Improving microbiome profiling with full-length 16S sequencing

Microbiome research often starts with a seemingly simple question: who is there? Getting a clear answer, however, depends largely on how closely researchers can look. In complex samples, particularly those collected from soil, plants, insects, and other heterogeneous environments, microbial diversity can easily be compressed into broad signals. Some organisms become difficult to distinguish, while others may be missed altogether if the sequencing method doesn’t provide enough resolution.

Image Credit:Shutterstock.com/ALIOUI Mohammed Elamine7 

This challenge is one reason researchers are taking a closer look at full-length 16S sequencing alongside more controlled PCR amplification approaches. Used together, these methods can reveal microbial diversity that conventional short-read workflows may leave unresolved. The webinar Who’s Really There? Long-read 16S and adaptive amplification reveal microbiomes you’ve been missing explores this in detail, looking at how long-read sequencing and iconPCR technology can increase unique ASV detection in complex microbial communities.

None of this means short-read 16S sequencing has lost its value. It remains widely used because it is scalable, well established, and effective for many community-level studies. The challenge is that researchers can see only a relatively small section of the 16S gene. When bacteria are closely related, the sequenced region may not contain enough variation to tell them apart.

That distinction can make a real difference. Closely related taxa do not necessarily behave in the same way or play the same biological role. When researchers group several organisms into one broad signal, they risk underestimating microbial diversity or missing ecological patterns that would otherwise be visible. They may also overlook strain-level changes with implications for health, agriculture, or environmental monitoring.

Full-length sequencing gives researchers more sequence information to work with. PacBio HiFi sequencing, for instance, generates highly accurate long reads by sequencing circularized DNA molecules multiple times and using those passes to create a consensus sequence. Applied to full-length 16S studies, it means variation can be examined across the entire gene instead of being inferred from a single, shorter variable region.

And that extra information can change what a sample appears to contain.

Dr. Charles Mason, a research biologist at USDA ARS, illustrated this with a study using agriculturally relevant microbiome samples. One example involved Mediterranean fruit flies. When the dataset was first analyzed using short-read V4 sequencing, the microbial community appeared dominated by a single Klebsiella ASV across cohorts and time points.

The same DNA told a different story when we re-examined it using full-length 16S sequencing with PacBio Kinnex. More ASVs became visible, along with greater structure and variability across the microbial community. In other words, what had initially appeared to be one overwhelmingly dominant signal turned out to contain a much richer and more diverse microbial landscape.

For agricultural microbiome research, that added resolution is particularly valuable. The study discussed in the webinar deliberately included samples that reflected the variability researchers encounter outside highly controlled experiments. These included different arthropod species as well as soil and leaf material, all of which can differ substantially in microbial biomass, composition, and biodiversity.

That variability creates another problem: even if sequencing provides enough resolution, sample preparation can introduce bias before sequencing ever begins.

PCR amplification is a key point where this can happen. In a conventional PCR workflow, researchers typically choose a fixed number of amplification cycles in advance and apply that number across samples. The difficulty is that samples rarely amplify at exactly the same rate. Some reach sufficient amplification relatively quickly, while others need considerably more time.

Applying the same cycle count to all of them can therefore create problems at both ends. Samples with high input or high microbial biomass may continue amplifying well beyond the point where enough material has been generated. That overamplification can increase the formation of chimeras and PCR duplicates, introducing technical artifacts into the library.

Those artifacts are not simply an inefficient use of sequencing capacity. They can reduce the number of reads that survive filtering and, more importantly, distort the representation of the original microbial community. Balancing read numbers later in the workflow cannot fully correct for this. Once errors and chimeric products are present in the amplified material, the underlying information has already been affected.

Adaptive amplification approaches the problem differently by controlling amplification while it is happening rather than trying to compensate afterward. n6’s iconPCR monitors real-time fluorescence in individually controlled wells, allowing each reaction to stop when it reaches the appropriate amplification endpoint. Its AutoNorm function keeps fast-amplifying or high-input samples from being pushed too far, while giving lower-input and slower-amplifying samples enough cycles to reach their target.

The webinar results showed what that difference means in practice. With a conventional 30-cycle PCR library, about 30% of sequences remained after filtering. In the autonormalized library, that figure increased to roughly 50%. Autonormalization also resulted in a more even distribution of samples and fewer chimeric reads, particularly compared with libraries produced under higher-cycle PCR conditions.

The workflow also benefited. More consistent amplification and normalization can reduce the manual preparation otherwise needed to balance samples before sequencing. During the webinar Q&A, Mason explained that for much of the 16S work presented, samples can move from extraction to PCR and then directly into pooling and Kinnex library preparation.

For laboratories working with many samples, often from different projects or users, reducing those intermediate steps can make the workflow considerably easier to manage. It also means less manual intervention at a stage where differences in sample handling can introduce additional variability.

Adaptive amplification is not entirely hands-off, however. You still need to consider key parameters. Samples with very high DNA concentrations may need to be diluted before PCR, and primer dimer formation needs to be kept under control for autonormalization to work effectively. AutoNorm settings and maximum cycle numbers may also need adjustment depending on the application.

The webinar offered a useful example of this. Many of the low-biomass 16S insect samples discussed used a maximum of 30 cycles, while some fungal ITS workflows may require fewer cycles because dimers can begin appearing later in the amplification process. Rather than assuming one PCR setup will suit every sample type, the workflow still needs to account for the biology and behavior of the material being analyzed.

Taken together, these developments point toward a broader shift in how complex microbiomes can be studied. Better sequencing resolution is only part of the equation. Researchers also need library preparation methods that preserve the biological differences already present in the sample instead of introducing technical variation that makes those differences harder to see.

Full-length 16S sequencing addresses one side of that problem by giving researchers a more informative genetic target. Adaptive amplification addresses another by controlling how researchers amplify that target before sequencing. Combining the two can provide a clearer picture of microbial communities, particularly in heterogeneous samples where differences in biomass and closely related taxa make analysis more difficult.

For complex microbiomes, the organisms researchers are looking for may already be present. The harder part is ensuring the workflow lets them be seen. With more complete 16S sequences and PCR amplification that responds to individual samples rather than treating them all identically, researchers can get closer to answering a more revealing version of that original question: not simply who appears to be there, but who has been there all along?

About n6

n6 is a genomics company focused on simplifying sample prep and helping scientists get better data, faster. As genomics scales, n6 believes workflows should become easier, not harder. Our instruments combine multiple workflow steps into one streamlined process, reducing complexity at any throughput. We partner closely with scientists to remove barriers in the lab and build the tools genomics has always needed, but never had.

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