Mitogenomic characterisation of non-native freshwater snails in Australia: Implications for biosecurity and trematode vector surveillance

Abstract

Freshwater snails play essential roles in the transmission of trematode parasites that affect humans, livestock and wildlife. Australia's freshwater ecosystems are increasingly influenced by non-native and potentially invasive snail species that may pose biosecurity challenges and alter parasite transmission dynamics. This study characterised the complete mitochondrial genomes for four non-native snail taxa established in Australia (Pseudosuccinea columella, Orientogalba viridis, Physa acuta and Planorbella sp.) and for Galba truncatula, a high-priority exotic species considered a potential invader. Using long-read sequencing and comparative analyses, 15 complete mitogenomes were assembled, annotated and compared across three families (Lymnaeidae, Physidae and Planorbidae). Genome sizes ranged from 13.7 to 14.3 kb and exhibited conserved gene organisation and marked A + T bias. Australian populations of P. columella, O. viridis and Ph. acuta showed very limited mitochondrial nucleotide variability, consistent with founder effects, demographic bottlenecks and self-fertilisation, in contrast to the marked divergence observed among lineages within Galba from European laboratory strains. Phylogenetic inference based on concatenated and single-gene (cytochrome c oxidase subunit 1, cox1) datasets confirmed well-resolved family-level relationships and revealed cryptic diversity within Galba. The mitogenomes defined here provide molecular references for future taxonomic studies, diagnostic assay development and environmental (e)DNA monitoring of freshwater snails. These genomic resources establish a basis for biosecurity preparedness and vector surveillance in Australia and contribute to a broader One Health approach by supporting early detection, accurate identification and risk assessment of trematode-transmitting snails in freshwater ecosystems.

1. Introduction

Invasive freshwater snails are key agents of ecological disruption and disease transmission worldwide [1], [2]. Their establishment in new environments can displace native mollusc fauna, alter ecosystem functions and introduce transmission pathways for trematode diseases (trematodiases), including fascioliasis, schistosomiasis and echinostomiasis, which affect humans, livestock and wildlife [1], [3]. Globalisation, trade and the aquarium industry have accelerated their spread, creating new invasion pathways and opportunities for parasite emergence across continents [2], [3], [4]. However, despite their growing importance at the interface of biodiversity, agriculture, and public health, invasive snail vectors remain poorly characterised at the genomic level, limiting our ability to identify species accurately, trace introductions and assess their biosecurity risk.

Australia is particularly vulnerable to these emerging invasions. Its endemic freshwater snail fauna is both diverse and evolutionarily unique, yet increasingly exposed to non-native taxa introduced through urbanisation, agriculture and aquarium trade [5], [6]. The establishment of such species poses dual threats: ecological competition with native taxa and the potential introduction or intensified transmission of trematodes of veterinary and public-health concern. Fascioliasis, caused by Fasciola hepatica, is one of the most important trematode diseases of livestock [7] and, although primarily a veterinary concern in Australia [8], is a recognised zoonotic disease [7]. While native Austropeplea species serve as the principal intermediate host [9], several exotic lymnaeids, including Pseudosuccinea columella, Orientogalba viridis, Stagnicola palustris, Lymnaea stagnalis and Radix peregra have been recorded in Australia, with the first two species being the most encountered [5], [10]. Understanding the identity, diversity and potential vector capacity of these introduced snails is, therefore, critical for managing future transmission risks and safeguarding endemic biodiversity.

Despite extensive morphological study of Australian freshwater snails [5], molecular information remains limited; most studies have relied on individual mitochondrial (e.g., cox1 and 16S) or nuclear ribosomal markers (e.g., internal transcribed spacers, ITS) that can yield conflicting phylogenetic relationships [11]. Such limitations have hindered accurate species identification, particularly within morphologically plastic genera such as Galba and Radix [12], [13]. Complete mitochondrial genomes (mitogenomes) provide a resource for designing robust primers and, consequently, more reliable markers for molecular identification and characterisation, as well as environmental DNA (eDNA) surveillance [14], [15].

