Development of a qPCR assay and tremabiome deep amplicon sequencing method for differentiation of fluke species in livestock

for differentiation of fluke species in livestock 2 Short title: Detection techniques for fluke infection 3 Muhammad Abbas1, Kezia Kozel1, Olukayode Daramola2, Nick Selemetas3, Qasim Ali4, Shoaib 4 Ashraf5,6, , Isah Ibrahim7, Inaki Deza-Cruz8, Sai Fingerhood9, Mark W. Robinson10, Eric R 5 Morgan10, Umer Chaudhry 11 *, Martha Betson1* 6 1 Department of Comparative Biomedical Sciences, School of Veterinary Medicine, 7 University of Surrey, Guildford, UK 8 2School of Veterinary Medicine, University of Lancashire, Preston, United Kingdom 9 3 Department of Microbial Sciences, School of Veterinary Biosciences, University of Surrey, 10 Guildford, UK 11 4 Department of Parasitology, Agriculture University Dera Ismail Khan, Pakistan 12 5Department of Pathobiology, College of Veterinary Medicine, Riphah International 13 University, 54000 Lahore, Pakistan 14 6Department of Biomedical Sciences, Ross University, School of Veterinary Medicine 15 (RUSVM), St Kitts and Nevis, West Indies 16 7Department of Veterinary Parasitology and Entomology, Faculty of Veterinary Medicine, 17 Ahmadu Bello University, Zaria, Nigeria 18 8The Royal (Dick) School of Veterinary Studies and The Roslin Institute, The University of 19 Edinburgh Easter Bush Veterinary Centre, Midlothian, EH25 9RG 20 9Department of Veterinary Pathology, University of Nottingham, UK 21 10School of Biological Sciences, Queen’s University, Belfast, UK 22 11Department of Veterinary Biomedical Sciences, Lewyt College of Veterinary Medicine, 23 Long Island University, USA 24 Corresponding authors: 25 *Martha Betson, [email protected] 26 * Umer Chaudhry, [email protected] 27 28 29 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 2

30

31 Trematode parasites, or flukes, are a significant economic threat to ruminant production 32 worldwide. Traditional diagnostic methods rely on egg sedimentation from faeces, a time-33 consuming methodology lacking sensitivity and specificity. This study aimed to develop and 34 validate two diagnostic methods: firstly, qPCR for accurate identification of Fasciola spp., 35 and secondly, tremabiome, deep amplicon sequencing technique for identifying fluke 36 species using faecal egg DNA. 37 Methodology: 38 To detect fluke infection primers targeting mitochondrial DNA were repurposed to develop 39 a SYBR Green qPCR diagnostic. For the identification of fluke species, a tremabiome 40 approach was developed. A reference sequence library and taxonomy file were generated 41 for 21 fluke species, enabling species sequence read separation and extracting amplicon 42 sequence variants (ASVs). To validate the qPCR and tremabiome approach, 402 faecal 43 samples were collected from cattle and sheep across the UK. Fluke eggs were isolated by 44 sedimentation, detected by microscopy and qPCR, and tremabiome used to identify fluke 45 eggs to species level. 46

47 qPCR demonstrated high analytical sensitivity, detecting Fasciola hepatica DNA down to 48 19.2fg and F. gigantica down to 6.4fg, with no cross-amplification of other flukes. 49 Tremabiome was able to detect as few as five F. hepatica and Calicophoron daubneyi eggs 50 and identify mixed infections. High levels of co-infection (14.4%) of F. hepatica and C. 51 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 3 daubneyi were observed in faecal samples, followed by single infections with C. daubneyi 52 (12.6%) and F. hepatica (3.2%). Notably, tremabiome detected F. hepatica in 20 samples 53 missed by qPCR. Data analysis identified 55 and 32 ASVs for F. hepatica and C. daubneyi, 54 respectively, with phylogenetic clustering within their respective clades. 55

56 This study developed qPCR assay for Fasciola detection and validated a tremabiome deep 57 amplicon sequencing for fluke species differentiation. These approaches have improved 58 capacity to identify fluke species compared to microscopy and are valuable tools for 59 enhancing fasciolosis surveillance and control. 60

trematode; amplicon deep sequencing; Fasciola; molecular detection; speciation 61 Author Summary 62 Flukes are flatworm parasites that cause disease domestic and wild animals and humans. 63 The main species infecting cattle and sheep globally are the liver flukes F. hepatica and F. 64 gigantica, with other species including the rumen fluke Calicophoron daubneyi locally 65 important or emerging. Infections result in serious economic losses. The traditional method 66 of diagnosing fluke infection involves observation of eggs in faecal samples under the 67 microscope, but this can be time-consuming and error prone, since the eggs of different 68 species often look similar. In this study, we developed and validated two methods to 69 improve detection: qPCR, a sensitive DNA-based test to identify Fasciola infections, and 70 tremabiome, a DNA sequencing technique that can accurately differentiate between 71 different fluke species. We tested these methods using faecal samples collected from cattle 72 and sheep across the UK. The qPCR could detect small amounts of Fasciola DNA, while 73 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 4 tremabiome was more sensitive, identifying different fluke species from as few as five eggs. 74 Our study found that co-infections of F. hepatica and C. daubneyi are common in the UK. 75 The approaches we have developed could be valuable tools for to improve fluke diagnosis 76 and enable better control of this important parasitic disease. 77

78 Trematode parasites, or flukes, are widespread globally and include several species that 79 cause serious disease in animals and humans. Fasciolosis is a neglected foodborne tropical 80 disease caused by the zoonotic flukes Fasciola hepatica and Fasciola gigantica. Unlike other 81 neglected tropical diseases, Fasciola infections in humans and animals have a broad reach 82 globally, being found in more than 75 countries, with 2.4 million people infected, and 83 millions more at risk [1]. The prevalence in livestock is less well known, however, a recent 84 meta-analysis suggests the global prevalence of fasciolosis in cattle and sheep across 85 continents ranges from 12-97% and 9-58% respectively across continents [2]. 86 Ensuring food security is increasingly challenging with a growing global population. In 2020, 87 the agri-food sector contributed 115 billion GBP, making up 6.0% of the UK economy [3], 88 with other national economies considerably more dependent on farming. Recent global 89 estimates indicate that fasciolosis may cost annual losses in animal productivity exceeding 90 US$3.2 billion [4,5]. In the UK, fasciolosis prevails in ruminants, costing the cattle industry 91 13-40 million GBP yearly, reducing dairy farms’ net profit by 12% and beef farms’ by 6% [6]. 92 Fasciola infections can lead to delayed animal slaughter [7], and condemnation of damaged 93 livers [8]. According to the Food Standards Agency in 2014, 22% of British cattle livers are 94 condemned due to fluke [9]. Losses to fasciolosis are widespread; for example, Australia 95 faces one of the highest disease burdens, with estimated annual losses reaching 96 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 5 approximately 129 million (range 38–193 million) AUD annually [10]. Infected animals suffer 97 reduced weight, anaemia, reduced milk yield and fat content [8], lower reproduction, and 98 higher mortality [11]. 99 Flukes other than Fasciola spp. are also economically important. Calicophoron daubneyi 100 belongs to the family Paramphistomidae, a group of flukes typically found in the 101 forestomachs of ruminants. Unlike the flattened morphology common to most trematodes, 102 these flukes exhibit a distinct conical shape as adults [12]. C. daubneyi is considered an 103 emerging threat in Europe due to its impact on livestock productivity. The larval stage of 104 rumen fluke are released into the duodenum, where they attach to the intestinal lining and 105 causes tissue damage. Although chronic C. daubneyi infection is not typically associated with 106 clinical disease, some negative effects on production have been reported [12]. Recent 107 studies suggest that paramphistomosis is now more prevalent than fasciolosis in certain 108 regions of the UK [9–11]. However, currently, diagnostic options for rumen fluke are limited 109 and need further research. 110 Traditionally, diagnosis of both Fasciola and Calicophoron infections relies on microscopic 111 identification of fluke eggs in the host faeces [13–15], with eggs usually observed 10−12 112 weeks post-infection and thereafter [14–16]. The effectiveness of microscopy relies on 113 personnel training and expertise. Moreover, it becomes labour-intensive when handling a 114 large number of samples, particularly if the person lacks sufficient experience, leading to 115 low sensitivity [17]. Distinguishing between F. hepatica and C. daubneyi solely based on egg 116 morphology in faecal samples can be challenging as both parasites produce eggs with 117 comparable sizes and shapes [18,19]. Although, it is reported that F. hepatica eggs can be 118 identified by their operculum [20] and yellowish colour [21], these features can be difficult 119 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 6 to observe consistently using standard light microscopy. As a result, trusting solely in egg 120 morphology for diagnosis may lead to misidentification. Molecular diagnostics based on 121 Fasciola DNA detection are rapidly progressing; for instance, qPCR [22] and PCR techniques 122 have been applied to adult worms and infected snails [23]. Additionally, techniques such as 123 nested PCR [14] and Loop-Mediated Isothermal Amplification (LAMP) are being explored 124 [24] and are under assessment for their speed, reliability, and accuracy compared to other 125

