Nematode mitochondrial metagenomics: A new tool for biodiversity analysis

Molecular characterization and prevalence assessment of Durettenema sp. (Nematoda: Trichostrongyloidea) in the great leaf-nosed bats (Hipposideros armiger) in South China

The viruses associated with bats have generated significant concern; however, there is limited knowledge regarding the endoparasites that affect these mammals. This study involved the collection of seven nematode specimens (three males and four females) from the intestines of Hipposideros armiger in Shaoguan City, Guangdong, China. Next-generation sequencing was employed to obtain the mitochondrial DNA (mtDNA) genome, which was determined to be 14,130 base pairs in length. The mitochondrial genome comprised 12 protein-coding genes, 21 tRNA genes, 2 rRNA genes, and an AT-rich non-coding region. Phylogenetic analyses based on mtDNA sequences indicated that the nematode forms a sister clade to Nematodirus, exhibiting only 74% nucleotide identity. In contrast, the nuclear ITS1 gene demonstrated a high degree of nucleotide identity (98.6%-98.8%) with Durettenema guangdongense. Consequently, the parasitic nematode identified from H. armiger is likely to belong to the genus Durettenema and has been designated as Durettenema sp. 888. Furthermore, an epidemiological investigation revealed the presence of the parasitic nematode infections in H. armiger collected from Guangdong, Guangxi, and Guizhou Provinces. Given the widespread distribution of H. armiger and their tendency to inhabit areas in close proximity to human dwellings, the influence of parasite prevalence on bat population numbers and potential for human and domestic animal transmission of this pathogen warrants further investigation.

High-Throughput Sequencing Enables Rapid Analyses of Nematode Mitochondrial Genomes from an Environmental Sample

Mitochondrial genomes serve as essential tools in evolutionary biology, phylogenetics, and population genetics due to their maternal inheritance, lack of recombination, and conserved structure. Traditional morphological methods for identifying nematodes are often insufficient for distinguishing cryptic species complexes. This study highlights recent advancements in nematode mitochondrial genome research, particularly the impact of long-read sequencing technologies such as Oxford Nanopore. These technologies have facilitated the assembly of mitochondrial genomes from mixed soil samples, overcoming challenges associated with designing specific primers for long PCR amplification across different groups of parasitic nematodes. In this study, we successfully recovered and assembled eleven nematode mitochondrial genomes using long-read sequencing, including those of two plant-parasitic nematode species. Notably, we detected Heterodera cruciferae in Victoria, expanding its known geographic range within Australia. Additionally, short-read sequencing data from a previous draft genome study revealed the presence of the mitochondrial genome of Heterodera filipjevi. Comparative analyses of Heterodera mitogenomes revealed conserved protein-coding genes essential for oxidative phosphorylation, as well as gene rearrangements and variations in transfer RNA placement, which may reflect adaptations to parasitic lifestyles. The consistently high A+T content and strand asymmetry observed across species align with trends reported in related genera. This study demonstrates the utility of long-read sequencing for identifying coexisting nematode species in agricultural fields, providing a rapid, accurate, and comprehensive alternative to traditional diagnostic methods. By incorporating non-target endemic species into public databases, this approach enhances biodiversity records and informs biosecurity strategies. These findings reinforce the potential of mitochondrial genomics to strengthen Australia's as well as the global biosecurity framework against plant-parasitic nematode threats.

Emerging Trends and Technologies Used for the Identification, Detection, and Characterisation of Plant-Parasitic Nematode Infestation in Crops

Accurate identification and estimation of the population densities of microscopic, soil-dwelling plant-parasitic nematodes (PPNs) are essential, as PPNs cause significant economic losses in agricultural production systems worldwide. This study presents a comprehensive review of emerging techniques used for the identification of PPNs, including morphological identification, molecular diagnostics such as polymerase chain reaction (PCR), high-throughput sequencing, meta barcoding, remote sensing, hyperspectral analysis, and image processing. Classical morphological methods require a microscope and nematode taxonomist to identify species, which is laborious and time-consuming. Alternatively, quantitative polymerase chain reaction (qPCR) has emerged as a reliable and efficient approach for PPN identification and quantification; however, the cost associated with the reagents, instrumentation, and careful optimisation of reaction conditions can be prohibitive. High-throughput sequencing and meta-barcoding are used to study the biodiversity of all tropical groups of nematodes, not just PPNs, and are useful for describing changes in soil ecology. Convolutional neural network (CNN) methods are necessary to automate the detection and counting of PPNs from microscopic images, including complex cases like tangled nematodes. Remote sensing and hyperspectral methods offer non-invasive approaches to estimate nematode infestations and facilitate early diagnosis of plant stress caused by nematodes and rapid management of PPNs. This review provides a valuable resource for researchers, practitioners, and policymakers involved in nematology and plant protection. It highlights the importance of fast, efficient, and robust identification protocols and decision-support tools in mitigating the impact of PPNs on global agriculture and food security.

