Lobanov et al. Parasites & Vectors (2023) 16:466 https://doi.org/10.1186/s13071-023-06035-1 RESEARCH Identification of Trichinella taxa by ITS-1 amplicon next-generation sequencing with an improved resolution for detecting underrepresented genotypes in mixed natural infections Vladislav A. Lobanov1*, Kelly A. Konecsni1, W. Brad Scandrett1 and Emily J. Jenkins2 Abstract Background Amplicon-based next-generation sequencing (NGS) has rapidly gained popularity as a powerful method for delineating taxa in complex communities, including helminths. Here, we applied this approach to identify species and genotypes of zoonotic nematodes of the Trichinella genus. A known limitation of the current multiplex PCR (mPCR) assay recommended by the International Commission on Trichinellosis is that it does not differentiate Trichinella nativa from T. chanchalensis. Methods The new assay entails deep sequencing of an amplified variable fragment of the ribosomal cistron’s (rDNA) internal transcribed spacer 1 using the Illumina platform. The assay was evaluated using first-stage larvae (L1) of select laboratory strains of various Trichinella taxa mixed in known proportions and then validated using archived L1 from 109 wildlife hosts. The species/genotypes of these L1 isolates from wildlife were previously determined using mPCR. Results NGS data analysis for Trichinella laboratory strains selected as representative of North American fauna revealed a sequence representation bias. Trichinella pseudospiralis, a non-encapsulated species, was the most under- represented when mixed with T. spiralis, T. murrelli, T. nativa and Trichinella T6 in equal quantities. However, five L1 of T. pseudospiralis were readily revealed by NGS in a mix with 2000 L1 of T. nativa (1:400 ratio). From naturally infected wildlife, all Trichinella taxa revealed by mPCR were also identified by NGS in 103 of 107 (96.3%) samples amplified on both assays. NGS identified additional taxa in 11 (10.3%) samples, whereas additional taxa were revealed by mPCR in only four (3.7%) samples. Most isolates comprised single or mixed infections of T. nativa and Trichinella T6. On NGS, T. chanchalensis (T13) was detected in combination with Trichinella T6 in a wolverine (Gulo gulo) and in combination with T. nativa and Trichinella T6 in a marten (Martes americana) from the Northwest Territories, Canada. Conclusions This new NGS assay demonstrates strong potential as a single assay for identifying all recognised Trich- inella taxa as well as improved sensitivity for detecting under-represented and novel genotypes in mixed infections. In addition, we report a new host record for T. chanchalensis in American marten. Open Access © Crown 2023. Parasites & Vectors *Correspondence: Vladislav A. Lobanov vladislav.lobanov@inspection.gc.ca Full list of author information is available at the end of the article http://crossmark.crossref.org/dialog/?doi=10.1186/s13071-023-06035-1&domain=pdf Page 2 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 Background All known taxa of the parasitic nematodes in the genus Trichinella are considered capable of causing trichinello- sis in humans, a globally significant food-borne zoonotic disease. This zoonosis has been chiefly associated with the consumption of pork, omnivorous or carnivorous wild game and horse meat [1]. The recent discovery of a new member of this genus named Trichinella chancha- lensis in wolverines from northwestern Canada brought the number of recognised taxa to 13 [2]. Among them are 10 named species and three unnamed genotypes divided into two evolutionary clades characterised by the pres- ence or absence of a collagen capsule surrounding the infective L1. Encapsulated taxa are confined to mammals, whereas non-encapsulated species are found in either mammals and birds or mammals and reptiles [3]. The only species responsible for the domestic cycle involving pigs and synanthropic rats is T. spiralis [4]. This species is highly adapted to swine, as substantiated by its high reproductive capacity and prolonged survival of infective L1 in the striated muscle of this host [5]. Epide- miological data suggest that the occurrence of T. spiralis in wildlife (sylvatic cycle) is caused mainly by spillover from the domestic cycle [6]. The controlled management conditions under which swine are raised in industrial- ised countries and regulations for trichinellosis control have substantially reduced the risk of such spillover and acquiring this disease from commercially produced pork. Nowadays, trichinellosis cases in such countries are mainly linked to the consumption of insufficiently cooked or processed game meat (such as wild boar, bear and wal- rus) harbouring sylvatic Trichinella spp. [7]. Except for T. pseudospiralis, sylvatic Trichinella spp. found in North America have very low infectivity for swine and thus constitute a negligible risk of introduction into commer- cial pig herds (reviewed in [8]). However, the infectivity of T. chanchalensis for swine and other livestock species remains to be determined. Continuous risk-based moni- toring of indicator wildlife hosts for Trichinella spp. is, therefore, required to support claims of negligible risk status of the commercial swine population [9]. Direct detection of Trichinella L1 in striated mus- cle from known predilection sites by artificial digestion followed by microscopic examination of the resultant sediment is the internationally accepted method for food safety and epidemiological surveillance [10, 11]. However, identifying