[25]. However, significant challenges remain in detecting Fasciola DNA in faecal 126 material, highlighting the need for a reliable, time-efficient and accurate diagnostic method, 127 which can handle medium to large sample sizes and is capable of differentiating F. hepatica 128 infections from other fluke species. 129 Next-generation sequencing technologies are transforming the diagnosis of infectious 130 diseases whilst also paving the way for new research areas, such as microbiome studies [26–131 28]. Amplicon sequencing using next-generation approaches has been applied to identify 132 gastrointestinal nematode species in ruminants (“nemabiome”) [29], to quantify 133 trypanosome and piroplasm species in ruminant blood samples (“haemoprotobiome”) 134 [30,31]. Similar “tremabiome” technology has been applied to quantify single species adult 135 fluke infections in ruminants [32–34]. Despite the prevalence of mixed fluke infections in 136 ruminants [32,33], this approach has not yet been used to understand fluke egg 137 communities in single and mixed species infections. 138 This study aimed to develop a user-friendly real time diagnostic tool to detect F. hepatica 139 and F. gigantica infections, and to distinguish them from other species such as rumen fluke. 140 Specifically, a SYBR Green qPCR-based assay was utilised to amplify the mitochondrial 141 NADH1 (mt-ND1) DNA marker without the need for fluorescent probes. This assay was 142 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 7 designed to screen Fasciola spp. infections from faecal sedimented material of naturally 143 infected cattle and sheep. Additionally, we combined two previously published deep 144 amplicon sequencing approaches tested on adult flukes of Fasciola and Calicophoron spp. 145 [32,34] to create a tremabiome approach capable of differentiating between various species 146 of fluke. Finally, both methods were validated using field samples of fluke eggs and adults 147 collected from different regions across the UK and compared to microscopy. 148

149 Ethical statement 150 Non-invasive collection of faecal samples was approved by the NASPA (Non-Animal 151 Scientific Procedures Act) sub-committee of AWERB, University of Surrey, UK, under the 152

NASPA-2122-04 for the project “Developing Novel Rapid Diagnostics for 153 Neglected Parasitic Diseases.” Adult F. hepatica were collected at licenced slaughterhouses 154 and through post-mortem examination. Completion of a University of Surrey SAGE-AR 155 indicated that no formal ethical approval was required for adult fluke sampling. 156 Positive control samples 157 All adult F. hepatica worms and sedimented eggs were collected from UK, whilst adult 158 worms and eggs purified from adult worms of F. gigantica, C. daubneyi, Paramphistomum 159 epiclitum and Explanatum explanatum were collected from abattoirs in Pakistan in our 160 previous studies [32–36]. Adult worm tissue was processed following a previously described 161 protocol [33] and DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen, USA). 162 DNA was then extracted from eggs of positive controls (F. hepatica, F. gigantica, C. 163 daubneyi, E. explanatum) utilising the DNeasy PowerSoil Pro Kits (Qiagen, USA), with slight 164 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 8 modification. Briefly these modifications included the incubation of sedimented material 165 with the lysis buffer (CD1) for 10 minutes at 65°C, followed by 10 minutes of bead-beating in 166 a TissueLyser LT (Qiagen, USA). The manufacturer's protocol was then followed, with DNA 167 being eluted in 10mM Tris buffer and stored at -80°C for downstream analysis. 168 Field sample collection 169 To engage cattle and sheep farmers, the study was advertised by email to registered 170 veterinary practitioners using the Royal College of Veterinary Surgeons Find a Vet site 171 filtering for practices specialising in cattle, sheep and/or goats, and camelids. In addition, 172 societies for sheep and cattle listed by the Department for Environment, Food and Rural 173 Affairs (https://www.gov.uk/government/publications/lists-of-recognised-animal-breeding-174 organisations) in the UK were also approached via the email contact listed. Participants 175 were sent a Royal Mail prepaid SafeBox with a sampling kit, a short questionnaire, and 176 participant information sheet and consent form according to ethical requirements. No 177 samples were used without the written informed consent of the farmer. A total of 402 178 faecal samples were collected from 19 cattle and sheep farms across various geographical 179 regions of the UK through 10 registered veterinary practitioners from December 2022 to 180 May 2024 (Table S1). 181 In addition to faecal samples, adult F. hepatica worms were collected from abattoirs and at 182 post-mortem analysis from cattle (n=2) originating from West Sussex, and East Sussex, as 183 well as from sheep (n=10) from West Sussex, Kent, Derbyshire, Renfrewshire Scotland and 184 County Tyrone Northern Ireland. All samples were transported to the School of Veterinary 185 Medicine at the University of Surrey, UK, and subsequently stored at -20°C for further 186 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 9 analysis. DNA from the adult flukes was extracted as described in section “Positive control 187 samples”. 188 Morphological identification of fluke eggs 189 Faecal samples were initially processed using standard sedimentation methodology [37] and 190 then to streamline the process a time-saving method Flukefinder® (Diagnostic System, USA) 191 was also used [18,38], with slight adjustments. Both methods utilised 7-10 grams of faecal 192

