Fig 1.
Development of qPCR and criteria for sample inclusion and exclusion.
(a) Workflow adopted for developing qPCR and screening of faecal samples for the presence of Fasciola infection mainly in sheep and cattle. (b) Flow diagram indicating the number of samples included and excluded from testing using different fluke detection methods in this study. Samples were excluded from testing based on specific criteria, including absence of fluke eggs, failed DNA extraction, poor sequence quality, non-specific amplification, absence of sequence reads, or insufficient DNA. https://BioRender.com/dkxo0ek.
Table 1.
Fluke species identification by microscopy, ITS2 PCR, and Sanger sequencing on fluke egg-positive samples (n = 128).
Fig 2.
Receiver Operating Characteristic (ROC) curves to investigate agreement between microscopy, qPCR, Sanger sequencing, and deep amplicon sequencing for identification of fluke species in microscopy positive faecal samples.
Each panel shows the ROC curve comparing two methods (A) microscopy and Sanger sequencing (B) microscopy and qPCR, (C) microscopy and deep amplicon sequencing, (D) qPCR and deep amplicon sequencing, (E) deep amplicon sequencing and Sanger sequencing. Blue curves represent F. hepatica and red curves represent rumen flukes (C. daubneyi + P. epiclitum). The area under the curve (AUC) values are displayed in the legends. The x-axis represents the false positive rate (1 – specificity) and the y-axis represents the true positive rate (sensitivity). A diagonal dashed line indicates random classification performance (AUC = 0.5).
Fig 3.
Sensitivity of qPCR targeting mt-ND1 mitochondrial DNA of (A) F. hepatica and (B) F. gigantica.
The standard curve was plotted using qPCR data from 5-fold serial dilutions of adult worm DNA extracted from the head of F. hepatica and F. gigantica. DNA quantification was performed using Qubit. The average Cq values from three replicates were plotted against the DNA quantity to create the standard curve. The amplification profiles and melt curves for F. hepatica and F. gigantica at 81.5°C and 82°C respectively are also shown.
Table 2.
Variation in F. hepatica and F. gigantica SYBR green qPCR Cq values within and between assays using data from the test of analytical sensitivity.
Fig 4.
Specificity of mt-ND1 primers in qPCR for amplification of F. hepatica and F. gigantica.
(A) Specificity of mt-ND1 primers evaluated with DNA of other flukes, Paramphistomum, E. explanatum, and C. daubneyi. (B) Specificity of mt-ND1 primers tested with DNA of the nematode, T. circumcincta. Amplification curves are shown on the left-hand side and melt curves on the right-hand side. There is no cross-amplification with non-target species in any of the reactions.
Table 3.
Fluke species identification by microscopy, qPCR (for F. hepatica), and deep amplicon sequencing on 128 fluke egg-positive samples.
Fig 5.
Correlation of fluke egg count (FEC) per gram of faecal material with Cq values observed in qPCR from natural Fasciola infections.
A scatterplot of qPCR-positive samples is shown as red circles. The dotted red line indicates a simple linear regression analysis. Significant correlation (p = 0.00026, R2 = 0.22) was noted for between egg counts and Cq values, with higher egg counts was associated with lower Cq values.
Fig 6.
Sequence representation of the mock mixture of fluke species in deep amplicon sequencing.
(a) F. hepatica, F. gigantica, and C. daubneyi. DNA was extracted in triplicate from pooled samples containing 250 eggs of each species. The DNA mixture was amplified using PCR with different numbers of cycles (25 ×, 30 ×, and 35×), with triplicate testing for each pool. The x-axis indicates PCR cycle number, while the y-axis represents the percentage of ITS2 rDNA sequence reads for each species. Triplicate runs were grouped based on the number of amplification cycles and averages are displayed in the last three columns. (b) Relative proportions of F. hepatica and C. daubneyi in egg DNA mixtures were assessed using deep amplicon sequencing. DNA was extracted from mock pools containing varying ratios of these two fluke species, enabling evaluation of the assay’s accuracy across a range of species mixes. The x-axis represents egg mixtures with varying F. hepatica: C. daubneyi ratios: M1 (negative control), M2 (99:1), M3 (90:10), M4 (70:30), M5 (50:50), M6 (30:70), M7 (10:90), M8 (1:99), M9 (100% C. daubneyi), and M10 (100% F. hepatica). The y-axis shows the percentage of ITS2 rDNA sequence reads for each species.
Fig 7.
Threshold of deep amplicon sequencing.
Application of deep amplicon sequencing was assessed in mock egg mixtures with gradually decreasing counts of F. hepatica and C. daubneyi eggs. Two sets of mixtures were designed using eggs from four fluke species (F. hepatica, F. gigantica, E. explanatum and C. daubneyi). In panel (a), which focuses on F. hepatica, MM1 contained 500 eggs of F. hepatica along with 50 eggs of each of the other three species, creating a high relative abundance of F. hepatica. In mixtures MM2 through MM6, the number of F. hepatica eggs was reduced to 50, 20, 15, 5 and 0 eggs, respectively, while the counts for the other three fluke species remained constant at 50 eggs. Panel (b) follows a similar design but targets C. daubneyi: MM1 contained 500 eggs of C. daubneyi plus 50 eggs each of F. hepatica, F. gigantica, and E. explanatum, and in mixtures MM2 to MM6 the number of C. daubneyi eggs was reduced to 50, 20, 15, 5 and 0 eggs, with the other species maintained at 50 eggs each. Additionally, single-species control pools were included as MM7 (F. hepatica), MM8 (F. gigantica), MM9 (E. explanatum), and MM10 (C. daubneyi), each containing 50 eggs. The assay results show the ability to detect and accurately quantify trace levels of target DNA in mixed fluke egg populations.
Fig 8.
Deep amplicon sequencing applied to field samples.
This figure illustrates the application of the deep amplicon sequencing assay on DNA extracted from sedimented faecal eggs and adult worm populations collected from cattle and sheep across various regions in the UK. The charts displays five groups based morphological identification by microscopy including C. daubneyi, F. hepatica, fluke (unspeciated samples), mixed eggs and worms (adult F. hepatica worms). Eggs per gram for each sample is shown above the bars. Percentage bars show species sequence reads obtained from deep sequencing generated after 35 amplification cycles. F. hepatica read percentages are represented in blue and C. daubneyi in green. (a) Samples from cattle. (b) Samples from sheep.
Fig 9.
Neighbour-joining tree of rDNA ITS2 sequences constructed using 154 reference sequences of different fluke species downloaded from the NCBI database, along with 87 ASVs identified in this study, 55 from F. hepatica and 32 from C. daubneyi.
ASVs corresponding to F. hepatica are marked with blue triangles, while those of C. daubneyi are represented by blue circles. The black triangles indicate F. hepatica, white triangles indicate F. gigantica and black circles indicate C. daubneyi sequences from the NCBI database. The ASVs clustered closely with their respective reference taxa, confirming accurate taxonomic assignment.
Table 4.
Fluke species identification by qPCR and deep amplicon sequencing on 128 fluke egg-positive samples.
Table 5.
Fluke species identification by Sanger sequencing and deep amplicon sequencing on 128 fluke egg-positive samples.