isolated L1 requires molecular genotyping methods as they are morphologically indis- tinguishable amongst the different Trichinella taxa [12]. A conventional multiplex PCR (mPCR) targeting the internal transcribed spacers 1 and 2 and the large subu- nit’s expansion segment five of rDNA is currently the most widely used method for identifying Trichinella spp. [13]. This genotyping method endorsed by the Interna- tional Commission on Trichinellosis (ICT) enables reli- able differentiation of most Trichinella taxa. However, ancillary methods are required to distinguish T. nativa from T. chanchalensis (sympatric in North America) and T. patagoniensis, or T. britovi from Trichinella genotypes T8 and T9 [2, 12]. A real-time PCR with high-resolution melting analysis that differentiated eight Trichinella spp. has also been described [14]. However, this assay and mPCR require several individual larva preparations to detect co-infections with two or more Trichinella spp. Such co-infections are common in sentinel host species from geographic areas where different Trichinella spp. occur in sympatry [15, 16]. However, individual larva preparations are labour-intensive and likely underes- timate the prevalences of co-infections with different Trichinella spp. NGS methods may enable a higher sensitivity for detecting underrepresented species in mixed infections. A growing number of published studies have described the species composition of complex parasitic nematode communities using DNA metabarcoding by deep ampli- con NGS in various livestock and wildlife host species [17–23]. In the current study, we leveraged this NGS approach for genotyping Trichinella spp. and demon- strated its utility in identifying genotypes of these para- sitic nematodes isolated from various wildlife hosts in North America and elsewhere, including differentiating the newly discovered T. chanchalensis from T. nativa, which is currently difficult with commonly used assays. Methods Parasite material The laboratory strains of sylvatic Trichinella spp. and T. spiralis described below have been maintained at the Center for Food-borne and Animal Parasitology (CFAP) by serial passages in CD-1 mice (Charles River) and Sprague-Dawley rats (Charles River), respectively. L1s of these strains were isolated from skinned and evis- cerated carcasses of the infected rodents (from 146 to 451 days post-infection) by the pepsin and hydrochloric acid magnetic stirrer artificial digestion method [24] and stored in phosphate-buffered saline (PBS) at − 70 °C until use. Laboratory animal use protocols were approved by the Animal Research Ethics Board of the University of Keywords Trichinella, Next-generation sequencing, Genotyping method, Wildlife surveillance Page 3 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 Saskatchewan and adhered to the Canadian Council on Animal Care guidelines for humane animal use. The T. nativa strain was initially isolated in 2013 from a natu- rally infected walrus (Odobenus rosmarus) from Nunavik (Quebec, Canada). The T. murrelli and T. pseudospiralis strains were first isolated from muscle tissue samples of naturally infected cougars (Puma concolor cougar) from British Columbia, Canada, received in 2001 and 2004, respectively. The T. spiralis strain was isolated in 2013 from meat products from a naturally infected, non-com- mercially raised domestic pig in southwest Ontario, Can- ada [25]. Trichinella T6 (ISS 40) and T. britovi (ISS 107) were initially obtained from the International Trichinella Reference Centre (ITRC) repository (Istituto Superiore di Sanità, Rome, Italy). Additional strains not currently maintained in rodents at CFAP included the T. murrelli strain isolated in our laboratory from a naturally infected horse in 2012 [26] as well as T. murrelli (ISS 345) and T. nelsoni (ISS 29, ISS 37 and ISS 232) from ITRC. To evaluate the NGS method’s performance using field material, we selected a representative set of archived L1 samples that we previously isolated from various wildlife host species from Canada (Additional file  2: Table  S1). The original muscle samples collected from wildlife car- casses, primarily in western and northern Canada, were submitted by federal and provincial agencies or univer- sity researchers. Genotyping results generated by mPCR performed as described elsewhere [13] were available for many of these samples. If required and as available, remaining frozen muscle tissues of the source wildlife host were thawed and processed by the artificial digestion method [24] to obtain additional L1. We also assessed L1 isolated from six host species in Russia obtained from the ITRC repository (Additional file 2: Table S1). We focused on larval pools previously genotyped by mPCR as sin- gle or mixed infections with T. nativa since mPCR can- not differentiate T. nativa from potentially co-existing T. chanchalensis [2]. To prepare samples with defined larval numbers, L1 is first-stage larvae (plural) of selected pools were counted using a Leica M50 stereo microscope with a magnifica- tion of 10 or 16 × . Larvae were manually selected with a pipette from an aliquot in PBS in a petri dish and trans- ferred into microcentrifuge tubes. Tubes with single- larva preparations were examined under the microscope to verify the transfer. DNA extraction for the NGS library preparation Total DNA was extracted from L1 pools (range: 2–100 L1 in a pool) using the PureLink Genomic DNA Mini Kit (Thermo Fisher Scientific, Carlsbad, CA, USA) according to the manufacturer’s