DNA sequencing can identify viruses and other pathogens by reading their genetic material from a sample, then matching or classifying those sequences to reveal which organisms are present, even if they are new or unexpected.

Core Idea in Simple Terms

When you sequence DNA (or RNA converted to DNA), you get millions of short “reads” from everything in the sample: human cells, bacteria, fungi, and viruses.

Bioinformatic tools then:

  • Clean the raw reads and remove low‑quality data.
  • Subtract host (e.g., human) sequences using reference genomes.
  • Align the remaining reads to large databases of known microbial and viral genomes (like GenBank).
  • Assemble longer contigs to reconstruct partial or whole pathogen genomes.

If enough reads match a viral genome (or another pathogen), you infer that pathogen is present; if they match something only distantly, you may have found a novel variant or even a new virus.

How This Works for Viruses

Viruses can have DNA or RNA genomes, so the first step depends on the type.

  • DNA viruses: Their DNA is extracted and sequenced directly using next‑generation sequencing (NGS).
  • RNA viruses: Their RNA is first copied into complementary DNA (cDNA) using reverse transcriptase, similar to RT‑PCR for SARS‑CoV‑2, then sequenced.

Once sequenced, two main strategies are used:

  • Targeted sequencing : You enrich for a particular virus (or panel) using specific primers or capture probes, then sequence those regions to confirm presence and genotype (for example, influenza, hepatitis, HPV).
  • Metagenomic (untargeted) sequencing : You sequence everything in the sample without prior assumptions, then classify reads computationally to detect known and unknown viruses in one run.

This enables:

  • Detection of mixed infections and co‑circulating viruses.
  • Discovery of highly divergent or emerging viruses that standard PCR panels might miss.

Extending Beyond Viruses: Other Pathogen Classes

Exactly the same sequencing logic can be applied to bacteria, fungi, and parasites; the main difference is the databases and analysis filters you use.

  • Bacteria
    • Whole‑genome sequencing (WGS) reads are mapped to bacterial genome databases to identify species and sometimes strain.
* 16S rRNA gene sequencing targets a conserved bacterial gene region to profile bacterial communities (microbiome) and detect potential pathogens.
  • Fungi
    • Internal transcribed spacer (ITS) region sequencing is a common fungal “barcode” to identify yeasts and molds.
* WGS of fungal pathogens can track outbreaks and antifungal resistance markers.
  • Parasites and other eukaryotic pathogens
    • Specific marker genes or whole genomes (e.g., Plasmodium, Trypanosoma) can be sequenced and compared to parasite databases.

Because metagenomic NGS does not require prior targeting, one dataset can simultaneously reveal viruses, bacteria, fungi, and parasites present in a sample.

Here is a compact view:

[7][5] [10][8] [8][6] [6][8]
Pathogen class What is sequenced? Typical use
Viruses Whole genome (DNA or cDNA from RNA) Detect known/novel viruses, variants, outbreak tracing.
Bacteria Whole genome or 16S rRNA gene Species/strain ID, resistance genes, microbiome profiling.
Fungi ITS region or whole genome Identification of clinical and environmental fungi.
Parasites Marker genes or whole genome Species ID, epidemiology, drug resistance markers.

Example Story: Finding a Hidden Virus in a Gut Sample

Imagine a patient with severe diarrhea where routine tests (culture, PCR panels) are negative. Clinicians send a stool sample for metagenomic sequencing.

  1. All nucleic acids are extracted and host DNA is reduced where possible (e.g., by filtering or enzymatic digestion).
  1. The remaining material is converted to a sequencing library and run on an NGS platform, generating millions of reads.
  1. Bioinformatics removes human reads, then compares the rest against nucleotide databases.
  1. Most reads match normal gut bacteria, but a cluster of reads aligns to a poorly characterized viral genome from the “gut virome” in public databases.
  1. Assembly reconstructs a nearly complete viral genome; its divergence suggests a new strain or potentially a novel virus associated with the illness.

This kind of workflow—now routine since the COVID‑19 era—shows how sequencing turns a complex mixture into a detailed map of all pathogens present, including unknown ones.

Strengths and Limitations

Strengths

  • Detects a wide range of pathogens in one test, including unexpected or novel agents.
  • Provides genome‑level detail for strain typing, resistance genes, and evolutionary analysis.
  • Helps in outbreak tracking and surveillance (e.g., SARS‑CoV‑2 variant monitoring).

Limitations

  • Cost, turnaround time, and bioinformatics complexity are still higher than standard PCR in many settings.
  • Distinguishing clinically relevant infection from harmless colonization or background virome/bacteriome can be difficult.
  • Sensitivity can be limited when pathogen load is low or host/background DNA is overwhelming.

So, DNA (and RNA) sequencing has become a powerful, general‑purpose tool to detect and characterize viruses and other pathogens across different classes, complementing but not completely replacing targeted diagnostic tests.

Information gathered from public forums or data available on the internet and portrayed here.