Researchers from the University of Florida surveyed nematode communities in four strawberry fields in Hillsborough County, three managed conventionally and one managed organically. Sampling took place in June 2021, roughly two months after the strawberry crop was terminated, when soil temperatures were among the hottest of the year. Using a gas-powered auger, the team collected soil cores from four separate depths, from the surface down to one metre, at known hot spots of the northern root-knot nematode, Meloidogyne hapla, a pest likely introduced to Florida on infected transplants from out-of-state nurseries.

Each sample was split and processed two ways. The traditional approach involved extracting live nematodes from the soil using centrifugal flotation, counting them under an inverted microscope and identifying plant parasites to genus or species by morphology, while free-living worms were assigned only to broad trophic groups. The second approach was a targeted form of mitochondrial metagenomics, or mtMG. Whole DNA was extracted from the entire nematode suspension, sequencing libraries were prepared and then enriched for mitochondrial DNA using hybridisation capture probes designed against nematode mitochondrial genomes. The samples were sequenced on an Illumina NovaSeq 6000, and the resulting reads were assembled into contigs and matched against a curated nematode mitochondrial reference database.

The molecular workflow required careful quality control. Of 301 contigs that passed initial classification, 35 were discarded after phylogenetic tree analysis revealed poor alignments suggestive of misidentification, a problem concentrated in the suborder Tylenchina. The team also screened for haplotypes, closely related sequence variants within species, using maximum likelihood trees with bootstrap support, distinguishing genuine population diversity from assembly errors. This conservative filtering proved essential for trustworthy species-level detections.

The comparison revealed significant differences in both richness and composition between the two methods. The annotated COX1 mtMG approach, which identified mitochondrial contigs by open reading frame annotation rather than read mapping, recovered far more taxa than the read-mapping variants and came closest to mirroring the morphological data. It tentatively identified 14 bacterial-feeding species across nine genera that morphology could only label as ‘bacterial feeders’, and it detected animal-parasitic nematodes, likely present as eggs or unidentifiable juvenile stages, that microscopy missed entirely in every sample.

Yet the molecular method had its own blind spots. Morphology detected plant parasites such as the sting nematode Belonolaimus longicaudatus, Nanidorus minor and Tylenchorhynchus species that mtMG failed to recover, almost certainly because their mitochondrial reference sequences are missing from the database. Conversely, mtMG picked up Mesocriconema species and the dagger nematode Xiphinema brevicollum that microscopy had not found. The two approaches also disagreed on omnivores and predators, which appeared only in the morphological counts, probably because their low abundance meant too few sequencing reads to assemble.

Where the methods agreed, the agreement was powerful. Both consistently detected Meloidogyne across all fields, and mtMG went further, precisely identifying M. hapla in three fields while also revealing the co-occurrence of M. javanica, M. incognita and M. luci in the organic field, along with multiple haplotypes of M. hapla that morphology cannot distinguish. This capacity to resolve species and population-level variation matters enormously, because species identity can dictate which management strategy a grower should adopt, and haplotype diversity has been linked to emerging nematicide resistance.

Despite their differences in detected taxa, both methods converged on the same ecological conclusions. Field identity was the dominant factor structuring nematode community composition, reflecting each field’s distinct management history, and sampling depth played a significant role as well. The mtMG data in particular showed that Meloidogyne species were recovered throughout the entire one-metre soil column, supporting earlier evidence that plant-parasitic nematodes migrate vertically through Florida’s deep sandy soils, likely in response to heat, tillage or fumigation. This vertical movement has practical implications, since deep soil layers may act as reservoirs from which root-knot populations re-establish after fumigation.

The authors conclude that mtMG and morphology are highly complementary tools, and that combining them yields a far more accurate picture of nematode diversity than either alone. They identify four priorities for improving the molecular approach: expanding the phylogenetic coverage of the mitochondrial reference database, refining contig filtering and classification pipelines, improving detection of under-represented trophic groups such as omnivores and predators, and adding reference sequences for rare crop pests. As the database grows, mtMG should become increasingly capable of flagging subtle genetic variants, including nematicide-resistant haplotypes, giving growers an earlier warning than morphology could ever provide.

For Florida’s strawberry industry, which produced roughly 511 million dollars’ worth of fruit in 2022 across some 12,000 acres, the stakes are considerable. Sting and root-knot nematodes remain among the most damaging pests growers face, and management increasingly relies on targeted, environmentally sustainable approaches rather than broad-spectrum fumigants. Accurate, species-level monitoring of entire nematode communities, the kind of monitoring this study shows is achievable when molecular and morphological methods are deployed together, could become a cornerstone of that transition.

Subject of Research: Comparison of mitochondrial metagenomics and morphological identification for surveying nematode communities in strawberry fields

Article Title: Improving understanding of nematode communities in agricultural settings: a comparison of mitometagenomics and morphology

Article References: Gendron, E. M. S., Oliveira, C. J., Desaeger, J., & Porazinska, D. L. (2024). Improving understanding of nematode communities in agricultural settings: a comparison of mitometagenomics and morphology. Metabarcoding and Metagenomics, 8, Article e123387. https://doi.org/10.3897/mbmg.8.123387

Image Credits: AI Generated

DOI: 10.3897/mbmg.8.123387

Keywords: nematodes, mitochondrial metagenomics, morphology, strawberry, Florida, plant-parasitic nematodes, Meloidogyne, soil biodiversity, metabarcoding, agriculture, soil depth, pest management