protocol for tissue samples. Briefly, PureLink Genomic Digestion Buffer was added to L1 suspended in a small volume of PBS to ~ 180 μl, followed by 20 μl of Proteinase K. The sample was incubated in a thermomixer for 3 h at 56 °C with shaking at 900 revolu- tions per minute. After the incubation, 20 μl of RNase A was added to the lysate, and the tube was incubated for 2 min at room temperature. After adding 200 μl of Pure- Link Genomic Lysis/Binding Buffer and 200  μl of  100% ethanol, DNA was purified via spin column and eluted with 50  μl of  PureLink Genomic Elution Buffer. A 180- μl aliquot of PBS used for the preparation of larval pools was processed with every batch of samples as a DNA extraction negative control. Purified DNA samples were stored at − 20 °C until use. Genotyping of Trichinella L1 by mPCR For a few selected wildlife-derived L1 pools that did not have previously determined mPCR genotyping results, five single larvae and a pool of ≤ 10 L1 were prepared per sample. DNA extraction using the DNA IQ System and Tissue and Hair Extraction Kits (Promega, Madison, WI, USA) and mPCR were performed per ICT recommenda- tions for genotyping Trichinella spp. [12]. Each PCR run included a negative DNA extraction control, no template control (i.e., nuclease-free water) and several positive controls extracted from L1 of selected Trichinella labora- tory strains. A modification of the published procedure entailed using SYBR Gold (Thermo Fisher Scientific) to increase the sensitivity of DNA band visualisation. After electrophoresis, agarose gels were incubated in a working dilution of SYBR Gold in 1 × Tris–borate-EDTA buffer for 1  h (rocked at room temperature) and visualized using the CemiDoc MP Imaging System (Bio-Rad). ITS‑1 fragment amplification and NGS library preparation Universal primers were designed with Clone Manager Professional 9.51 (Sci Ed Software) to amplify a variable fragment of ITS-1 of all known Trichinella taxa. The size of this fragment varies among reference sequences used in this study from 325 base pairs (bp) for T. chancha- lensis to 451  bp for T. pseudospiralis. Illumina adapter sequences were added to these primers using the approach described elsewhere [17]. The 100  pmol/μl stocks of four forward or reverse primers (Table 1) pro- duced by Integrated DNA Technologies were mixed in equal proportions before use. The ITS-1 fragment was amplified in a 25-μl reaction containing 5 μl of  5 × PrimeSTAR GXL buffer (Takara Bio, Kusatsu, Shiga, Japan), 2 μl of  2.5  mM dNTP mix (Takara Bio), 0.75 μl of each 10  pmol/μl forward and reverse primer mix, 0.5 μl of  PrimeSTAR GXL DNA Polymerase (Takara Bio), 13.5 μl of  nuclease-free water and 2.5 μl DNA template. The cycling protocol consisted of initial denaturation at 98 °C for 2 min followed by 30 Page 4 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 cycles of denaturation at 98  °C for 20  s, primer anneal- ing at 60 °C for 15 s and elongation at 68 °C for 30 s. The final extension was performed at 68  °C for 5  min. Each PCR run included a no template control (i.e., nuclease- free water) and DNA extraction negative control. After analysis of PCR results by agarose gel electrophoresis, amplicons were purified using AMPure XP magnetic beads (1 × ; Beckman Coulter, Brea, CA, USA) accord- ing to the manufacturer’s guidelines and DNA was eluted from beads with 22 μl of 0.1 × TE (1 × TE buffer pH 8 from Thermo Fisher Scientific diluted tenfold with nucle- ase-free water). After measuring the DNA concentration of each library using the Qubit 3.0 Fluorometer (Thermo Fisher Scientific) and Qubit 1 × dsDNA HS Assay Kit (Life Technologies, Eugene, OR, USA), purified PCR products were diluted with 0.1 × TE to 6.7 ng/μl. Indices and sequencing tags were then added by a limited-cycle PCR using 15 μl (~ 100  ng) of diluted PCR product or undiluted bead-purified reaction mixture for the DNA extraction negative control, 5 μl each of an i7 and i5 oli- gonucleotide from Nextera XT Index Kit v2 Set A (Illu- mina, San Diego, CA, USA) and 25 μl of 2 × NEBNext Ultra II Q5 Master Mix (New England Biolabs, Ipswich, MA, USA). The cycling protocol included initial dena- turation at 98  °C for 2  min followed by seven cycles of denaturation at 98 °C for 10 s, primer annealing at 55 °C for 30 s and elongation at 65 °C for 1 min and 15 s. The final extension was carried out at 65 °C for 5 min. Following the purification of amplicons using AMPure XP beads (1 ×), the DNA concentration of each library diluted 1:5 with 0.1 × TE was measured using the Qubit 3.0 Fluorometer as described above. The DNA fragment size distribution analysis was performed using the QIAx- cel Advanced System (Qiagen, Hilden, Germany) accord- ing to the manufacturer’s guide (NGS Sample Quality Control using the QIAxcel Advanced System, February 2018). The molar concentration of a library was calcu- lated using the following equation. Concentration, nM = Concentration, ng µL 660 g mol ×QIAxcel Peak Value × 106 The libraries were diluted to 4  nM with resuspension buffer (10  mM Tris–HCl pH 8.5, 0.1% v/v Tween 20), and 5 μl of each diluted library was pooled. Each prepa- ration of pooled libraries included at least one library prepared from DNA extraction negative control to rule out potential contamination of reagents. After alkaline denaturation, the preparation of pooled libraries was diluted to 8 pM and mixed (at a 3:1 ratio by volume) with denatured PhiX Control v3 (Illumina) diluted to the same concentration. This preparation was