which was combined with 50 ml of water, sieved through gauze and then passed 193 through the Flukefinder® apparatus. The collected filtered material from both methods was 194 then mixed with 250 ml of water in a conical beaker. After three minutes, the supernatant 195 was removed; this step was repeated thrice for clarity. The sediment was transferred to a 50 196 ml centrifuge tube filled with water, and the supernatant was aspirated after 3 minutes. This 197 process was repeated with a 15 ml centrifuge tube. Finally, the sediment was transferred to 198 a 1.5 ml Eppendorf tube in 1 ml of PBS and was stored at 4°C for subsequent microscopy 199 and DNA isolation. 200 Morphological egg examination involved inspecting 100 to 500 μl of sedimented faeces 201 stained with 0.5% methylene blue (Pro-Lab, UK) in a counting chamber (Graticules Optics 202 Limited, UK) under a compound microscope (Nikon, Japan) at 100× magnification with a lens 203 containing a graticule. Samples positive for fluke eggs (n=128) were assessed for the 204 presence of F. hepatica or C. daubneyi eggs based on their morphological characteristics, 205 including size, shape, colour and operculum [18–21]. The overall workflow is summarised in 206 Fig. 1 (a). 207 Any sedimented faecal samples which were identified as positive for fluke eggs by 208 microscopy were subsequently subjected to DNA isolation utilising the DNeasy PowerSoil 209 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 10 Pro Kits (Qiagen, USA) according to the manufacturer’s instructions as described in the 210 section “Positive control samples”. 211 Molecular identification of fluke eggs 212 PCR was performed using universal ITS2 primers [39] on selected fluke egg-positive samples 213 and all positive controls. Further, Fasciola specific mt-ND1 primers [33] were applied to 214 selected samples to confirm the diagnostic accuracy of the PCR targets. This was followed by 215 Sanger sequencing to confirm the presence and correct amplification of DNA for different 216 fluke species. 217 All PCR reactions were prepared with DreamTaq Green PCR master mix (Thermo Scientific, 218 USA) in a 25 μl reaction mix, with primer concentrations of 200 nM and 4 μl of sample DNA 219 template. The PCR cycling conditions were initial denaturation at 95°C for 5 minutes, 220 followed by 35 cycles of denaturation at 95°C for 1 minute, annealing at 55°C (ITS2 primers), 221 50°C (mt-ND1 primers) for 1 minute, and extension at 72°C for 1 minute. The final extension 222 step was carried out at 72°C for 5 minutes. Positive controls consisted of DNA from F. 223 hepatica and F. gigantica adult worms. The resulting PCR products were purified and 224 cleaned using a NucleoMag kit for clean-up and size selection of NGS library prep reactions 225 (MACHEREY-NAGEL, GmbH & Co.KG). Sanger sequencing of the PCR product was performed 226 by Source Biosciences, UK and Eurofins Genomics, Germany. Selected samples were 227 subjected to conventional PCR and Sanger sequencing due to limited resources. All obtained 228 sequences were visualised using Geneious version 8.0.5 (https://www.geneious.com), and 229 the FASTA sequences were submited to the BLASTn tool on NCBI to confirm fluke species 230 identity. 231 Development and validation of a SYBR green qPCR to detect Fasciola eggs at species level 232 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 11 A SYBR green qPCR assay was developed to detect Fasciola spp., ingus mt-ND1 primers. 233 These mt-ND1 primers were previously designed and employed in a meta-barcoded PCR 234 [33]. In the SYBR green assay, 3 μl of DNA was subjected to qPCR using 10 μl of 2X 235 SsoAdvanced Universal SYBR Green Supermix (Bio-Rad, USA), resulting in a total reaction 236 mix volume of 20 μL, including 500 nM of mt-ND1 primers. 237 The cycling program was initial denaturation at 98 ℃ for 3 mins, followed by 40 cycles of 238 denaturation at 98 ℃ for 15 secs and annealing at 60 ℃ for 30 secs on a CFX96 Real-Time 239 PCR machine (Bio-Rad, USA). Subsequently, a melt curve was generated from 65 ℃ to 95 ℃ 240 with an increment of 0.5 ℃ for 0.05 secs per plate read. Positive and negative controls were 241 employed as described above. All samples were subjected to qPCR in triplicate, and the 242 resulting data were visualised using CFX Maestro Version: 5.3.022.1030 (Bio-Rad, USA). 243 Detection sensitivity limits of the assay were assessed using five-fold serial dilutions of F. 244 hepatica (ranging from 300 pg to 0.768 fg) and F. gigantica (ranging from 500 pg to 1.28 fg) 245 adult worm DNA. The DNA was quantified using Qubit™ dsDNA HS and BR Assay Kits 246 (Invitrogen™). The analytical specificity of the assays was evaluated by testing 1 ng of DNA 247 from other prevalent flukes and nematodes found in sheep and cattle. These included C. 248 daubneyi, P. epiclitum, E. explanatum, and the nematode Teladorsagia circumcincta. The 249 sensitivity and specificity tests were conducted in triplicate and repeated twice. 250 The reliability of the method was measured by comparing inter- and intra-assay variations in 251 Cq values for F. hepatica and F. gigantica DNA. For validation, the newly developed qPCR 252 assay was applied to egg DNA extracted from sedimented faecal samples. 253 Development and validation of deep amplicon sequencing to detect fluke eggs at species 254 level 255 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 12 A universal ITS2 rDNA marker for a range of 21 different fluke species (Table S2; DOI: 256 10.17632/zyvwc6ppy8.1) targeting coding regions of 5.8S and 28S rDNA was used, expected 257 to produce a fragment of 490 –743 bp [39]. The primers were meta -barcoded by adding 258 Illumina adaptor sequences to the both forward and reverse primers, along with up to three 259 random 'N' nucleotides positioned between the adaptor sequences and the locus -specific 260 primers. Additionally, modified phosphate bonds were added between the last three 261 nucleotides of each primer to enhance their stability (Table S3) and used in PCR amplification 262 to detect fluke species. To assess the representation of spec ies read depth , mock DNA 263 mixtures were prepared in triplicate by pooling 250 eggs of each species, including F. 264 hepatica, F. gigantica, and C. daubneyi and subjected to amplicon sequencing in triplicate. 265 PCR cycle numbers were adjusted 35x, 30x and 25x in the first round to examine their effect 266 on species representation . Further, to evaluate species representation using egg DNA , we 267 created seven mock egg pools in triplicate , adjusting the proportion of F. hepatica and C. 268 daubneyi in an approximate total of 250 eggs with ratios of 99:1, 90:10, 70:30, 50:50, 30:70, 269 10:90, and 1:99. Moreover, to test the threshold of deep amplicon sequencing, pools of equal 270 egg proportions (50 eggs) were prepared from three out of four species ( F. hepatica , F. 271 gigantica, E. explanatum, C. daubneyi). The fourth species ( F. hepatica or C. daubneyi) was 272 then added in decreasing numbers of 500, 50, 20, 15, 5, and 0 eggs, creating six mock pools. 273 The first round of PCR was performed using the KAPA HiFi PCR Kit (KAPA BIOSYSTEMS, South 274 Africa). The modified primer sets, adaptors, barcoded PCR amplification conditions, magnetic 275 bead purification methods and bioinformatic analysis were based on our previously described 276

[33]. The first-round PCR products were subjected to a second -round PCR using a 277 barcoded primer set to attach a unique barcode index fragment required for Illumina 278 sequencing [30] Fig. 1 (b). 279 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 13 10 μl of each second round barcoded PCR product were combined to create a pooled library 280 and then purified by agarose gel electrophoresis to remove non-specific products and adaptor 281 dimers. During post -run processing, the MiSeq system separated all sequencing data by 282 sample quality using the barcoded indices to generate FASTQ files (raw sequence read files 283 available at Mendeley database DOI: 10.17632/zyvwc6ppy8.1), see workflow diagram Fig. 1 284 (b). 285 The FASTQ files obtained from the post -run Illumina MiSeq (BioProject ID PRJNA1273189 ) 286 were analysed in Mothur/1.41.0-Python-2.7.15 [40] using the High-Performance Cluster (HPC) 287 system at the University of Surrey, UK . Pipelines described in our previous study [41] were 288 utilised with modifications of the newly developed reference sequence library (Script 289 available at DOI: 10.17632/zyvwc6ppy8.1). 290 To generate a taxonomy file, ITS2 rDNA reference sequences (n=545) were obtained from 291 NCBI, representing 21 fluke species (Table S2). The genetic distances between different fluke 292 species were then calculated based on the sequenced region. Overall, a variation in genetic 293 identity was found between different fluke species ranging from 40% to 99% (Table S4, DOI: 294 10.17632/zyvwc6ppy8.1). Finally, a phylogenetic tree of 154 unique sequences showed a 295 distinct clustering of each fluke species (Fig. 2) as described in the section phylogenetic 296 analysis. 297 Following extraction of the taxonomy file, quality filtering was conducted for the 298 identification of unique fluke sequences, detailed count tables were generated and an 299 alignment (ALIGN) file of sequences across all samples was produced. This workflow ensured 300 a robust, high -quality dataset suitable for downstream taxonomic studies for flukes using a 301 series of commands (Script available at DOI: 10.17632/zyvwc6ppy8.1). 302 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 14 The count table and alignment (ALIGN) file were further used for the extraction of amplicon 303 sequence variants (ASVs) . The R script extracted specific ASVs corresponding to the target 304 species of flukes applying cutoff values of 250 reads each (NCBI accession numbers; 305 PV752375-PV752429, PV752431 -PV752462). The R script started by cleaning sequence 306 names, trimming whitespace and converting them to lowercase to ensure consistency for 307 successful merging. After identifying unmatched sequences, the datasets were merged based 308 on sequence names. The merged data was filtered to retain only rows with a ‘total’ count of 309 at least 250 reads, ensuring that only high-quality consensus sequences remained. A custom 310 function was employed to write the sequences into a combined FASTA file, preserving both 311 the sequence names and read counts. Next, the script utilised the Biostrings package to clean 312 the sequences by removing ‘N’ characters and ambiguous bases, saving the high -quality 313 sequences to a final FASTA file (R script available at D OI: 10.17632/zyvwc6ppy8.1). This 314 comprehensive approach ensure d accurate sequence extraction for subsequent analysis. 315 Finally, the sample-wise separated FASTA files were subjected to remote NCBI BLASTn loop 316 command using “ blastn: 2.16.0+ ” in the HPC cluster system ( command line available DOI: 317 10.17632/zyvwc6ppy8.1). Mismatched sequences with the NCBI database were considered 318 contaminated sequences and discarded. 319 Statistical analysis of qPCR and deep amplicon sequencing data 320 For qPCR analysis, the raw Cq values were extracted from CFX Maestro Version: 321 5.3.022.1030 (Bio-Rad, USA) and a linear standard curve was created by plotting DNA 322 quantities against the average Cq values for each concentration tested. For deep amplicon 323 sequence reads data analysis, the sequences from the bioinformatics pipeline were further 324 analysed for sequence accuracy and percentage identity using remote blastn: 2.16.0+ with 325 the NCBI database. To determine the percentage composition of F. hepatica, F. gigantica, C. 326 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 15 daubneyi, and E. explanatum in mock egg mixtures (positive control) and field samples, 327 species composition percentages were calculated by dividing the classified sequence reads 328 for each species by the total reads per sample. A one-way ANOVA was applied to assess the 329 proportional representation of mock mixes comprising different fluke species eggs across 330 varying PCR amplification cycles. The association between qPCR and tremabiome results 331 was assessed using Chi-squared analysis. All visualisations of data were performed in R 332 version 4.3.3 (R scripts are available at DOI: 10.17632/zyvwc6ppy8.1) 333 Phylogenetic analysis 334 Phylogenetic trees were generated from unique reference sequences of ITS2 rDNA from 21 335 different fluke species downloaded from NCBI GenBank (Table S2). The sequences were 336 aligned using the MUSCLE alignment tool in Geneious v8.0.5 (Biomatters Ltd, New Zealand) 337 and genetic distances were calculated (Table S4). Further, a phylogenetic tree of the unique 338 ITS2 rDNA sequences for all 21 fluke species and ASVs of the flukes was constructed using 339 the Neighbor-Joining method [42]. The evolutionary distances were computed using the 340 Maximum Composite Likelihood method [43] in MEGA11 [44] with a bootstrap value of 2000 341 [45]. 342

