Learn how a strategic, targeted approach can help you detect your microbe of interest even when it makes up less than 1% of your sample.

Much of what we know about microbial communities has come from metagenomic studies. These high-throughput approaches have allowed us to map taxonomic diversity and relative abundances of species, understand the functional metabolic potential of complex samples, and even reveal the existence of microbes that have resisted isolation via traditional culture techniques. Metagenomics has also shown us how microbiome composition and activity can shift dramatically in response to illness or environmental stressors.

However, broad-brush approaches often reach a limit when the research objective shifts from “what is there” to “exactly which strain is there and what is its functional potential.” In complex samples such as human tissue, wastewater, or soil, the microbial targets of interest are frequently buried under a mountain of background noise. When 99% or more of your sequencing reads belong to the host or a dominant environmental species, the rare pathogens or specific functional genes you need to see remain invisible.

Target enrichment via hybridization capture changes this dynamic. By using target-specific RNA “baits” to physically pull sequences of interest from a DNA mixture, researchers can achieve the sensitivity and depth required for strain-level resolution, including novel polymorphisms.

 

The sensitivity gap in complex samples

Standard sequencing methods often fail in high-background environments for three reasons:

  1. Assay sensitivity: In shotgun metagenomics, rare microbes are often missed because the sequencing depth required to see them is economically unfeasible.
  2. Amplification bias: Target sequencing via PCR amplification is a powerful traditional approach, but is limited by short read lengths and primer bias. If a new strain has a mutation at a primer binding site, it essentially disappears from the data.1
  3. Sample degradation: Microbial DNA that is degraded may not be successfully amplified, sequenced, or detected, especially in complex samples.

Hybridization capture addresses these hurdles by allowing probes to capture sequences even with slight differences from the reference, enabling the discovery of new variants, more comprehensive and accurate microbial community profiling, and/or better pathogen genome assembly. For a deeper look at these differences, see our comparison: Hybridization capture vs. amplicon sequencing: When and why it matters.

 

Evidence in action: deep microbial sequencing case studies

The technical heavy lifting of hybridization capture is best seen in recent peer-reviewed applications. These studies demonstrate how target enrichment moves the conversation from broad identification to precise genomic characterization.

Mapping the resistome in environmental samples

Antimicrobial resistance (AMR) is one of the most significant challenges in public health. In a 2021(a) study, Beaudry et al. validated a resistome hybridization bait set consisting of 19,933 unique probes targeting 3,565 unique nucleotide sequences that confer resistance.2 The method was tested in both a mock microbial community and complex environmental samples, achieving an increase in the proportion of on-target reads by as much as >200-fold. Hybridization capture identified 18 classes of resistance and 318 total resistance genes in poultry litter samples, which was significantly more compared to the six classes of resistance and 33 total resistance genes identified in the non-enriched libraries.

Key takeaway: Target capture can accurately profile AMR genes in environments where traditional metagenomics lacks the depth to provide a complete picture of the resistome.

High-resolution 16S rRNA characterization

While amplifying and sequencing a subset of the 16S variable regions is a staple of microbiome analysis, it often lacks the resolution to distinguish between species. Beaudry (2021b) et al. developed an extensive 16S rRNA bait set to offer a middle ground between shotgun metagenomics and amplicon sequencing.3 This approach targeted the full 16S rRNA gene and provided characterization that performed as well as metagenomic sequencing in both mock and complex environmental samples, but with significantly lower read requirements and streamlined data analysis.

Key takeaway: Hybridization capture of the full 16S gene enables economical, high-resolution strain-level identification within complex samples while simplifying data analysis.

Pathogen surveillance: Cryptosporidium spp. and Borna disease virus

For rare pathogen detection, the signal-to-noise ratio is the primary obstacle.

In 2024, Bayona-Vasquez used a bait set to enrich multiple species of human-infecting Cryptosporidium spp. from a wide range of sample types.4 This comprehensive full-genome bait set increased both the breadth and depth of sequencing coverage, allowing for accurate pathogen detection and species identification that would have been impossible without standard methods.

Key takeaway: Hybridization capture facilitates the accurate detection and identification of target species within complex samples while decreasing costs associated with traditional metagenomic analysis.

In a 2024 molecular epidemiology study, Ebinger et al. used bait sets and NGS to connect clinical disease cases in humans and animals to specific geographic regions.5 The high-resolution data allowed researchers to perform in-depth phylogeographic analysis, tracing the spread of the virus with high confidence.

Key takeaway: In-depth phylogenetic analysis of human and animal viral samples, powered by hybridization capture, enables resolution of disease transmission dynamics and visualization of regions with higher risk for exposure.

Tracking AMR spread via plasmid host detection

Understanding how AMR spreads requires looking at mobile genetic elements like plasmids. In 2025, Casteneda-Barba et al. used a targeted Hi-C approach combined with bait sets to enrich for plasmid-specific DNA in complex soil communities.6 This allowed the team to identify rare plasmid hosts and better understand the transfer dynamics that drive the spread of resistance in the environment.

Key takeaway: The combination of Hi-C with target capture enables a lowering of the limit of detection for a method designed to link plasmids with their host bacteria, enabling researchers to better detect novel plasmid transfer between hosts in complex microbial communities.

 

Precise tools for complex questions

When your research requires finding a rare strain in a sea of host DNA and/or RNA, or mapping every resistance gene in a wastewater sample, a “broad” sequencing approach often lacks sufficient sensitivity to deliver the high-resolution data you need. Hybridization capture provides a path to deeper insights by focusing your sequencing budget exactly where it matters: directly on your targets of interest.

Whether you are using myBaits Expert Predesigned Panels for known pathogens or designing a custom panel for a unique environmental target, our scientific team is available to help you design a solution that fits your specific research aims.

 

References

  1. Ceballos-Garzon. Applying targeted gene hybridization capture to viruses with a focus to SARS-CoV-2. (2024) doi: 10.1016/j.virusres.2023.199293
  2. Beaudry, M. Escaping the fate of Sisyphus: assessing resistome hybridization baits for antimicrobial resistance gene capture. (2021a) https://doi.org/10.1111/1462-2920.15767
  3. Beaudry, M. Improved Microbial Community Characterization of 16S rRNA via Metagenome Hybridization Capture Enrichment.(2021b) https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2021.644662/full
  4. Bayona-Vasquez, NJ. Whole genome targeted enrichment and sequencing of human-infecting Cryptosporidium spp. (2024) doi: 10.21203/rs.3.rs-4294842/v1
  5. Ebinger, A. Lethal Borna disease virus 1 infections of humans and animals-in-depth molecular epidemiology and phylogeography. (2024) https://www.nature.com/articles/s41467-024-52192-x
  6. Casteneda-Barba, S. Detection of rare plasmid hosts using a targeted Hi-C approach. (2025) https://doi.org/10.1093/ismeco/ycae161

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