incubated at 96  °C for 2 min, followed by 5 min in an ice bath before load- ing into the reagent cartridge of a MiSeq Reagent Kit v2 500-cycles (Illumina). The MiSeq instrument was set to perform paired-end sequencing and output FASTQ files without post-run analysis. After each sequencing run, the instrument’s template line was washed with 0.01% (v/v) sodium hypochlorite to minimise sample carryover from previous runs. NGS data analysis workflow The quality of generated raw reads was assessed using FastQC 0.11.9 (https:// www. bioin forma tics. babra ham. ac. uk/ proje cts/ fastqc/). The sequencing data analysis was performed using Geneious 11.1.5 software (Bio- matters, Auckland, New Zealand). Paired reads were set for each library from FASTQ files containing demul- tiplexed forward and reverse reads. The following oper- ations were run as a standardised automated workflow. Illumina adapter and quality trimming and sorting were performed using the BBDuk plugin with minimum quality for ‘Trim Low Quality’ set to 30 and minimum length for ‘Discard Short Reads’ set to 200  bp. After merging paired reads using BBMerge with a merge rate set to ‘High’ and deselecting unmerged reads, quality- filtered merged reads were analysed using the Classify Sequences plugin with sensitivity set to ‘High Sensitiv- ity/Medium’. This plugin performs pairwise alignment of reads to a custom database of reference sequences. The database contained a single manually verified Table 1 Oligonucleotides used in this study Sequences complementary to the target region are underlined Primer name Primer sequence (5′–3′) ITS-1-F-Adp TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAG CTG CGG AAG GAT CAT TAT CGT ITS-1-F-Adp1N TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAGNCTG CGG AAG GAT CAT TAT CGT ITS-1-F-Adp2N TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAGNNCTG CGG AAG GAT CAT TAT CGT ITS-1-F-Adp3N TCG TCG GCA GCG TCA GAT GTG TAT AAG AGA CAGNNNCTG CGG AAG GAT CAT TAT CGT ITS-1-R-Adp GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACAG AAC CGT CAT GTT GCA CAA GTC ITS-1-R-Adp1N GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACAGNAAC CGT CAT GTT GCA CAA GTC ITS-1-R-Adp2N GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACAGNNAAC CGT CAT GTT GCA CAA GTC ITS-1-R-Adp3N GTC TCG TGG GCT CGG AGA TGT GTA TAA GAG ACAGNNNAAC CGT CAT GTT GCA CAA GTC https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ https://www.bioinformatics.babraham.ac.uk/projects/fastqc/ Page 5 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 consensus sequence of the ITS-1 fragment for each of the 13 Trichinella taxa (Additional file  1). The output summary provides information about the total number and percent of reads mapped to a reference at a speci- fied identity threshold. The minimum overlap identity to classify at the species level was 99% (default value). The minimum percent identity higher than next best result to classify was the default 0.2% unless otherwise stated. For genotyping L1 from wildlife, we applied an arbitrary cut-off represented by a minimum of 0.5% of reads mapped to a reference for assigning taxa in NGS data analysis. Using sequences found in standard databases, such as ‘Nucleotide collection’ and ‘Whole-genome shotgun con- tigs’, available on the National Center for Biotechnology Information (NCBI) website, we produced consensus sequences of the ITS-1 fragment for all Trichinella taxa except T. nelsoni because of a potential misassembly of reads in this region of the T. nelsoni whole-genome data set. To address this problem, we amplified ITS-1 from single-larva preparations of T. nelsoni strains ISS 29, ISS 37 and ISS 232. Products amplified from five such preparations per strain were purified using AMPure XP beads and subjected to Sanger sequencing at the National Research Council Canada (Saskatoon, Canada). For- ward and reverse sequencing reads were assembled into contigs using Clone Manager Professional 9.51, and a consensus sequence was generated after aligning these contigs with the Multiple Alignment using Fast Fourier Transform (MAFFT) plugin in Geneious 11.1.5. Quality-filtered merged paired reads of selected librar- ies were further analysed by mapping to the 13 reference sequences in the database using the BBMap plugin and calling variants using FreeBayes with ’Minimum Alter- nate Fraction’ set to 0.15 (Geneious 11.1.5). Statistical data analysis Statistical significance of the difference in the proportion of reads mapped to a reference from the actual propor- tion of this species in a pool was determined using the Wilcoxon matched-pairs signed rank test, with a p-value < 0.05 considered significant using Prism 6.07 software (GraphPad, La Jolla, CA, USA). The degree of agreement between mPCR and NGS on genotyping the L1 pools from wildlife for each identified Trichinella genotype was assessed using Cohen’s kappa (GraphPad QuickCalcs available at https:// www. graph pad. com/ quick calcs/; accessed on 2023–08-10). Kappa values were assigned the following strengths of agreement: < 0.00 no agree- ment, 0.00–0.20 slight, 0.21–0.40 fair, 0.41–0.60 moder- ate, 0.61–0.80 substantial and 0.81–1.00 almost perfect agreement [27]. Results Analysis of interspecific variation of the ITS‑1 reference sequences The phylogenetic tree constructed from consensus refer- ence sequences of the ITS-1 marker demonstrates that this fragment possesses sufficient variability for differ- entiating currently recognised Trichinella taxa (Fig.  1). The highest percent