343 Fluke identification by microscopy 344 A total of 402 faecal samples were examined, out of which 128 were positive for fluke eggs. 345 The sampled animals included cattle (n=154), sheep (n=233), water buffalo (n=1), alpaca 346 (n=4), and goats (n=2), with animal species unspecified for 8 samples. Of these samples, 191 347 had a history of Fasciola infection, 119 had no history, and 92 had an unknown history 348 (Table S1). The cattle and sheep sampled represented diverse age groups, ranging from 349 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 16 calves and lambs to adults, providing a comprehensive representation of the animal host 350 population. Notably, only one sheep farm from Wales was included, and no faecal samples 351 were collected from Northern Ireland. Based on egg morphology and staining, 30 samples 352 were identified as C. daubneyi, 71 as F. hepatica, five as mixed infection, and 22 remained 353 undecided (Table S5). 354 PCR and Sanger sequencing for fluke identification and comparison with microscopy 355 Out of 128 samples positive for fluke eggs, DNA was successfully extracted from 125. PCR 356 was performed on 85 randomly selected samples using universal ITS2 primers, with bands 357 observed in 73 samples. From the 71 samples believed to be F. hepatica by microscopy, 37 358 were screened by PCR, of which 31 samples were analysed by Sanger sequencing. Of these 359 31, three were confirmed as F. hepatica, 19 as C. daubneyi and nine samples demonstrated 360 poor sequence quality. Of the 30 C. daubneyi positive samples identified by microscopy, 30 361 were screened by PCR, of which 27 samples were then analysed by Sanger Sequencing. Of 362 these 27 samples, 16 were confirmed as C. daubneyi, one was confirmed to be F. hepatica, 363 one was identified as Paramphistomum epiclitum, and nine demonstrated poor sequence 364 quality. Of the five samples which were identified as mixed infections by microscopy (F. 365 hepatica and C. daubneyi), three were screened by PCR and analysed by Sanger sequencing. 366 Of these three mixed infection samples, Sanger sequencing identified one sample as F. 367 hepatica, and two as C. daubneyi. In the 22 samples where microscopy could not determine 368 the fluke species present, 15 samples were screened by PCR, of which 14 were subsequently 369 analysed by Sanger sequencing. From these, two samples were confirmed as F. hepatica, six 370 as C. daubneyi, and six demonstrated poor sequence quality (Table 1, Table S5). 371 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 17 In addition to the ITS2 PCR and Sanger sequencing, a third PCR based diagnostic test, 372 targeting mitochondrial target mt-ND1 and specific for identifying Fasciola spp. was utilised. 373 For this, 15 samples were randomly selected within the diagnostic categories already 374 created (F. hepatica, C. daubneyi, mixed and unknown). From the two morphologically 375 identified C. daubneyi samples selected, one was confirmed as F. hepatica, while the other 376 had poor sequence quality. For instance, from the nine morphologically identified F. 377 hepatica samples, two were initially identified as F. hepatica but were confirmed as C. 378 daubneyi by ITS2, whereas mt-ND1 sequencing confirmed them as F. hepatica. This suggests 379 that microscopy failed to identify mixed infections in those two samples. Additionally, one 380 sample had poor ITS2 sequence quality but was confirmed as F. hepatica by mt-ND1 and 381 three samples were not sequenced for ITS2 but were confirmed as F. hepatica by mt-ND1. 382 Additionally, one morphologically identified mixed infection by microscopy was supported 383 by ITS2 and ND1 PCR assays and subsequent Sanger sequencing, confirming the presence of 384 C. daubneyi and F. hepatica, respectively. Among the three morphologically unidentified 385 samples, one was confirmed as C. daubneyi by ITS2, with mt-ND1 sequencing demonstrating 386 poor sequence quality, while another was not sequenced for ITS2 but confirmed as F. 387 hepatica by mt-ND1. (Table 2, Table S5). These findings highlight discrepancies between 388 morphological identification and molecular confirmation using a nuclear and mitochondrial 389 DNA target, emphasising the need for more accurate molecular techniques. 390 Detection of Fasciola species using a newly developed qPCR assay 391 To provide a simple, low-cost, sensitive, universal, and accurate molecular method for 392 diagnosing Fasciola infections in faeces, a SYBR green qPCR assay was developed using a 393 repurposed primer set targeting mt-ND1 specific to F. hepatica and F. gigantica. The assay's 394 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 18 analytical sensitivity was first assessed using quantified F. hepatica and F. gigantica adult 395 worm DNA (positive controls). The assay’s limit of detection based on a 1:5 DNA dilution 396 series was found to be 19.2 fg for F. hepatica and 6.4 fg for F. gigantica DNA. A linear 397 standard curve was generated, showing an efficiency of 97% (R² = 0.9759) for F. hepatica 398 and 99% (R² = 0.9995) for F. gigantica, demonstrating efficient primer binding and target 399 amplification. Additionally, qPCR melt curve analysis identified distinct peaks at 81.50°C for 400 F. hepatica and F. gigantica (Fig. S1, A and B), confirming the specificity of primer binding to 401 the same DNA target, and absence of nonspecific primer interactions. The specificity of the 402 qPCR assay was evaluated against DNA from other prevalent fluke and nematode species. 403 The melt curve analysis confirmed that only F. hepatica and F. gigantica produced 404 amplification peaks at 81.50°C, with no cross-amplification (Fig. S2). The assay exhibited 405 strong reproducibility, with coefficients of variation (CV) below 6.0% for intra-assay and 406 inter-assay. The mean Cq values ranged from 21.96 to 38.26 for F. hepatica with DNA 407 dilutions ranging from 300 pg to 19.2 fg and 18.62 to 38.24 for F. gigantica with DNA 408 dilutions ranging from 500 pg to 6.4 fg), maintaining consistency across replicates (Table S6). 409 To gain further clarification on which Fasciola species were present in the 128 egg-positive 410 field samples obtained, the newly developed specific SYBR green qPCR was utilised. Of the 411 128 samples screened, 57 were positive for F. hepatica, 66 were negative, and five were 412 either not determined or failed DNA extraction. 413 Comparison of microscopy and qPCR for fluke species diagnosis 414 Among the 71 samples identified as F. hepatica positive by microscopy, qPCR confirmed F. 415 hepatica in 34 samples, while 33 samples were negative, and four were not determined or 416 failed DNA extraction. From the 30 samples identified as C. daubneyi by microscopy, qPCR 417 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 19 detected F. hepatica in seven samples, whereas 23 samples tested negative. From the five 418 samples identified as mixed infections by microscopy, qPCR confirmed four as positive for F. 419 hepatica infections, while one sample tested negative. Finally, of the 22 samples which were 420 undecided using microscopy, qPCR identified 12 as F. hepatica, nine as negative, and one 421 sample was not determined or with failed DNA extraction (Table 3, Table S5). 422 Detection of fluke species using a newly developed tremabiome deep amplicon 423 sequencing method 424 To accurately identify mixed-species as well as single-species fluke infections, a tremabiome 425 deep amplicon sequencing assay was developed using a universal primer set targeting rDNA 426 ITS2, specific to fluke species. Initially, the sequence representation of three different fluke 427 species F. hepatica, F. gigantica, and C. daubneyi in the deep amplicon sequencing assay was 428 determined (Fig. 3a). This allowed the evaluation of proportional DNA sequence output reads 429 relative to known species ratios. Each species showed significant representation in the 430 sequence counts in each mix (Fig. 3a). Furthermore, the number of cycles (25X, 30X and 35X) 431 used during the adaptor PCR were validated to ensure sufficient DNA was generated for 432 sequencing whilst maintaining a balance between amplification efficiency and accuracy. 433 Whilst it is known that an appropriate number of cycles helps minimise deviations and PCR 434 bias, and over -amplification causing sequence dominanc e, we found that the number of 435 cycles did not affect the sequence representation of any species. In each mock pool, C. 436 daubneyi generated the highest number of sequence reads, followed by F. gigantica and F. 437 hepatica. Despite these trends, no statistically significant differences were observed in the 438 proportional representation of any species across the different PCR amplification cycles ( F. 439 gigantica, P = 0.730; F. hepatica, P = 0.774; and C. daubneyi, P = 0.258) (Fig. 3a) . 440 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 20 We further assessed the assay’s accuracy in identifying relative species proportions in mixed 441 infections by testing pairwise mixtures of F. hepatica and C. daubneyi eggs (Fig. 3b). This 442 range of mixes enabled thorough validation of the sequencing assay, demonstrating reliable 443 detection of the two species across egg ratios, which is essential for accurately identifying 444 species representation in mixed infections. These species were selected due to their high 445 prevalence, frequent co -occurrence in UK cattle and sheep herds, and availability in our 446 laboratory (Fig. 3b, File S1). This approach addresse d the sensitivity of deep amplicon 447 sequencing assays in detecting trace -level amplicons. We observed minimal variation in 448 species representation across different mixes, which did not affect the overall interpretation 449 of relative species abundance. For example, the 99% F. hepatica: 1% C. daubneyi mix and the 450 90% F. hepatica: 10% C. daubneyi mix displayed similar species representations further . We 451 tested the thresholds of the deep amplicon assay for fluke egg DNA with decreasing egg levels 452 in mixed populations, for example, F. hepatica and C. daubneyi (Fig. 4a and 4b, File S2, and 453 File S3). A notable observation was the production of a lower number of sequenced reads, 454 particularly for F. hepatica; however, this does not affect the identification. Importantly, the 455 assay detected both F. hepatica and C. daubneyi DNA at levels down to 5 eggs per pool. 456 After validation, the assay was applied to 125 of the 128 fluke egg-positive samples to analyse 457 fluke species distributions in natural infections in cattle and sheep. In cattle, 67 samples (eggs: 458 n=65, worms: n=2) produced sequence reads. The data revealed that F. hepatica was present 459 in 4 samples (eggs: n=2, worms: n=2), C. daubneyi in 28, and mixed infections in 35 faecal 460 samples. Similarly, in sheep, 67 samples (eggs: n=57, worms: n=10) generated sequence 461 reads. The data showed F. hepatica in 21 samples (eggs: n=11, worms: n=10), C. daubneyi in 462 23, and mixed infections in 23 faecal samples (Fig. 5, File S4). Notably, out of the 125 faecal 463 samples sequenced, 122 produced reads, as 3 samples failed to yield sequencing reads. This 464 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 21 analysis highlights a higher prevalence of mixed infections followed by C. daubneyi and F. 465 hepatica singular infections in cattle and sheep. The sequence reads of all samples were 466 aligned with F. hepatica and C. daubneyi with BLASTn (DOI: 10.17632/zyvwc6ppy8.1). 467 Finally, ASVs were generated for C. daubneyi and F. hepatica from all sequence reads of the 468 samples collected from different counties in the UK. ASVs were up to 461 bp and 527 bp for 469 C. daubneyi and F. hepatica , respectively . In total, 87 ASVs were identified, including F. 470 hepatica (n=55) and C. daubneyi (n=32) (DOI: 10.17632/zyvwc6ppy8.1). A phylogenetic tree 471 of all ASVs with reference sequences of 21 fluke species (outlined in the methodology section) 472 showed that F. hepatica and C. daubneyi species separated into distinct clades (Fig. 6). 473 Comparison of microscopy and tremabiome deep amplicon sequening for fluke species 474 diagnosis 475 Of the 71 samples identified as F. hepatica by microscopy, tremabiome detected only 11 as 476 single F. hepatica infections. However, tremabiome classified 26 of the 71 samples as C. 477 daubneyi and 30 as mixed infections, suggesting that some samples identified as F. hepatica 478 by qPCR (n=34) were mixed infections. Among the 30 samples marked as C. daubneyi by 479 microscopy, tremabiome detected two as F. hepatica, 21 as C. daubneyi, and seven as mixed 480 infections. For the microscopically recognised five mixed infections, tremabiome confirmed 481 four as mixed infections, while one was classified as C. daubneyi. Lastly, among the 22 samples 482 that were undecided by microscopy, tremabiome identified three as C. daubneyi, 17 as mixed 483 infections, and two as not determined or with failed DNA extraction (Table. 3, Table S5). 484 Comparison of qPCR and tremabiome deep amplicon sequencing for fluke species diagnosis 485 A significant correlation (p<0.001) was noted between the identification of F. hepatica 486 infections using qPCR and the tremabiome approach. Nevertheless, there were 20 samples 487 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 22 which tested negative by qPCR, but F. hepatica sequences were detected by deep amplicon 488 (three single and 17 mixed infections). Conversely, deep amplicon sequencing did not produce 489 F. hepatica reads for 8 qPCR -positive samples (Table 4, Table S5). For these samples , FECs 490 ranged from 1-221 eggs per gram of faecal material, but due to mixed infections of F. hepatica 491 and C. daubneyi, the egg counts for individual fluke species are not clear . Interestingly, C. 492 daubneyi reads were generated for the 8 samples, which were positive by Fasciola qPCR, but 493 did not have F. hepatica reads in tremabiome, despite the qPCR demonstrating no specificity 494 issues towards C. daubneyi during assay validation. 495 Comparison of Sanger sequencing and tremabiome deep amplicon sequencing for species 496 identification 497 Sanger sequencing identified 7 samples as F. hepatica of which tremabiome confirmed two 498 as F. hepatica, and five as mixed infections, and none as C. daubneyi. Among the 43 samples 499 identified as C. daubneyi by Sanger sequencing, tremabiome confirmed 29 as C. daubneyi and 500 14 as mixed infections. Notably, the sample identified as P. epiclitum by Sanger sequencing 501 was detected as F. hepatica in tremabiome sequencng (Table. 5, Table S5). 502