In this context, there remains a critical need for comprehensive genomic resources to improve the identification of introduced freshwater snail taxa in Australia. Mitogenomic data are critical for One Health by enabling accurate assessment of invasion dynamics, clarifying taxonomic boundaries and supporting biosecurity surveillance for snail vectors of parasites of veterinary and public-health importance. Here, we undertook an integrated mitogenomic investigation of some freshwater snails representing three key families (Lymnaeidae, Physidae and Planorbidae), known or suspected to include intermediate hosts of trematodes. The long-read sequencing and analytical platform established provides a foundation for extensive systematic studies as well as for the monitoring and risk assessment of invasive gastropods in Australasia. This study provides the first comparative mitogenomic framework for invasive freshwater snails in Australia and establishes essential genomic baselines for future ecological, parasitological and biosecurity research.

2. Materials and methods

2.1. Snail collection and DNA isolation

We collected snail specimens from freshwater bodies, pet-store aquaria and laboratory cultures (Table 1). The snails were immediately preserved in RNAlater, stored at 4 °C overnight and transferred to −20 °C for long-term storage. For DNA extraction, we excised foot tissue (50 mg) from each individual, rinsed it in nuclease-free water and homogenised the sample in a 1.5 mL microtube using Eppendorf® micropestles (Eppendorf, Germany). DNA was extracted using the E.Z.N.A. Mollusc DNA Kit (OMEGA Bio-tek, USA), and concentration measured using a Qubit® 3.0 fluorometer with the High-Sensitivity Assay (Life Technologies, Carlsbad, CA, USA).

Table 1.

Mitochondrial genome accession numbers, collection locations (including latitude and longitude), habitat types, and corresponding species and family of snail specimens included in this study.

Family: species	Sample	Location (latitude, longitude)	Habitat type
Lymnaeidae:
Galba truncatula	PX857456	Dünnernstrasse, Welschenrohr, Switzerland (−47.2803, 7.5456)	Laboratory aquarium
	PX857457	Hauptstrasse, Wohlen bei Bern, Switzerland (−46.9710, 7.3558)	Laboratory aquarium
	PX857458	England, United Kingdom (53.1638, −2.8984)	Laboratory aquarium
	PX857459	England, United Kingdom (53.1317, −2.6723)	Laboratory aquarium
Galba sp.	PX857460	Unknown origin, maintained in England, United Kingdom	Laboratory aquarium
Orientogalba viridis	PX857461	Werribee South, Victoria, Australia (−37.9447, 144.6989)	Irrigation channel
	PX857462	Watergardens, Victoria, Australia (−37.6970, 144.7721)	Pet store aquarium
Pseudosuccinea columella	PX857463	Gillamatong Creek, Braidwood, New South Wales, Australia (−35.4387, 149.7981)	Creek
	PX857464	Darwin Botanic Gardens, Northern Territories, Australia (−12.4455, 130.8366)	Pond
	PX857465	Guyatt Lake, Sale, Victoria, Australia (−38.1152, 147.0751)	Lake
	PX857466	Stoney Creek, New South Wales, Australia (−37.0656, 149.6851)	Creek
	PX857467	Cataract Gorge, Tasmania, Australia (−41.4460, 147.1208)	River
Physidae:
Physa acuta	PX857468	Werribee South, Victoria, Australia (−37.9447, 144.6989)	Irrigation channel
	PX857469	Macquarie River, Tasmania, Australia (−41.9077, 147.3914)	River
Planorbidae:
Planorbella sp.	PX857470	Melbourne, Victoria, Australia (−37.8071, 144.9570)	Pet store aquarium

2.2. Targeted amplification, sequencing and mitogenome assembly

We amplified mitochondrial DNA (mtDNA) using the REPLI-g Mitochondrial DNA Kit (Qiagen, Germany) with a mix of eight short primers (11–14 nt; phosphorothioate linkages between the final three bases), targeting the cox1, rrnS and 1rrnL genes, based on previously established methods [16]. Amplified mtDNA from each specimen was assigned a unique barcode and pooled using the RAPID Barcoding Kit (SQK-RBK114.24; Oxford Nanopore Technologies). The pooled library (100 ng) was loaded on to an R10.4.1 flow cell and sequenced for 24 h on a PromethION 2 Solo platform (Oxford Nanopore Technologies, UK). Raw reads were generated in the POD5 format, base-called using Dorado v.0.8.3 (super-accuracy model), demultiplexed, converted from BAM to FASTQ using Dorado demux and compressed with pigz v.2.8.