identity (99.14%; only three single nucleotide polymorphisms in this fragment) was between T. murrelli and T. britovi as well as T. murrelli and Trich- inella T9 (Additional file 3: Table S3). Performance of the NGS genotyping assay with preparations of mixed laboratory strains of Trichinella To evaluate the NGS method’s performance in identify- ing co-infecting genotypes, L1 of T. spiralis and T. nativa laboratory strains mixed at various ratios for a total of approximately 2000 pooled L1 were used for the library preparation. After sequencing, the mean number of paired reads per library was 991,506 (range: 828,602– 1,159,000). In the sequencing data analysis, the num- ber of reads mapped to a reference sequence correlated directly with the number of L1 of the respective species in the mix (Fig. 2a). For the libraries prepared from only one, two or five T. spiralis L1 in a pool, 0.065%, 0.08% and 0.68% of quality-filtered merged reads, respectively, were Fig. 1 Phylogenetic tree based on consensus sequences of the ITS-1 fragment of 13 Trichinella taxa from the custom database used in this study. The sequences were aligned using the MAFFT plugin in Geneious 11.1.5 with default settings. The neighbour-joining method was then applied to produce the tree using the Tamura-Nei model with a bootstrap resampling set at 1000. Bootstrap values are shown at the nodes. Branches of the non-encapsulated clade are depicted in blue https://www.graphpad.com/quickcalcs/ Page 6 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 mapped to the T. spiralis reference sequence. A notice- able sequence representation bias towards T. spiralis was illustrated by a higher proportion of reads mapped to the corresponding reference when mixed with an equal num- ber (1000 L1) of T. nativa in the pool. In the next experiment, libraries produced from a series of pools of 100 L1 consisting of different propor- tions of T. nativa and Trichinella T6 were sequenced. A lower number of L1 in a pool was used because com- paratively low numbers of L1 are typically isolated from wildlife samples. The mean number of paired reads gen- erated per library in this sequencing run was 908,614 (range: 820,348–999,492). There was again a positive cor- relation between the number of reads mapped to a refer- ence and the number of L1 of the same species in a pool (Fig.  2b). When only a single L1 of Trichinella T6 or T. nativa was included in a pool, 2.08% and 0.87% of reads were mapped to the respective reference sequences. The sequence representation in this NGS run was biased towards Trichinella T6. We also sequenced this set of libraries using the same version of the MiSeq Reagent kit containing a ’nano’ flow cell. The mean number of paired reads per library was 11-fold lower (82,410; Range: 78,064–90,028) than that generated using a ‘standard’ flow cell. However, the pro- portions of reads mapped to T. nativa and Trichinella T6 references were similar for each library between the runs generated by either flow cell type, with a difference not exceeding ± 0.8% (Additional file 4: Table S4). In these data sets, the background level represented by the pro- portion of reads mapped to a non-target reference did not exceed 0.03%. Assessment of the sequence representation bias in the NGS assay To further assess the sequence representation bias in the NGS genotyping assay, libraries were generated from six preparations containing 100 L1 each of T. spiralis, T. nativa, T. pseudospiralis, T. murrelli (from cougar) and Trichinella T6. Figure 3 demonstrates a significant devia- tion of the mean percent of reads mapped to a reference sequence from the actual proportion of the correspond- ing species in a pool for these Trichinella taxa except T. murrelli. Trichinella T6 was consistently the most over- represented genotype, whereas T. pseudospiralis was the most underrepresented. In preparations of one, two or five L1 of T. pseudospiralis mixed with approximately 2000 L1 of T. nativa, 0.035%, 0.175% and 0.5% of reads were mapped to the T. pseudospiralis reference sequence. Identification of available Trichinella spp. with the highest homology of the ITS‑1 fragment by the NGS assay Since homology between ITS-1 consensus sequences of T. britovi and T. murrelli in the custom database was comparatively high, which could reduce the resolution provided by this marker for differentiating these taxa, triplicate 500 L1 sub-samples of larval pools of avail- able laboratory strains of these species (except for the horse-derived T. murrelli strain where only 100 L1 per sub-sample were used) were assayed by NGS. For the three T. murrelli strains, the mean proportion of reads mapped to the T. murrelli reference with standard devia- tion was 96.9 ± 2.5%. The proportion of reads assigned to non-target taxa was within background levels (i.e., < 0.03%). In contrast, although 96.5 ± 0.17% of reads for Fig. 2 Analysis by the NGS method of larval preparations of two different Trichinella taxa mixed in varying proportions. Columns depict the percent of reads mapped to corresponding reference sequences for (a) pools of approximately 2000 L1 consisting of different proportions of T. spiralis (T1) and T. nativa (T2) and (b) pools of 100 L1 of T. nativa (T2) and Trichinella T6 mixed in the numbers indicated Page 7 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 the single available T. britovi strain were mapped to the corresponding reference sequence, a significant propor- tion of these reads (3.35 ± 0.16%) also mapped to the T. murrelli