation methods, next-generation sequencing (NGS) has propelled biological research into a new era. Whole-genome sequencing, epigenomics, metagenomics, and microbiomics are just a few of the many NGS applications today that are enabling advances in epidemiology, cancer diagnostics, and pharmaceuticals.
Offering greater speed, lower cost, and higher throughput than first-generation methods, next-generation sequencing (NGS) has propelled biological research into a new era. Whole-genome sequencing, epigenomics, metagenomics, and microbiomics are just a few of the many NGS applications today that are driving advances in epidemiology, cancer diagnostics, and drug discovery, and greatly improving our understanding of biology. An understanding of how organisms use genetic information to survive and reproduce in their environment. Changing environment.
With a variety of sequencing instruments and service providers on the market, NGS is rapidly being embraced by laboratories of all sizes and budgets. While sequencing and data analysis are often automated, the upstream NGS steps, namely sample processing and library preparation, are often performed manually. Fortunately, with some effort and optimization, these steps can be easily automated on a pipetting robot, saving the user a lot of potential headaches. Here, we look at the top 5 reasons to automate your NGS workflow.
Scalability
If you've ever tried to manually process large numbers of NGS-bound samples, the potential for scale-up should get you excited about automation. The exact capabilities of the robot depend on the model, but in most cases you will be able to process up to 96 samples simultaneously, significantly reducing the time required to manually process the same number of samples.
Automation also saves you the dreaded hassle of batch processing of samples, which is often necessary in manual setups due to centrifuge size, risk of sample degradation (e.g. when working with RNA), and maximum quantity limitations. Samples that people feel comfortable handling at all times. More important than avoiding trouble, fewer batches means less or no batch-to-batch variation.
2.Innovation
Scaling NGS experiments through automation will inevitably allow you to solve new research questions that are nearly impossible to solve with manual setups. Here are a few examples of a range of NGS applications:
Drug discovery: Screening large numbers of novel compounds to look for desired transcriptional or epigenetic changes in disease material (e.g., cell lines) rather than trying to single out compounds that may have therapeutically relevant effects.
Microbiomics: Analyze a large enough sample set to get a picture of the "normal" microflora in your species of choice. This would be an impossible task if you could only process 12 or 24 samples at a time.
Plant breeding: Large-scale identification of agronomically important genes and genetic markers to aid genomic selection and genetic engineering to develop new varieties with highly desirable traits.
Disease research and diagnosis: Screening large clinical samples to discover new disease-related genes or biomarkers.
Environmental monitoring: Assessing the health of an ecosystem through qualitative and quantitative sequence analysis of its invertebrate inhabitants.
In addition to increasing your own research innovation, higher throughput should prompt greater collaboration with other labs, opening the door to new projects and discoveries that would otherwise be very challenging (if possible).
Consistent data quality
Throughout the NGS workflow, sample processing, library construction, and downstream processing steps such as PCR amplification and library standardization are particularly prone to human error. The protocol is lengthy, with many pipetting steps and changing reagent volumes, and often requires transferring samples to new tubes along the way. Incorrect labeling, contamination, pipetting errors, or the slightest deviation from the protocol can significantly impact the resulting data.
Even if human error is entirely unavoidable, variation between batches and sample handling between workers is unavoidable. It would also be impractical, if not impossible, to monitor these errors and changes in the NGS workflow. Automated sample and library preparation alleviates this problem, providing better process control, accurate and efficient workflows, and better run reproducibility independent of personnel changes, so whether you have 1 sample or 1,000, you can deliver Reliability and consistent data quality.
Increase time away
It's not entirely black and white, as you'll need to invest some time and effort in the startup phase to ensure your pipetting robot can perform strict protocols. If you're lucky, you might be able to find a script for your robot from its supplier or the supplier of your chosen nucleic acid extraction and library preparation kit, many of which work with automation vendors to develop automation-ready protocols.
Regardless, once your automation setup is up and running, you can enjoy spending valuable lab time planning new critical experiments rather than repetitive sample and library preparation. Automation can also reduce the effort required to train staff on multiple different protocols, freeing up more resources and preventing staff from repetitive strain injuries caused by excessive pipetting.
Reduce costs
Depending on your current resources, there may be considerable expenditure during the setup and optimization phase, for example you will need to obtain a pipetting robot if your laboratory does not already have one. You'll also need to spend time programming the robot to perform various protocols. However, once your automation setup is up and running, the savings in staff training and sample processing time as well as the avoidance of material and reagent losses due to human error can translate into significant cost savings, especially when NGS is a routine and critical part when doing your research.
Can you automate work?
Don’t worry, even the best automation setup can’t completely eliminate the need for human intervention. You still need to incorporate quality control checks