For mitogenome assembly, we first subsampled 5,000 reads of >500 bp for each barcode using seqtk v.1.3-r106 and clustered homologous sequences with NGSpeciesID [17]. Representative clusters containing ≥30 reads were annotated against a mitochondrial genome reference database (Supplementary Table 1) using pblat [18] with a ≥25% identity threshold. For each barcode, we selected representative clusters showing highest sequence homology to mitochondrial genomes and then mapped all raw reads to these using minimap2 v.2.24 [19]; matching reads were retained with seqtk. Cluster-assigned reads were assembled with Canu v.2.3 [20] (minimum read length 1,000 bp, genome size 10 kb) and Flye v.2.9 [21] (−-meta and –nano-raw options). Contigs obtained from both assemblers were concatenated and aligned to reference mitogenomes using pblat; those showing >75% identity were imported into Geneious Prime 2024.0.7 (https://www.geneious.com). Annotations were generated using MITOS2 [22] employing the RefSeq89 database and the Invertebrate Mitochondrial Code (transl_table=5), then manually curated following the annotation criteria of Fourdrilis et al., [23], to verify open-reading frames, gene boundaries and absence of overlaps between protein-coding and tRNA genes.

2.3. Comparative and phylogenetic analyses

We compared the mitogenomes produced in this study with published sequences of related snail taxa to assess genetic variation and genome structure. Pairwise nucleotide differences were calculated using Geneious Prime, and nucleotide diversity (π) was estimated across the 13 protein-coding and two ribosomal RNA genes for each family (Lymnaeidae, Physidae and Planorbidae) and for the combined dataset. To account for variation in gene order among taxa, we rearranged genes alphabetically and retained only reference genomes with consistent annotations and manually curating them as required. Sliding-window analysis (300 bp window, 25 bp step) were performed in R using the pegas package v.0.13 [24], and results were displayed using ggplot2 [25].

Phylogenetic relationships were inferred from both concatenated mitogenome datasets and individual gene alignments. The 13 mitochondrial protein-coding genes were aligned with MAFFT v.7 [26] (L-INSi algorithm) and trimmed using trimAl [27] (strictplus mode). Substitution models were determined for individual genes using ModelTest-NG v.0.1.8 [28], [29]. Concatenated alignments were partitioned by gene boundaries via a custom Python script, and Bayesian inference was implemented in MrBayes v.3.2.7 [30] using the model specified for each partition. Two independent runs of 16 Markov chains were executed for 2 million generations, with convergence confirmed when split-frequency SD < 0.01 and PSRF ≈ 1; the first 25% of trees were discarded as burn-in to produce a 50% majority-rule consensus tree.

To assess relationships within Galba and Ph. acuta, we constructed additional trees using partial cox1 sequences obtained from GenBank. Sequences were aligned with MAFFT (−-adjustdirection), trimmed with trimAl (strict mode) and clustered at 0.98 identity using CD-HIT [31]. Representative sequences from individual clusters were analysed using the same tree-building method (Bayesian). Resultant trees were displayed using FigTree v1.4.3 (https://tree.bio.ed.ac.uk/software/fig tree/) and annotated in R using ggtree [32].

3. Results

3.1. Mitochondrial genome architecture and patterns of intraspecific variation

We assembled and annotated 15 complete mitochondrial genomes from five genera of freshwater snails representing the families Lymnaeidae, Physidae and Planorbidae (Table 2). Mitogenome sizes ranged from 13,731 bp (G. truncatula) to 14,265 bp (Ph. acuta), each containing the standard complement of 13 protein-coding genes, 22 tRNAs and two rRNAs. All genomes were A + T-rich (69.53–74.03%), with Galba sp. showing the highest and Physa the lowest A + T content. Gene order was conserved within families, with truncated stop codons detected in nine protein-coding genes of O. viridis, seven in P. columella, Galba spp., and Planorbella sp., and one in Ph. acuta (Table 3).

Table 2.

Mitochondrial genomes assembled and annotated in this study, showing genome size (bp), overall AT content (%), and gene order.

