September 5, 2024

4 Ways to Get More Microbial Reads for Less Cost

Metagenomic next-generation sequencing (mNGS) has become a crucial tool in microbiome research, infectious disease studies, and clinical diagnostics. However, optimizing mNGS workflows to get more microbial reads while minimizing costs remains a significant challenge. Common obstacles include high host cell content, sample contamination, under-optimized sequencing depth, and the complexities of bioinformatic analysis.

Addressing these challenges can lead to more reliable and actionable results without inflating sequencing costs. Here are four effective ways to achieve more microbial reads for less cost in your mNGS projects:

1. Minimize Host DNA Interference to Get More Microbial Reads

One of the biggest challenges in mNGS is the overwhelming presence of host genetic material, which can dominate sequencing reads and obscure microbial signals. Host interference reduces the sensitivity of detecting pathogens or other microbes and increases the sequencing depth required, driving up costs. Implementing a host depletion step before sequencing can significantly enrich microbial reads as seen in this study. Host depletion allows for a more focused sequencing effort on microbial content, ultimately reducing the number of sequencing reads needed and cutting down on expenses.

The Devin™ Host Depletion filter by Micronbrane Medical offers a novel, efficient approach that overcomes the challenges associated with traditional methods. Read the White Paper!

Nucleated Host Cell Depletion with High Microbial Passing Efficiency — Utilizes Zwitterionic Interface Ultra-Self-assemble Coating (ZISC) technology to remove 99% of host DNA while allowing over 90% of microbial cells to pass through unaltered.
Versatility Across Sample Types — The Devin filter works with a wide range of samples, including complex fluids like blood, without the need for pre-extracted DNA, providing consistent results.
Quick and Simple Workflow — With our filter host depletion is complete in under 5 minutes, unlike other methods that require lengthy and complex protocols, making Devin ideal for high-throughput and urgent applications.
Cost-Effective and Compatible — By reducing host cells, deep sequencing is unnecessary, which lowers costs, and enables compatibility with a wide variety of downstream protocols.

2. Streamline mNGS Workflow to Reduce Contamination

Contamination is a persistent problem in mNGS workflows, which can lead to inaccurate results and wasted sequencing runs. Establishing a streamlined, contamination-aware workflow can significantly improve the integrity of sequencing data. This involves using dedicated workspaces, employing stringent contamination controls, and optimizing each step of the workflow to minimize cross-contamination risks. Incorporating system controls and no-template controls (NTCs) is also essential to monitor and detect potential contamination throughout the process, ensuring that any background signals are accounted for. Reducing contamination and using these controls not only increases confidence in your results but also eliminates the need for costly re-sequencing and additional analyses, thereby keeping overall costs low. For a step-by-step protocol covering every stage from sample collection to bioinformatics filtering, see Metagenomics Sample Prep: How to Reduce Contamination at Every Step.

Devin Microbial Enrichment Kit

The Devin Microbial Enrichment Kit addresses contamination issues in mNGS workflows by utilizing ultra-clean, mNGS-grade reagents that significantly reduce the risk of cross-contamination and ensure high-quality sequencing data. By incorporating our mNGS-grade reagents into your workflow, the Devin Kit simplifies the extraction process and enhances the reliability of sequencing results. The Devin Microbial Enrichment Kit can lower the risk of false positives, ultimately reducing costs associated with data validation and quality control, providing you with greater confidence in your findings.

What does mNGS-grade mean? We coined this term because our kits:

This transparency allows you to reduce the risk of unexpected variables impacting your sequencing results.

3. Match Sequencing Depth and Multiplexing to Your Workflow

Understanding where mNGS costs accumulate is essential for targeting the right optimizations. Host DNA interference is the single largest cost driver: without pre-sequencing depletion, laboratories must sequence far deeper to capture enough microbial signal. That deeper sequencing inflates reagent costs, demands more data storage, and increases the computational intensity of downstream analysis.

With effective host depletion reducing human reads by approximately 99%, the PaRTI-Seq workflow can identify pathogens with as few as 5 million reads — compared to the 20 million or more reads required by standard protocols. This means laboratories can process four times more samples per sequencing run, cutting the per-sample sequencing cost by 75%.

Host depletion also enables laboratories to use lower-cost sequencing hardware effectively. The ONT Flongle flow cell costs approximately $90 per run. Without host depletion, its limited throughput (roughly 2.6 Gb) would be consumed almost entirely by human reads. With the Devin filter removing 99% of host DNA beforehand, that same $90 run produces actionable microbial data.

Host-depleted samples processed through the full Micronbrane workflow produce 10 to 1,000 times more microbial reads compared to standard protocols. This improvement in microbial read fraction means laboratories achieve diagnostic-quality results at a fraction of the sequencing depth, translating directly to lower reagent consumption and faster turnaround times. For a deeper dive into cost reduction strategies with data from real mNGS workflows, see 4 Strategies for Reducing mNGS Costs Per Sample.

4. Enhance Bioinformatics Analysis for Accurate Pathogen Detection

Efficient and precise data analysis methods are essential for identifying and quantifying microbial species accurately. Utilizing bioinformatic platforms and algorithms that are specifically tailored for mNGS data can improve the accuracy and sensitivity of pathogen detection.

Our bioinformatics pipeline was four years in the making and streamlines the analysis of mNGS data using our Pathogen Real-Time Identification by Sequencing (PaRTI-Seq) assay. For researchers, PaRTI-Seq RUO Analysis is available for free with a code in the PaRTI-Seq Kit.

Conclusion

It is possible to get more microbial reads at a lower cost. By minimizing host DNA interference, streamlining workflows to reduce contamination, right-sizing sequencing depth and throughput, and enhancing bioinformatic analysis, you can significantly improve the cost-effectiveness and reliability of your mNGS projects.

Library prep for low-biomass and host-depleted samples is a topic in its own right — for a kit-by-kit comparison across input ranges and sequencing platforms, see Best NGS Library Prep Kits for Metagenomic Sequencing.

If you’re looking for an end-to-end solution to address these challenges, consider integrating Micronbrane Medical’s PaRTI-Seq assay into your mNGS workflow. PaRTI-Seq is designed to optimize each of these critical steps, offering an efficient approach to metagenomic sequencing that maximizes microbial reads while minimizing costs.