reference. However, forty single-larva prepara- tions of the same T. britovi L1 pool genotyped by mPCR produced a band pattern consistent only with T. britovi (not shown), indicating contamination of this labora- tory strain with T. murrelli was unlikely. To eliminate any cross-talk in classifying reads, sequencing data for T. britovi were re-analysed with the default value of ’mini- mum percent identity higher than next best result to classify’ (overlap identity range for considering reference sequences to be equally suitable matches to the query) increased to 0.4%. As a result, 94.41 ± 0.19% of reads were mapped to the T. britovi reference, while the number of reads assigned to T. murrelli was reduced to the back- ground level. The number of reads unclassified because of conflicting taxonomy increased; however, the values remained comparatively low at 5.56 ± 0.19%. Comparing the performance of NGS assay to mPCR using archived L1 samples from 17 different species of wild carnivores Genotyping results generated by both assays for L1 samples from 107 individual animals are summarised in Table  2. Two L1 samples isolated from a cougar and a wolverine did not amplify in mPCR, but NGS revealed co-infections with two taxa in both cases (Additional file  2: Table  S1). All Trichinella genotypes identified by mPCR were also identified by the NGS method in 103 (96.3%) samples. Complete agreement between the two genotyping assays was observed in 92 (86%) of the 107 samples. Partial agreement was observed in 11 (10.3%) samples for which additional Trichinella taxa were iden- tified by NGS and four (3.7%) samples for which addi- tional taxa were identified by mPCR. Co-infections with multiple (two or three) taxa were revealed in 16 (14.9%) and 24 (22.4%) of the 107 animals by mPCR and NGS, respectively. The kappa coefficient values indicated almost perfect agreement between mPCR and NGS for five identified Trichinella taxa, substantial agreement for T. spiralis and no agreement for T. chanchalensis (Addi- tional file  5: Table  S5). The mean proportion of unclas- sified reads with standard deviation for this data set was 4.17 ± 2.1%. The numbers of mapped reads for DNA extraction negative control libraries included in every NGS run were consistently within background levels. We sought to clarify discrepancies between results obtained with mPCR and NGS if additional isolated L1 or muscle tissues were still available. For example, for the L1 sample derived from a wolf (Canis lupus) in the Euro- pean part of Russia (ISS 7613) where co-infection with T. nativa, T. britovi and T. spiralis was identified by mPCR performed at ITRC, we found only T. nativa and T. brit- ovi by both NGS and mPCR in our laboratory. Similarly, where T. spiralis and T. nativa had been identified from ISS 7607 (a stray dog from Chukotka Autonomous Dis- trict, Russia) by mPCR performed at ITRC, we identified only T. nativa by NGS and mPCR in our laboratory. We also observed a discrepancy between quantitative assess- ments of T. nativa and T. britovi proportions in the ISS 7613 L1 pool for the two methods. By mPCR performed in our laboratory, 16 of 22 (72.7%) single-larva prepara- tions were identified as T. britovi and the remaining six (27.3%) as T. nativa. In contrast, in NGS data analyses for libraries prepared from 100 L1 of this pool or pooled equal DNA aliquots from the 22 single-larva prepara- tions, markedly more reads were assigned to T. nativa (82.11% and 65.17%) than T. britovi (14.5% and 34.47%), implying preferential amplification of the ITS-1 fragment of T. nativa. Detecting T. chanchalensis in two wild mustelids in Canada by NGS Although most isolates from Canadian wildlife com- prised single or mixed infections of T. nativa and Trichinella T6 (Table  3), T. chanchalensis (84.1% of quality-filtered merged reads) was identified by the NGS method in co-infection with Trichinella T6 (2.5%) in a wolverine from the Northwest Territories (NT, Canada) (Additional file  2: Table  S1). DNA extracted from L1 of Fig. 3 Assessment of the sequence representation bias in the NGS method. Two and four preparations of a pool containing 100 L1 of each of five laboratory strains, T. spiralis (T1), T. nativa (T2), T. pseudospiralis (T4), T. murrelli (T5) and Trichinella T6, were analysed by the NGS method in two separate runs. Individual values representing the percent of reads mapped to a reference sequence are depicted as a scatter plot with median represented by a solid line and range depicted by bars. The shown p-values are exact values. Asterisks indicate statistical significance of the difference in the determined proportion of reads mapped to a reference from the actual proportion (i.e., 20%) of this genotype in a pool Page 8 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 this pool did not amplify in mPCR. Furthermore, T. chanchalensis (5.2% of reads) was identified in co-infec- tion with T. nativa (15.4%) and Trichinella T6 (70.9%) in an American marten from NT. In contrast, only T. nativa was identified in this sample by mPCR. We also mapped quality-sorted merged reads of these two librar- ies to reference sequences in the database using the BBMap plugin, which showed 100% pairwise identity of generated consensus sequences with the T. chanchalensis reference. However, variant calling using FreeBayes has elucidated markedly different profiles of lower-frequency ITS-1 variants in T. chanchalensis L1 isolated from wol- verine and American marten (Table 4). Discussion In this study, we