Family	Species and accession no.	Genome size (bp)	AT%	Gene order (5′–3′)
Lymnaeidae	Galba truncatula:			cox1–trnV–rrnL–trnL–trnP–trnA–nad6–nad5–nad1–nad4L–nad4–cob–trnD–trnF–cox2–cox1–trnY–trnW–trnC–trnG–trnH–trnQ–trnL–atp8–trnN–atp6–trnR–trnE–rrnS–trnM–nad3–trnS–nad4–trnT–cox3–cox1–trnI–nad2–trnK
	PX857456	13,738	73.73
	PX857457	13,738	73.69
	PX857458	13,737	73.77
	PX857459	13,731	73.66
	Galba sp.:
	PX857460	13,741	74.03
	Orientogalba viridis:
	PX857461	13,766	72.78
	PX857462	13,769	72.76
	Pseudosuccinea columella:
	PX857463	13,821	73.35
	PX857464	13,822	73.35
	PX857465	13,821	73.35
	PX857466	13,820	73.35
	PX857467	13,821	73.35
Physidae	Physa acuta:			cox1–trnP–nad6–nad5–nad1–trnD–trnF–cox2–trnY–trnW–nad4L–trnC–trnQ–atp6–trnR–trnE–rrnS–trnM–trnT–cox3–trnI–nad2–trnK–trnV–rrnL–trnL–trnA–cob–trnG–trnH–trnL–atp8–trnN–nad3–trnS–trnS–nad4
	PX857468	14,264	69.53
	PX857469	14,265	69.54
Planorbid	Planorbella sp.:			cox1–trnV–rrnL–trnL–trnA–trnP–nad6–nad5–nad1–nad4L–cob–trnD–trnC–trnF–cox2–trnY–trnW–trnG–trnH–trnQ–trnL–atp8–trnN–atp6–trnR–trnE–rrnS–trnM–nad3–trnS–trnS–nad4–trnT–cox3–trnI–nad2–trnK
	PX857470	13,757	72.72

Table 3.

Comparison between initiation and termination codons and lengths of protein-coding genes within the mitogenomes characterised in this study. For each protein coding genes, the initiation and termination codons are presented first followed by the lengths in base pairs (initiation/termination/length). Genes are presented in alphabetical order. An asterisk (*) indicates an incomplete stop codon.

Genes	Galba truncatula		Galba sp.	Orientogalba viridis	Pseudosuccinea columella	Physa acuta	Planorbella sp.
	PX857456–8	PX857459	PX857460	PX857461–2	PX857463–7	PX857468–9	PX857470
atp6	ATG/TA*/643	ATG/TA*/643	ATG/TA*/643	ATA/T*/637	ATG/T*/643	ATC/TAA/630	ATA/T*/648
atp8	ATC/TAA/153	ATC/TAA/153	ATT/TAA/153	ATT/T*/148	ATC/T*/154	ATC/TAA/114	ATC/T*/112
cox1	ATT/TAA/1494	ATT/TAA/1494	ATT/TAA/1494	ATT/TAA/1494	ATT/TAA/1494	ATT/TAA/1494	TTG/T*/1525
cox2	TTG/T*/ 655	TTG/T*/658	TTG/T*/655	TTG/T*/643	ATT/T*/655	TTG/TAA/621	ATT/T*/640
cox3	ATA/T*/784	ATA/T*/784	ATA/T*/784	ATG/T*/778	ATA/TAA/798	ATT/TAA/786	ATT/T*/793
cob	ATT/TA*/1093	ATT/TA*/1093	ATT/TA*/1093	ATT/T*/1084	ATT/T*/1093	ATA/TAA/1119	TTG/T*/1081
nad1	ATT/TAA/876	ATT/TAA/876	ATT/TAG/876	ATT/TAA/873	ATT/TAA/876	ATT/TAG/894	ATA/TAA/861
nad2	ATT/TA*/910	ATC/TA*/910	ATT/TA*/910	ATT/T*/904	ATT/T*/910	ATG/TAA/846	ATT/T*/913
nad3	ATA/T*/343	ATA/T*/343	ATT/T*/343	ATA/T*/340	ATA/T*/352	ATA/TAA/354	ATT/TAA/354
nad4	ATT/TAG/1326	ATT/TAG/1326	ATT/TAG/1326	ATT/T*/1327	ATT/TAG/1329	ATG/T*/1312	ATG/TAA/1290
nad4L	ATG/TA*/277	ATC/TA*/277	ATT/TA*;277	ATG/TA*/295	ATA/T*/277	ATA/TAA/279	ATT/TAA/255
nad5	ATT/TAG/1635	ATT/TAG/1635	ATT/TAG/1635	ATA/TAG/1647	ATT/TAG/1635	ATT/TAA/1569	ATA/TAG/1632
nad6	ATA/TAA/459	ATA/TAA/459	ATA/TAA/459	ATA/TAA/459	ATA/TAA/459	ATA/TAA/423	ATT/TAA/447