503 In this study we present new approaches for detecting and identifying fluke species in faecal 504 samples in the form of qPCR with high analytic al sensitivity and specificity for the detection 505 of Fasciola spp. and a deep amplicon sequencing assay which can accurately identify and 506 differentiate between closely related fluke species, such as F. hepatica, F. gigantica, and C. 507 daubneyi. These methods overcome important limitations of microscopic egg examination. 508 We selected the ITS2 and mt-ND1 genetic markers based on their previous application in fluke 509 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 23 species identification and their potential to differentiate between closely related flukes 510 [32,39]. 511 Multiple direct and indirect diagnostic approaches are available for diagnosing fluke 512 infections, each with its own set of limitations. However, farmers still require highly sensitive, 513 specific, and cost -effective early diagnostic procedures. Historically, the most widely used 514 traditional direct identification method is detecting fluke eggs in the hosts faeces. This can be 515 accomplished through various techniques such as FLOTAC [46], sedimentation, Flukefinder, 516 or the Kato -Katz thick smear method [47]. Whilst the use of fluke egg count s is simple, 517 however, this diagnostic route can be unreliable due to low intermittent egg deposition in the 518 faeces [48], and it is time-consuming and requires highly trained laboratory staff [37]. 519 Progress in the development of molecular-level diagnostic methods based on DNA detection 520 is underway, including PCR techniques [23], qPCR [22] and the LAMP approach [24]. High 521 throughput deep amplicon sequencing approach of metabarcoded DNA from parasite 522 populations using the Illumina MiSeq platform can offer a low -cost and potentially more 523 accurate alternative to traditional microscopic methods. For instance, adult Fasciola spp. and 524 C. daubneyi flukes ha ve previously been detected using tremabiome deep amplicon 525 sequencing [32–34] but this method has not been applied to the detection of eggs in faecal 526 samples. 527 In the present study, s pecies identification through m icroscopic examination was first 528 checked by PCR followed by Sanger sequencing. Our findings demonstrated that microscopy 529 has limitations in accurately identifying fluke species compared to Sanger sequencing and 530 qPCR and is a time-consuming process, as previously reported by Calvani et al., (2017) [37]. 531 Only about half of the microscopically positive samples (n=51) were confirmed by ITS2 Sanger 532 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 24 sequencing to contain F. hepatica or C. daubneyi DNA. A major contributing factor to this 533 finding could be the presence of mixed infections since fluke eggs are morphologically similar, 534 and this was confirmed by mt-ND1 Sanger sequencing [18,19]. PCR bands were observed on 535 the agarose gel for most of the samples , which indicated successful DNA amplification . 536 However, Sanger sequencing produced poor-quality sequence reads for many samples. Poor 537 sequencing quality can be due to non-specific amplifications, artefacts, and samples 538 containing mixed DNA templates from double infections [49]. Since DNA was extracted from 539 faecal material, additional factors such as low DNA concentration may also have contributed 540 to low-quality Sanger sequencing results. These findings indicated the need for more sensitive 541 and specific molecular diagnostic tools , such as qPCR and tremabiome deep amplicon 542 sequencing, to improve detection accuracy, particularly in complex natural infections. 543 We repurposed mt-ND1 markers to develop a SYBR Green qPCR assay to detect Fasciola spp. 544 The choice to use SYBR Green over fluorescence probe -based systems was due to its cost -545 effectiveness and simplicity. In contrast , previous studies used TaqMan probes to identify 546 Fasciola species [22,37,50]. Our assay's analytical sensitivity (19.2 fg for F. hepatica and 6.4 fg 547 for F. gigantica DNA) is lower than that reported in previous studies. For instance, Shi et al. , 548 (2020) achieved a detection limit of 1.67 pg of DNA using a SYBR Green qPCR assay targeting 549 the ITS2 region [51]. Similarly, previous studies have demonstrated the ability to detect F. 550 hepatica at levels below 10 eggs per gram directly from 150 mg of faecal material using a 551 TaqMan qPCR assay [37] and sensitivities as low as 1 pg/μL [22] and 1.6 pg/μL when targeting 552 the ITS1 region [52]. F. hepatica eDNA (14-50 fg) was detected in water samples with similar 553 sensitivity to our assay [53]. In 2024, a qPCR assay was reported which could detect 10 fg of 554 Fasciola DNA in water and 1 pg in human stool samples [54]. A limitation of our study is that 555 qPCR was only performed on fluke egg-positive samples due to limited resources. Thus, it was 556 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 25 not possible to formally determine diagnostic performance. This will be determined in future 557 work. The diagnostic sensitivity of other qPCR methods was reported to be 66% in human 558 stool samples [52] and 91 –100% in sheep and cattle compared to microscopy-based 559 techniques [37]. These estimates assume, however, that microscopy is the gold standard, 560 whereas it could miss positive cases that are detectable using molecular methods. 561 A limitation of our qPCR assay is that we are only able to detect Fasciola in DNA extracted 562 from sedimented material, not DNA extracted directly from faecal samples. Raw faecal 563 samples were tested in this study using the same DNA extraction methodology as 564 sedimented eggs, but it was not possible to detect Fasciola DNA using the qPCR 565 methodology described in the study (data not shown). However, sensitivity improved when 566 Fasciola eggs were first concentrated using faecal egg sedimentation before applying the 567 bead-beating approach for DNA isolation [37]. Similarly, other studies also employed 568 molecular procedures following the sedimentation process [18,50,55], and a few studies 569 have applied molecular techniques to detect natural Fasciola infections directly from faecal 570

