Omics technologies continue to expand diagnostic opportunities in parasitology. Following his presentation at ESCMID Global 2026, Francesco Asnicar, Researcher at the University of Trento, discusses how metagenomic tools are improving parasite detection, revealing hidden microbial diversity, and advancing understanding of parasite ecology and transmission.
From a diagnostic perspective, what limitations in current parasitology testing is metagenomics helping to overcome?
Current parasitology testing still relies heavily on microscopy, culture, and targeted PCR assays, which require prior suspicion of a specific organism and may miss low-abundance or unexpected pathogens.
Shotgun metagenomics sequences all DNA within a sample, enabling simultaneous detection of multiple microorganisms, including parasites. However, many analytical pipelines remain focused on prokaryotes and may not adequately detect eukaryotic parasites such as Blastocystis, Giardia, and Dientamoeba. Further development of non-prokaryotic pipelines will be important for clinical implementation.
How does metagenomic sequencing improve the detection of parasites, particularly in cases where traditional methods may miss low-abundance or unexpected pathogens?
Metagenomics can use species-specific computational pipelines to detect organisms such as Blastocystis, Giardia, and Dientamoeba by mapping sequencing reads to reference genomes and reconstructing genomes through metagenomic assembly. This allows identification of both known and previously uncharacterized organisms and supports phylogenetic analysis.
Sensitivity remains a challenge for low-abundance pathogens because very low organism levels may not generate enough sequencing reads for reliable detection.
What role can metagenomics play in routine screening and monitoring of parasitic infections in clinical laboratories?
Metagenomics may support longitudinal monitoring. In our data, more than 95 percent of individuals remained consistently Blastocystis-positive or -negative over a median follow-up of 180 days, and nearly all positive individuals retained the same subtype over time.
However, routine implementation still faces barriers including sequencing costs, turnaround times, and the lack of standardized protocols and parasite reference databases.
How are proteomics approaches complementing metagenomics in parasite detection and characterization?
The approaches are complementary. Metagenomics identifies which organisms and genes are present, whereas proteomics provides information about which proteins are actively expressed. Together, they may provide a more complete picture of parasite biology and activity.
What are the main challenges faced by laboratories when implementing metagenomics for parasitology?
A major challenge is establishing standardized workflows – spanning sample collection, DNA extraction, sequencing, quality control, and computational analysis – that generate reproducible results across laboratories.
Detection sensitivity also depends heavily on high-quality reference genomes, which remain limited for many rare parasite subtypes. Another challenge is balancing false positives and false negatives: stringent thresholds may miss true infections, while permissive approaches may introduce clinically irrelevant background noise.
How do you address issues such as contamination, sensitivity, and distinguishing clinically relevant findings from background noise?
In microbiome studies, contamination mainly refers to host-derived DNA, which is removed through preprocessing pipelines before microbial analysis.
For Blastocystis, we validated a conservative threshold requiring at least 10 percent breadth of coverage across a reference genome to confidently identify a subtype. Distinguishing clinically relevant findings from background noise remains difficult at the individual level, although large-scale meta-analyses may help identify broader prevalence patterns across healthy and diseased populations.
What opportunities does metagenomics offer for surveillance and tracking of parasitic diseases at a population level?
Metagenomics is well suited for population-scale surveillance because it can profile the entire microbial community within a sample. In our work, we identified geographic differences in Blastocystis prevalence across 32 countries and linked these patterns to lifestyle, diet, and host health factors.
Strain-level analyses may also support transmission studies. For example, we found that Blastocystis was largely absent in newborns and showed no evidence of vertical transmission, suggesting acquisition occurs later through environmental or interpersonal exposure.
Looking ahead, how do you see metagenomics and proteomics shaping the future of parasitology diagnostics in clinical and public health settings?
An important next step is expanding computational frameworks to better capture non-prokaryotic components of the microbiome, including fungi, protists, and parasites, which are often overlooked in standard pipelines.
As reference databases and validation methods improve, metagenomics may support applications such as donor screening for fecal microbiota transplantation, public health surveillance, and microbiome-targeted interventions. A key challenge will be translating large observational datasets into clinically actionable diagnostic tools.
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