Comparative analyses of whole mitochondrial genomes revealed minimal intraspecific divergence among Australian samples. Pairwise whole mitochondrial genome nucleotide distances were 0.04% for O. viridis, 0–0.03% for P. columella and 0.5% for Ph. acuta. Divergence from overseas reference genomes varied by taxon: Australian O. viridis differed by 1.4% from Chinese G. pervia (O. ollula: NC018536); P. columella sequences showed 0.47% divergence from an isolate from the USA (NC042905), reflecting a 64 bp deletion between tRNA-Cys and tRNA-His; and Ph. acuta diverged by 8.7–8.8% from USA isolates A and B (NC023253 and JQ390526, respectively). The Planorbella specimen from Victoria shared 93.35% identity with P. duryi (KY514384) at the whole-mitogenome level.

At the cox1 locus (1,527 bp; Table 3), all Australian representatives of Ph. acuta, P. columella and O. viridis were identical across sampling locations. Among G. truncatula isolates from Switzerland and England, sequence divergence was greater (pairwise cox1 identities 88–99.7%). The English laboratory strain with uncertain identification (PX857460) was more similar to G. neotropica from Peru (AM494008) than to other G. truncatula specimens from Switzerland or England. At the cox1 gene, the Australian specimen of Planorbella sp. shared 98.95% nucleotide identity with P. duryi (KY514384).

Across all taxa, mean nucleotide diversity (π) was 0.274, compared with within-family values of 0.192, 0.067 and 0.234 for the Lymnaeidae, Physidae and Planorbidae, respectively. Diversity peaks occurred in the genes cox2, nad3, nad4 and nad5 (Fig. 1).

Fig. 1.

Sliding-window nucleotide diversity (π) across concatenated mitochondrial protein coding and ribosomal RNA genes of three snail families (window size = 300 bp and a step size = 25). Curves represent: green = All families” (pairwise comparisons among all sequences); light blue = Lymnaeidae; purple = Planorbidae; dark blue = Physidae. Horizontal dashed lines mark the mean π for each curve: overall = 0.274, Lymnaeidae = 0.192, Planorbidae = 0.234, Physidae = 0.067. Gene boundaries are indicated by alternating grey shading along the x-axis, genes are arranged in the order of ribosomal RNAs followed by protein coding genes in alphabetical order and do not represent true gene order of the taxa represented. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.2. Mitochondrial topologies reveal constrained lineage divergence but marked variation within the genus Galba

Bayesian inference of concatenated nucleotide sequences from 13 mitochondrial protein-coding genes produced a strongly supported phylogeny (Fig. 2). The analysis showed monophyly of the Lymnaeidae and Planorbidae (pp = 1.0), which were inferred as sister clades. Within the Planorbidae, the Planorbella specimen from Australia clustered with P. duriyi from the USA and P. pilsbryi from Canada (Fig. 2). Within the Lymnaeidae, O. viridis formed a robust clade (pp = 1.0) with O. ollula, and the Austropeplea species endemic to Australia placed as a sister lineage to this group. Pseudosuccinea columella and G. truncatula, together with other Galba species, comprised a distinct sister lineage within the family, and Lymnaea stagnalis represented the most divergent lymnaeid taxon. The Galba specimen of unknown origin that was maintained in the laboratory in England (PX857460) was distinct from the remaining G. truncatula sequences, suggesting that it might represent a different species. Within the Physidae, Ph. acuta specimens from Victoria and Tasmania grouped tightly (pp = 1.0) and was closer to isolate A than isolate B from the USA.