and reported limitations [37,55]. One possible approach is LAMP [56], as this has 571 demonstrated low detection limits for Fasciola spp. DNA and results can be observed with 572 the naked eye [24,25]. A recent study successfully detected F. hepatica in DNA extracted 573 directly from faeces with a commercial kit, using both LAMP and PCR methodology targeting 574 ITS2 region [57]. Further work is needed to simplify extraction protocols. 575 In ruminants, fluke species often occur in complex and overlapping infections; for instance, F. 576 hepatica and C. daubneyi co-infections have been observed in cattle and sheep in the UK 577 [58,59] and the same has been reported elsewhere in Europe [18,60], including in Ireland [61] 578 and Germany [62]. We found that the microscopic egg identification for closely related flukes, 579 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 26 such as F. hepatica and C. daubneyi , is challenging due to their similar size and shape. 580 Therefore, the tremabiome technology was developed utilising universal ITS2 rDNA markers 581 to differentiate between multiple fluke species . The techniques were validated using fluke 582 egg DNA, isolated from faecal samples. To our knowledge, this is first time the tremabiome 583 deep amplicon sequencing approach has been applied to detect mixed fluke infections in 584 faeces. Previously the approach was applied to detect adult fluke samples [33,34]. 585 The tremabiome technique generated sequence reads for F. hepatica, F. gigantica, and C. 586 daubneyi. However, the proportion of sequence reads deviated from expected percentages . 587 For instance, we evaluated the assay's ability to accurately determine the relative species 588 proportions in pairwise combinations of F. hepatica and C. daubneyi. The results consistently 589 showed a higher proportion of reads for C. daubneyi compared to F. hepatica across all 590 mixtures. Such variation may arise from factors including the primers used for the target loci, 591 conserved priming sites, variations in DNA template concentrations during sample handling, 592 the number of PCR cycles, and the copy number of the target DNA locus [63]. Previously, for 593 nematodes, species-specific representation biases were addressed by calculating correction 594 factors using L3 larva l population DNA from different nematode species [29]. In the present 595 study, while working with fluke egg DNA obtained via faecal sedimentation , calculation of 596 correction factors did not remove sequence biases (File S5). This might be due to differences 597 in the eggshell chemistry or stability hardness of eggshells that has been described between 598 F. hepatica and C. daubneyi [64], leading to variations in DNA extraction efficiency. However, 599 we employed mechanical disruption before DNA isolation to mitigate this issue [37]. 600 Additionally, we used universal ITS2 primers to detect multiple fluke species in a single deep 601 amplicon sequencing run. Using species -specific primers in deep amplicon sequencing could 602 be a potential solution to reduce sequence biases [65]. Further, bioinformatics analysis of 603 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 27 sequencing data might introduce biases, leading to inaccuracies in species proportion 604 estimations. One major challenge can be the limited availability of reference sequence reads 605 in the NCBI database, for example, for F. hepatica 50 unique sequences and for C. daubneyi 606 19 unique sequences were found , which can impact species specific reads identification. 607 Additionally, taxa represented by low numbers of sequencing reads may pose a problem, as 608 these low -frequency reads were removed during data filtering while eliminating artefacts, 609 resulting in the underrepresentation of actual sequence reads. Therefore, there is a need for 610 more reference sequence data, which can enhance our capability of accurately distinguishing 611 true sequences. When the tremabiome technology was applied to field samples , many F. 612 hepatica and C. daubneyi co-infections were identified. Since F. hepatica is more pathogenic 613 and economically detrimental [6,66] than C. daubneyi [67,68], and treatment choices differ, 614 our method provides a valuable tool for differentiating co -infections of these two significant 615 parasites using faecal egg samples. 616 When applying the tremabiome approach to field samples, just over half of the 617 microscopically positive F. hepatica samples were confirmed by tremabiome deep amplicon 618 sequencing. Moreover, there was a significant correlation between the identification of F. 619 hepatica infections using qPCR and the tremabiome approach. Notably, the tremabiome 620 approach generated F. hepatica sequence reads in samples which tested negative by qPCR. 621 Conversely, tremabiome deep amplicon sequencing did not produce F. hepatica reads for a 622 few qPCR-positive samples. It has been reported that false negative results for molecular tests 623 may be due to low egg count in faecal samples [18]. Furthermore, one sample identified as P. 624 epiclitum by Sanger sequencing was not confirmed by tremabiome, which instead identified 625 it as F. hepatica . Previously P. leydeni has been reported in sheep [69], and deer [70] in 626 Ireland, but was not identified in the UK in our study. Therefore, each method has limitations, 627 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 28 but tremabiome remained the preferred tool for species -level fluke identification as it can 628 identify mixed infections. 629 Regarding the implementation of these methods, microscopy can be a suitable option for 630 analysing a small number of samples due to its low cost and accessibility, although, there were 631 potential issues of misidentifications [18,37]. In particular, a high proportion of samples 632 identified as positive for F. hepatica based on egg morphology were confirmed by 633 tremabiome to contain C. daubneyi, despite careful identification. For medium to high sample 634 volumes, qPCR is suitable to identify Fasciola spp. infections only and tremabiome deep 635 amplicon sequencing is potentially more effective choices for species level differentiation of 636 different flukes with an advantage of high throughput, as a single Illumina MiSeq run can 637 process up to 384 samples simultaneously. This capability makes the method suitable for both 638 research and diagnostic applications . Presently, t his study offers evidence of the high 639 prevalence of F. hepatica and C. daubneyi in UK ruminants. Expanding this method to larger 640 sample sizes across the UK and in other countries would provide a more comprehensive 641 epidemiological understanding of these infections. 642 The sequencing data generated from the set of natural field samples enhanced our 643 understanding of the genetic variation within fluke populations by revealing their ASVs . 644 Notably with ITS2 markers , we observed more ASVs for F. hepatica than C. daubneyi , 645 indicating possible greater genetic diversity within F. hepatica populations. Previously, 646 Fasciola species in Pakistan were differentiated using ITS2 markers in adult worms [32,39], 647 while high genetic diversity was reported using mt -ND1 markers [32,33]. Similarly, a study 648 from Spain and Peru identified Fasciola flukes using nuclear DNA markers but reported high 649 genetic diversity based on mitochondrial markers [71]. Further, high genetic diversity and 650 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 29 gene flow among Fasciola populations have been reported i n the UK, using microsatellite 651 markers [72,73]. Therefore, t he ITS2 rDNA provides a useful taxonomic resolution [32,39], 652 however, mitochondrial markers such as (ND1 and COX1) and genetic markers are typically 653 preferred for detailed population genetic studies [33,71,72,74–76]. Therefore, further 654 investigations using mitochondrial ND1 and nuclear genetic markers are required to 655 understand the genetic diversity of these fluke populations and is work in progress. 656 Although validated on cattle and sheep samples in this study, both the qPCR and tremabiome 657