developed and evaluated the perfor- mance of a new genotyping assay for Trichinella using amplicon-based NGS. Significant advantages of this method over other published genotyping assays are (i) the potential for differentiating all currently recognised Trichinella taxa without the need for ancillary assays, (ii) enhanced resolution for identifying underrepresented species in a mixed infection and (iii) a higher through- put by removing the need for single-larva preparations and increased multiplexing capability. We demonstrate that this genotyping assay enables accurate qualitative assessment of Trichinella taxa composition in a sample. With the cut-off selected for assigning taxa, the NGS method could reliably identify an underrepresented genotype at up to a 1:400 ratio in a larval pool. The new method also demonstrated a quantitative potential for establishing relative abundancies of different Trich- inella taxa in preparations of mixed laboratory strains. However, quantitative estimates generated by this NGS method for L1 from wildlife hosts should be interpreted in light of preferential amplification of genotypes with the least compromised L1. Using a representative set of L1 samples isolated from various wildlife host species, NGS performed at least as well as mPCR, which has been the customary method for Trichinella genotyping for over two decades [13]. All Trichinella taxa revealed by mPCR were also identified by the NGS method in 96.3% (103/107) of these samples, demonstrating high concordance between the two assays. In the remaining four L1 samples, the original mPCR assay identified an additional genotype. This discrepancy could be attributed to the prolonged storage of the frozen samples before testing by the NGS method. NGS outper- formed mPCR by detecting additional taxa in 11 sam- ples, including identifying T. chanchalensis along with T. nativa and Trichinella T6 in a larval pool isolated from an American marten from NT, Canada. Unfortunately, Table 2 Comparison of Trichinella genotyping results generated using mPCR and NGS for L1 samples from wildlife and other host species * L1 isolate(s) from Russia § Includes one L1 isolate from Russia Host species Number of animals Complete agreement Extra taxa identified by NGS mPCR Badger (Taxidea taxus) 3 3 Black Bear (Ursus americanus) 2 2 Brown Bear (Ursus arctos)* 2 2 Cat (Felis catus; stray)* 1 1 Cougar (Puma concolor cougar) 25 23 2 Coyote (Canis latrans) 10 10 Dog (Canis lupus familiaris; stray)* 1 1 Fisher (Pekania pennanti) 8 6 2 Grizzly Bear (Ursus arctos horribilis) 1 1 Himalayan Black Bear (Ursus thibetanus laniger)* 1 1 Lynx (Lynx canadensis) 1 1 Marten (Martes americana) 1 1 Raccoon (Procyon lotor) 1 1 Raccoon Dog (Nyctereutes procyonoides)* 2 2 Red Fox (Vulpes vulpes) 19 18 1 Wolf (Canis lupus)§ 20 17 3 Wolverine (Gulo gulo) 9 5 4 Total 107 92 (86%) 11 (10.3%) 4 (3.7%) Page 9 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 Ta bl e 3 Tr ic hi ne lla ta xa id en tifi ed b y N G S in th e 10 7 L1 p oo ls fr om w ild lif e an d ot he r h os t s pe ci es * T . b rit ov i Ba dg er Bl ac k Be ar Br ow n Be ar Ca t Co ug ar Co yo te D og Fi sh er G riz zl y Be ar H im al ay an Bl ac k Be ar Ly nx M ar te n Ra cc oo n Ra cc oo n D og Re d Fo x W ol f W ol ve rin e To ta l n o. 3 2 2 1 25 10 1 8 1 1 1 1 1 2 19 20 9 T2 1 1 1 12 10 1 3 1 1 1 18 11 5 T5 1 T6 3 1 9 3 T1 /T 2 1 T1 /T 2/ T4 1 T2 /T 3* 1 T2 /T 6 3 2 1 1 1 8 4 T2 /T 6/ T1 3 1 Page 10 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 no remaining L1 or muscle tissue were available from this animal to perform confirmatory genotyping on addi- tional single-larva preparations using ancillary restriction fragment length polymorphism analysis of an amplified cytochrome b gene fragment, capable of differentiat- ing these three taxa [2]. This finding represents the first record of T. chanchalensis infection in a host species other than wolverine. Revealing three Trichinella geno- types in the L1 pool from a marten in our study is con- gruent with a record of co-infection with T. britovi, T. nativa and T. spiralis detected in a pine marten (Martes martes) from Lithuania [28]. In a previous wildlife sur- vey conducted in our laboratory, the prevalence of Trich- inella spp. in 101 American martens from Nunavut and British Columbia was 3% [11]. Regardless of this reported low prevalence, our data support including marten and other mustelids in future surveys on geographic and host ranges of T. chanchalensis. The success rate of PCR genotyping on preparations containing damaged or partially disintegrated larvae can be significantly reduced [11, 15, 29]. Therefore, L1 of co- infecting Trichinella taxa having similar integrity is a crucial prerequisite to accurately quantitating their rela- tive abundances by amplicon-based NGS. For example, relative abundances of individual constituents of intesti- nal parasitic nematode communities in cattle and bison were accurately assessed by amplicon-based NGS using third-stage larvae hatched from excreted eggs via copr- oculture [17, 18]. However, the larval integrity of each co-infecting Trichinella spp. can vary considerably, espe- cially in sequential natural infections that are well sepa- rated in time or for taxa that are variably adapted to the host species. Trichinella L1 survive in hosts for varying periods with lifespan depending on many factors related to the parasite and the host [30]. Data on the length of larval survival of sylvatic Trichinella spp. in live hosts are limited. However, the