Fig. 2.

Bayesian inference phylogenetic relationships of snail within the families Lymnaeidae, Physidae, and Planorbidae inferred from concatenated nucleotide sequences of 13 mitochondrial protein-coding genes. Sequences generated in this study are shown in bold. Posterior probabilities are displayed at each node, with the scale bar representing phylogenetic distance in substitutions per site.

Phylogenetic analyses based on partial cox1 sequence data were conducted for Ph. acuta and G. truncatula to clarify geographic origins, given substantial intraspecific variation in G. truncatula specimens and the presence of isolates A and B within Ph. acuta. This approach was not applied to Planorbella sp. and O. viridis due to limited comparative sequences available and taxonomic ambiguity surrounding O. viridis. For P. columella, cox1 phylogenetic analysis was uninformative due to lack of intraspecific divergence, as all Australian isolates were identical to the globally invasive haplotype identified by Lounas et al. [33].

Physa acuta specimens from Australia fell within the cosmopolitan clade of this species (pp = 0.87), which included USA clade A and sequences from specimens collected on multiple continents. However, these sequences did not cluster closely with Ph. acuta haplotypes published in 2011 from Victoria, which instead grouped with an Iranian specimen (pp = 1.0) (Fig. 3). For Galba spp., inference based on cox1 sequences identified two main G. truncatula clades: one containing European and South American sequences (including those derived from Swiss and English specimens in this study; pp. = 1.0), and another comprising an English isolate from this study (PX857459) and a previously published sequence for G. truncatula from Germany (KP242625) with lower nodal support (pp = 0.76). The sequence from Galba sp. maintained in England (PX857460) formed a sister relationship (pp = 0.97) to the clade containing G. cubensis and G. neotropica (Fig. 4).

Fig. 3.

Bayesian phylogeny based on partial cytochrome c oxidase subunit 1 sequences of Physa acuta from Australia (bolded) and representative global populations. Posterior probabilities are indicated at nodes, and the scale bar denotes the number of substitutions per site.

Fig. 4.

Bayesian inference phylogenetic relationships inferred from partial cytochrome c oxidase 1 genes of Galba from laboratory cultures in Switzerland and England that were generated in this study (bolded) compared with sequences from other locations. Posterior probabilities are indicated at each node, with the scale bar representing phylogenetic distance in substitutions per site.

Overall, the results from the single-gene (cox1) analysis corroborated the topology of the mitogenomic tree (cf. Fig. 2), confirming well-resolved family-level relationships and highlighting marked genetic variability within Galba and global connectivity among Physa acuta populations. In contrast, Australian specimens of P. columella, O. viridis and Ph. acuta exhibited genetic uniformity, with minimal intraspecific divergence observed across sampling locations.

4. Discussion

This study characterised the complete mitogenomes of four introduced freshwater snail taxa established in Australia (P. columella, O. viridis, Ph. acuta and Planorbella sp.) and G. truncatula, a high-priority exotic species not yet present in this country. These data provide the first genomic resources for non-native snail vectors of potential public health, veterinary and ecological importance in Australia (Supplementary Table 2). The results reveal a conserved mitochondrial organisation for the families studied, limited genetic diversity within Australia, but pronounced divergence within the Galba laboratory strain from Europe. Such genetic uniformity among Australian samples indicates demographic bottlenecks [34], [35], founder effects and a capacity for self-fertilisation that facilitate rapid establishment from few individuals [33]. Pseudosuccinea columella exhibits this pattern across different states in Australia, spanning both urban and rural habitats, including a major livestock-producing region. These traits, combined with anthropogenic dispersal via aquatic vegetation and the aquarium trade, emphasise how hidden introductions can evade detection [36]. Establishing these genomic resources provide a baseline characterising the currently low genetic diversity of introduced populations in Australia, such that any future incursions, novel lineages or changes in population structure can be detected in subsequent monitoring and surveillance studies within the context of national biosecurity programs.