have a strong potential for the Fasciola spp. d etection in humans, particularly in 658 endemic regions where there is a possibility of zoonotic transmission of F. hepatica and F. 659 gigantica. Application of these methods on human faecal samples could improve case 660 detection, fluke species identification, and epidemiological understanding. 661

662 In conclusion, this study presents the first use of tremabiome deep amplicon sequencing for 663 detecting mixed infections of F. hepatica and C. daubneyi, and provides a direct comparison 664 between microscopy, PCR, Sanger sequencing, qPCR and tremabiome methods for 665 differentiating between fluke species. The tremabiome approach was highly effective for 666 detecting mixed fluke infections, compared to other techniques utilised in this study, 667 demonstrating high frequency of C. daubneyi and F. hepatica co-infections in farmed 668 ruminants in the UK. The methods were primarily validated using samples from natural 669 infections, with DNA extracted from faecal sedimented eggs, which allowed an easy and 670 non-invasive sampling approach at the farm level. Tremabiome and qPCR are promising 671 tools to complement microscopy in fluke disease surveillance and control in livestock and 672 humans. 673 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 30 Supporting information 674 675 File S1 Relative proportions of F. hepatica and C. daubneyi in egg DNA mixtures (XLSX) 676 File S2 Mock egg mixtures with gradually decreasing counts of F. hepatica eggs (XLSX) 677 File S3 Mock egg mixtures with gradually decreasing counts of C. daubneyi eggs (XLSX) 678 File S4 Deep amplicon sequence reads generated from field samples from cattle and 679 sheep (XLSX) 680 File S5 Correction factors calculations (PDF) 681 Table S1 Sample information (XLSX) 682 Table S2 Reference sequences downloaded from NCBI and unique sequence count (XLSX) 683 Table S3 mt-ND1 and ITS2 primer sequences (PDF) 684 Table S4 Genetic distances for different fluke species based on ITS2 marker (XLSX) 685 Table S5 Sample (n=128) details used for comparison of techniques for microscopy, PCR, 686 Sanger sequencing, qPCR, and tremabiome (XLSX) 687 Table S6 Coefficients of variation for qPCR (PDF) 688 Fig. S1 and Fig. S2 Analytical sensitivity and specificity of qPCR (PDF) 689

690 Part of this work was carried out using the computational HPC facilities and support provided 691 by the Research Computing Services team within IT Services at University of Surrey, 692 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 31 specifically the Eureka2 HPC cluster 693 (https://docs.pages.surrey.ac.uk/research_computing/hpc/clusters/eureka2.html). 694 This research was funded in whole, or in part, by the UK Research and Innovation (UKRI), 695 Biotechnology and Biological Sciences Research Council (BBSRC) through the FoodBioSystems 696 Doctoral Training Programme (BB/T008776/1) and the Sir Halley Stewart Trust (3153). For the 697 purpose of Open Access, the author s have applied a Creative Commons Attribution (CC BY) 698 public copyright licence to any Author Accepted Manuscript version arising from this 699 submission. 700 Credit authorship contribution statement 701 Muhammad Abbas : conceptualisation, investigation, methodology, bioinformatics, 702 validation, visualisation, data curations and analysis, writing original draft, review and editing; 703 Kezia Kozel : investigation, methodology, formal analysis, validation, writing original draft , 704 review and editing; Olukayode Daramola: writing original draft, review, formal analysis, data 705 curation, supervision; Nick Selemetas: review and editing, supervision; Qasim Ali: resources; 706 Shoaib Ashraf : resources; Isah Ibrahim : resources; Inaki Deza -Cruz: resources; review and 707 editing; Sai Fingerhood: resources; review and editing; Mark W Robinson: resources; review 708 and editing ; Eric R Morgan: funding acquisition; supervision, review and editing ; Umer 709 Chaudhry: conceptualisation, formal analysis, validation, data curation, writing, review and 710 editing, supervision; Martha Betson: conceptualisation, formal analysis, writing review and 711 editing, supervision, funding acquisition, project administration. 712 Data availability 713 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 32 All sequencing data produced in the paper are available at NCBI BioProject ID PRJNA1273189, 714 and accession numbers PV752160 -PV752182, PV752186 -PV752205, PV752431 -PV752462, 715 PV752238-PV752240, PV752248-PV752250, PV752375-PV752429, PV752270. 716 In addition, sequence data, scripts and codes are available at Mendeley data base DOI: 717 10.17632/zyvwc6ppy8.1. 718 All other data are reported in the paper and associated supplementary material. 719 Funding 720 Muhammad Abbas received funding from the UK Research and Innovation (UKRI), 721 Biotechnology and Biological Sciences Research Council (BBSRC) through the FoodBioSystems 722 Doctoral Training Programme for project ID FBS2022 titled “New tools for sustainable control 723 of liver fluke in ruminants” Grant Ref: BB/T008776/1 . Further, t his research was funded by 724 the Sir Halley Stewart Trust under the project “Rapid Diagnostics for Neglected Parasites.” 725 Competing Interest 726 The authors declare that no financial interests or personal relationships could have influenced 727 the work reported in this paper. 728