Assessing the potential of nematode metabarcoding for benthic monitoring of offshore oil platforms

Environmental DNA metabarcoding is gaining momentum as a time and cost-effective tool for biomonitoring and environmental impact assessment. Yet, its use as a replacement for the conventional marine benthic monitoring based on morphological analysis of macrofauna is still challenging. Here we propose to study the meiofauna, which is much better represented in sediment DNA samples. We focus on nematodes, which are the most numerous and diverse group of meiofauna. Our aim is to assess the potential of nematode metabarcoding to monitor impacts associated with offshore oil platform activities. To achieve this goal, we used nematode-optimized marker (18S V1V2-Nema) and universal eukaryotic marker (18S V9) region to analyse 252 sediment DNA samples collected near three offshore oil platforms in the North Sea. For both markers, we analysed changes in alpha and beta diversity in relation to distance from the platforms and environmental variables. We also defined three impact classes based on selected environmental variables that are associated with oil extraction activities and used random forest classifiers to compare the predictive performance of both datasets. Our results show that alpha- and beta-diversity of nematodes varies with the increasing distance from the platforms. The variables directly related to platform activity, such as Ba and THC, strongly influence the nematode community. The nematode metabarcoding data provide more robust predictive models than eukaryotic data. Furthermore, the nematode community appears more stable in time and space, as illustrated by the overlap of nematode datasets obtained from the same platform three years apart. A significative negative correlation between distance and Shannon diversity also advocates for higher performance of the V1V2-Nema over the V9. Overall, these results suggest that the sensitivity of nematodes is higher compared to the eukaryotic community. Hence, nematode metabarcoding has the potential to become an effective tool for benthic monitoring in marine environment.

Comparative mitochondrial genomics in Nematoda reveal astonishing variation in compositional biases and substitution rates indicative of multi-level selection

BACKGROUND

Nematodes are the most abundant and diverse metazoans on Earth, and are known to significantly affect ecosystem functioning. A better understanding of their biology and ecology, including potential adaptations to diverse habitats and lifestyles, is key to understanding their response to global change scenarios. Mitochondrial genomes offer high species level characterization, low cost of sequencing, and an ease of data handling that can provide insights into nematode evolutionary pressures.

RESULTS

Generally, nematode mitochondrial genomes exhibited similar structural characteristics (e.g., gene size and GC content), but displayed remarkable variability around these general patterns. Compositional strand biases showed strong codon position specific G skews and relationships with nematode life traits (especially parasitic feeding habits) equal to or greater than with predicted phylogeny. On average, nematode mitochondrial genomes showed low non-synonymous substitution rates, but also high clade specific deviations from these means. Despite the presence of significant mutational saturation, non-synonymous (dN) and synonymous (dS) substitution rates could still be significantly explained by feeding habit and/or habitat. Low ratios of dN:dS rates, particularly associated with the parasitic lifestyles, suggested the presence of strong purifying selection.

CONCLUSIONS

Nematode mitochondrial genomes demonstrated a capacity to accumulate diversity in composition, structure, and content while still maintaining functional genes. Moreover, they demonstrated a capacity for rapid evolutionary change pointing to a potential interaction between multi-level selection pressures and rapid evolution. In conclusion, this study helps establish a background for our understanding of the potential evolutionary pressures shaping nematode mitochondrial genomes, while outlining likely routes of future inquiry.

Multi-omics resources for the Australian southern stuttering frog (Mixophyes australis) reveal assorted antimicrobial peptides

The number of genome-level resources for non-model species continues to rapidly expand. However, frog species remain underrepresented, with up to 90% of frog genera having no genomic or transcriptomic data. Here, we assemble the first genomic and transcriptomic resources for the recently described southern stuttering frog (Mixophyes australis). The southern stuttering frog is ground-dwelling, inhabiting naturally vegetated riverbanks in south-eastern Australia. Using PacBio HiFi long-read sequencing and Hi-C scaffolding, we generated a high-quality genome assembly, with a scaffold N50 of 369.3 Mb and 95.1% of the genome contained in twelve scaffolds. Using this assembly, we identified the mitochondrial genome, and assembled six tissue-specific transcriptomes. We also bioinformatically characterised novel sequences of two families of antimicrobial peptides (AMPs) in the southern stuttering frog, the cathelicidins and β-defensins. While traditional peptidomic approaches to peptide discovery have typically identified one or two AMPs in a frog species from skin secretions, our bioinformatic approach discovered 12 cathelicidins and two β-defensins that were expressed in a range of tissues. We investigated the novelty of the peptides and found diverse predicted activities. Our bioinformatic approach highlights the benefits of multi-omics resources in peptide discovery and contributes valuable genomic resources in an under-represented taxon.