The lymnaeids P. columella and O. viridis are of biosecurity relevance because of their potential to transmit F. hepatica. Historical infection experiments showed that P. columella can sustain development of an Australian lineage of F. hepatica, although less efficiently than native Austropeplea species [10], whereas O. viridis exhibits variable vector competence in Asia and Oceania [37]. The taxonomy of O. viridis – previously conflated with O. ollula – has been contentious [38], therefore genetic confirmation is essential for accurate identification for epidemiological surveillance. The occurrence of O. viridis in Victorian irrigation systems and the aquarium trade [5], [10], together with records of Planorbella sp. in the same industry [5], highlights the aquarium trade as a pathway for introducing snails that can act as intermediate hosts (vectors) of trematode parasites in Australia. Such pathways represent tangible biosecurity risks as imported species may carry larval stages of parasites and establish populations in urban or rural waterways. The mitochondrial reference genomes defined here provide a foundation for the design of species-specific molecular and eDNA tools to detect introduced taxa before they become firmly established.

The physid Ph. acuta, presents a contrasting invasion scenario. It is widespread across Australia, acts as an intermediate host for native trematodes [39], [40], and has shown evidence of outcompeting endemic snails such as Glyptophysa gibbosa [41]. Although the displacement of lymnaeids might theoretically reduce transmission of F. hepatica, the broader ecological consequences of Ph. acuta colonisation, including biodiversity loss, possible shifts in parasite assemblages and altered transmission dynamics within freshwater systems, are likely to outweigh any benefits. The spread and ecological dominance of Ph. acuta exemplify the capacity of invasive snails to reshape freshwater ecosystems and challenge the resilience of biosecurity programs [42]. Furthermore, another physid species, Stenophysa marmorata has been reported in Indonesia and has potential of becoming invasive in Australia [43]. Monitoring will be important to detect incursions, assess ecological impacts and guide management strategies that balance biodiversity conservation and livestock health.

Beyond their value for ecological investigations, the complete mitogenomes characterised here provide data for taxonomy, molecular diagnostics, phylogenetic relationships and eDNA-based monitoring within Australia's biosecurity framework. The discovery of marked genetic variation within Galba and the uncertain identity of Planorbella sp. emphasise the importance of integrating genomic, morphological and ecological data for accurate species delimitation. Expanding geographic sampling, incorporating nuclear markers, conducting trematode surveys and experimental infections with local parasite lineages, and implementing long-term monitoring that explicitly integrates human, livestock and wildlife health will be central to translating these genetic baselines into evidence-based risk assessments and management strategies. The mitogenomic resources developed here represent a significant advance for molecular diagnostics and biosecurity preparedness, supporting a broader One Health agenda for the integrated management of parasites and their vectors.

CRediT authorship contribution statement

Tanapan Sukee: Writing – review & editing, Writing – original draft, Visualization, Validation, Resources, Methodology, Investigation, Formal analysis, Data curation. Sunita B. Sumanam: Writing – review & editing, Methodology, Investigation. Zhe-Yu Chen: Resources. Jane E. Hodgkinson: Writing – review & editing, Resources. Natalie Wiedemar: Writing – review & editing, Resources. Bonnie L. Webster: Writing – review & editing, Funding acquisition. Winston F. Ponder: Writing – review & editing, Funding acquisition, Formal analysis. Bill C.H. Chang: Funding acquisition. Robin B. Gasser: Writing – review & editing, Writing – original draft, Funding acquisition. Anson V. Koehler: Writing – review & editing, Writing – original draft, Resources, Funding acquisition. Neil D. Young: Writing – review & editing, Supervision, Resources, Methodology, Funding acquisition, Formal analysis, Conceptualization.

Funding

This study was financially supported by Australian Research Council (DP230100270 and FT230100559 to N.D.Y; LP180101085 and LP220200614 to R.B.G), the Swiss National Science Foundation (PZ00P3_216088 to N.W.) and The Perry Foundation UK, award to Dr Rebecca Hoyle.

Declaration of competing interest

The authors declare no competing interest that could have influenced the body of work reported in this paper.

Appendix A. Supplementary data

Supplementary table 1. List of mitochondrial reference sequences used in this study; Supplementary Table 2. Records of trematode parasites of veterinary, public health and ecological relevance found in the snail taxa (natural infections) included this study, their regional distribution and natural infection status in Australia.

Data availability

The complete mitochondrial genomes sequences generated from this study are available on GenBank under accession numbers PX857456 – PX857470.