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Genetic 966 diversity and population structure of Fasciola gigantica isolated from cattle in Malawi. Vet 967 Res Commun. 2025;49: 157. doi:10.1007/s11259-025-10717-9 968 969 970 971 972 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 39 973 974 975 976 977 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 40 978 979 Fig. 1: Developmemt of qPCR and tremabiome 980 (a) Workflow adopted for developing qPCR and screening of faecal samples for the presence 981 of F. hepatica infection. (b) Overview of development of the tremabiome method and its 982 application on natural fluke infections in ruminants in the UK. 983 984 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 41 985 Fig. 2: Neighbor-Joining tree generated for fluke species including reference sequences of 21 986 different fluke species. The reference sequences were downloaded from NCBI data, and 154 987 unique sequences were selected and aligned (Table S2, DOI: 10.17632/zyvwc6ppy8.1). 988 Different fluke species are indicated with symbols of different colours and shapes. F. 989 hepatica red triangle, F. gigantica black triangle, C. daubneyi black circle, Paramphistomum 990 leydeni red diamond, P. cervi grey diamond, C. microbothrium light blue circle, P. epiclitum 991 black diamond, Gastrothylax crumenifer triangle with red boundary no fill, Fischoederius 992 elongatus triangle with black boundary no fill, Dicrocoelium dendriticum red square, C. 993 calicophorum yellow circle, Fischoederius cobboldi circle with black boundary no fill, C. 994 microbothrioides red circle, Homalogaster paloniae circle with light blue boundary no fill, E. 995 explanatum square with black boundary no fill, C. raja grey circle, Watsonius watsoni 996 triangle with dark blue border no fill, Gastrodiscoides hominis triangle with light blue 997 boundary no fill, D. orientalis black square, D. hospes grey square, and Dicrocoelium 998 chinensis dark blue square. 999 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 42 1000 1001 1002 Fig. 3: Sequence representation of the mock mixture of fluke species in deep amplicon 1003 sequencing. 1004 (a) F. hepatica, F. gigantica, and C. daubneyi. DNA was extracted in triplicate from pooled 1005 samples containing 250 eggs of each species. The DNA mixture was amplified using PCR at 1006 three cycle levels (25X, 30X, and 35X), with triplicate testing for each pool. The x-axis 1007 indicates PCR cycle numbers, while the y-axis represents each species' percentage of ITS2 1008 rDNA sequence reads. Triplicates were averaged and grouped based on the amplification 1009 cycles in the last three columns. (b) Relative proportions of F. hepatica and C. daubneyi in 1010 egg DNA mixtures were assessed using deep amplicon sequencing. DNA was extracted from 1011 mock pools containing varying ratios of these two fluke species, enabling evaluation of the 1012 assay’s accuracy across a range of species proportions. The x-axis represents egg mixtures 1013 with varying F. hepatica: C. daubneyi ratios: M1 (negative control), M2 (99:1), M3 (90:10), 1014 M4 (70:30), M5 (50:50), M6 (30:70), M7 (10:90), M8 (1:99), M9 (100% C. daubneyi), and 1015 M10 (100% F. hepatica). The y-axis shows the percentage of ITS2 rDNA sequence reads for 1016 each species. 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 43 1028 1029 1030 1031 Fig. 4. Threshold of deep amplicon sequencing 1032 Application of deep amplicon sequencing to mock egg mixtures with gradually lower counts 1033 of F. hepatica and C. daubneyi eggs. Two sets of mixtures were designed using eggs from 1034 four fluke species (F. hepatica, F. gigantica, E. explanatum, and C. daubneyi). In panel (a), 1035 which focuses on F. hepatica, MM1 contained 500 eggs of F. hepatica along with 50 eggs of 1036 each of the other three species, creating a high relative abundance of F. hepatica. In 1037 mixtures MM2 through MM6, the number of F. hepatica eggs was reduced to 50, 20, 15 5, 1038 and 0 eggs, respectively, while the counts for the other three fluke species remained 1039 constant at 50 eggs. Panel (b) follows a similar design but targets C. daubneyi: MM1 1040 contained 500 eggs of C. daubneyi plus 50 eggs each of F. hepatica, F. gigantica, and E. 1041 explanatum, and in mixtures MM2 to MM6 the number of C. daubneyi eggs was reduced to 1042 50, 20, 15, 5, and 0 eggs, with the other species maintained at 50 eggs each. Additionally, 1043 single-species control pools were included as MM7 (F. hepatica), MM8 (F. gigantica), MM9 1044 (E. explanatum), and MM10 (C. daubneyi), each containing 50 eggs. The assay results show 1045 the ability to detect and accurately quantify trace levels of target DNA in mixed fluke egg 1046 populations. 1047 1048 1049 1050 1051 1052 1053 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 44 1054 Fig. 5: Tremabiome deep amplicon sequencing application on the field samples 1055 This figure illustrates the application of the tremabiome deep amplicon sequencing assay 1056 on DNA extracted from sedimented faecal eggs and adult worm populations collected from 1057 cattle and sheep across various regions in the UK. The charts display species proportions 1058 based on the percentage of sequence reads generated after 35 amplification cycles. 1059 Percentages of F. hepatica are represented in blue and C. daubneyi in green on the Y-axis. 1060 (a) Samples from cattle. (b) Samples from sheep. 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 45 1073 1074 Fig. 6: A Neighbor-Joining tree of rDNA ITS2 sequences constructed using 154 reference 1075 sequences of different fluke species downloaded from the NCBI database, along with 87 1076 ASVs identified in this study 55 from F. hepatica and 32 from C. daubneyi. ASVs 1077 corresponding to F. hepatica are marked with blue triangles, while those of C. daubneyi are 1078 represented by blue circles. The ASVs clustered closely with their respective reference taxa, 1079 confirming accurate taxonomic assignment. 1080 1081 1082 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 46 1083 Table. 1: Comparison of microscopy, ITS2 PCR and Sanger sequencing on fluke egg-positive samples 1084 Microscopy PCR Sanger sequencing using ITS2 Negative Positive Not performed ND2 Total F. hepatica C. daubneyi Paramphistomum epiclitum PSQ Not performed ND2 Total F. hepatica 7 30 32 2 71 3 19 0 9 38 2 71 C. daubneyi 4 26 0 0 30 1 16 1 9 3 0 30 Mixed 0 3 2 0 5 1 2 0 0 2 0 5 Fluke1 1 14 6 1 22 2 6 0 6 7 1 22 Total 12 73 40 3 128 7 43 1 24 50 3 128 1Unidentified flukes; 2 ND = DNA extraction failed; PSQ = poor sequence quality 1085 1086 1087 Table. 2: Comparison of microscopy and Sanger sequencing using mt-ND-1 markers on fluke egg-positive samples 1088 Microscopy Sanger sequencing using ND1 F. hepatica C. daubneyi PSQ Not performed ND2 Total F. hepatica 6 0 3 60 2 71 C. daubneyi 1 0 1 28 0 30 Mixed 1 0 0 4 0 5 Fluke1 1 0 2 18 1 22 Total 9 0 6 110 3 128 1Unidentified flukes; 2 ND = DNA extraction failed; PSQ = poor sequence quality 1089 1090 1091 1092 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 47 Table. 3: Comparison of microscopy, qPCR (for F. hepatica) and tremabiome on 128 fluke egg-positive samples 1093 Microscopy qPCR Tremabiome Negative Positive ND NP Total F. hepatica C. daubneyi Mixed ND2 No reads Total F. hepatica 33 34 2 2 71 11 26 30 2 2 71 C. daubneyi 23 7 0 0 30 2 21 7 0 0 30 Mixed 1 4 0 0 5 0 1 4 0 0 5 Fluke1 9 12 1 0 22 0 3 17 1 1 22 Total 66 57 3 2 128 13 51 58 3 3 128 1Unidentified flukes; 2 ND = DNA extraction failed; NP=Not performed 1094 1095 1096 Table. 4: Comparison of qPCR and tremabiome on 128 fluke egg-positive samples 1097 qPCR Tremabiome C. daubneyi F. hepatica Mixed ND No reads Total Negative 43 3 17 0 3 66 F. hepatica 8 10 39 0 0 57 ND 0 0 0 3 0 3 NP 0 0 2 0 0 2 Total 51 13 58 3 3 128 ND = DNA extraction failed, NP =Not performed 1098 1099 1100 1101 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is The copyright holder for this preprintthis version posted August 2, 2025. ; https://doi.org/10.1101/2025.07.31.667929doi: bioRxiv preprint 48 1102 Table. 5: Comparison of Sanger sequencing and tremabiome on selected samples 1103 Tremabiome Sanger sequencing using ITS2 F. hepatica C. daubneyi Paramphistomum epiclitum PSQ Not performed ND1 Total F. hepatica 2 0 1 2 8 0 13 C. daubneyi 0 29 0 9 13 0 51 Mixed 5 14 0 10 29 0 58 No reads 0 0 0 3 0 0 3 ND 0 0 0 0 0 3 3 Total 7 43 1 24 50 3 128 1ND = DNA extraction failed; PSQ = poor sequence quality 1104 1105 .CC-BY 4.0 International licensemade available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. 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