available evidence supports a range of adaptability of a given Trichinella genotype to different host species and different survival rates of distinct geno- types of these parasitic nematodes in a specific host [31, 32]. For example, larvae of T. britovi and T. pseudospira- lis established in experimentally infected pigs remained infective for a limited time and displayed different sur- vival rates [5]. Handling of samples collected for Trichinella testing can introduce additional quantification bias. Samples of muscle tissues from wildlife are often frozen before Trichinella L1 isolation by artificial digestion. Isolated L1 are also often stored frozen for various periods before further analysis. Freeze damage to L1 can occur, render- ing them poorly amplifiable or non-amplifiable by PCR [29]. Larvae of freeze-resistant Trichinella spp. are more likely to preserve their integrity after isolation from pre- viously frozen muscle tissues by artificial digestion. This could explain, at least in part, the observed discrepancy between quantitative assessments of proportions of highly freeze-resistant T. nativa and less freeze-resistant T. britovi in the ISS 7613 L1 pool obtained using mPCR and NGS in this study as well as our lack of detection of T. spiralis in samples previously genotyped by mPCR at ITRC (ISS 7607 and ISS 7613). Despite these limitations to accurate results posed by compromised larvae, it is recommended that sample selection should also include such larvae to best ensure NGS identifies all taxa present. The NGS method also demonstrated sequence rep- resentation biases in experiments with well-preserved Trichinella laboratory strains mixed at known propor- tions. Different steps of the NGS genotyping workflow can contribute to this phenomenon, where marker ampli- fication, sequencing and NGS data analysis are the most susceptible stages. One of the few studies that assessed and quantified the effects of such biases demonstrated variation of amplified marker fragment length as a pri- mary contributor to the distortion of relative abundance estimates [33]. In that study, shorter fragments of an artificial marker region were overrepresented compared to longer ones, whereas no significant effect of marker sequence composition on the relative proportion esti- mates was observed. In addition, this bias was more pro- nounced on Illumina MiSeq than on two PacBio models. Table 4 Differences in sequence variations of NGS reads mapped to the Trichinella chanchalensis reference for the L1 pools from wolverine and American marten * Vastly different depths of coverage were achieved due to not only different numbers of quality-filtered merged reads mapped to the T. chanchalensis reference between the two host species but also different numbers of total reads generated with the use of MiSeq Reagent kits with ’standard’ and ’nano’ flow cell AO, number of alternate observations; SNP, single nucleotide polymorphism Host species Variation type Nucleotide position Change AO Depth* Marten Indel 201—202 CA—> Deletion 184 1226 SNP 160 A—> G 187 1226 SNP 46 G—> C 187 1226 Wolverine SNP 289 T—> A 21,741 120,382 Page 11 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 Such preferential amplification of shorter sequences was likely a cause of the T. pseudospiralis underrepresenta- tion observed in this study, as the ITS-1 marker fragment of this species is the longest among the taxa used. Align- ment of the ITS-1 fragment sequences of 13 Trichinella taxa from our custom database (not shown) demon- strated complete homology in binding sites for univer- sal primers used in this study, except a single nucleotide substitution in the reverse primer binding site of the T. pseudospiralis ITS-1 fragment located closer to the 5’ end of the oligonucleotide sequence. This substitution could also contribute to the observed underrepresentation of T. pseudospiralis. Also, loci of rDNA are considered to be amongst the most unstable genomic regions, given their repetitive nature and high transcriptional activity [34]. Although the variation of rDNA copy numbers among Trichinella spp. has not been sufficiently studied, it was shown that such copy numbers estimated using whole genome shotgun data varied substantially within and across several other nematode taxa [35]. This phenome- non would further contribute to sequence representation biases in DNA metabarcoding, limiting its quantitative reliability. The accuracy of taxa delineation by DNA metabar- coding largely depends on the taxonomic resolution provided by selected markers [36]. We chose a variable fragment of ITS-1 because it displayed sufficient inter- specific sequence variation for reliable differentiation of even the sibling taxa T. nativa and Trichinella T6, North America’s most commonly observed genotypes in wildlife [11]. However, ITS-1 reference sequences of T. britovi, T. murrelli and Trichinella T9 were 99.1% identical, potentially reducing the resolution provided by this marker for differentiating these taxa. Further- more, there is evidence of T. britovi ITS-1 alleles with even higher homology to T. murrelli. The search of the NCBI database using the T. murrelli reference sequence as a query generated several hits represented by T. britovi isolates from different wildlife hosts in Israel (e.g., KU374884, KU374875) [37] with 99.4% identity of this fragment. Although T. britovi, T. murrelli and Trichinella T9 are geographically well separated [1, 38], reliable differentiation of these taxa would still be desir- able. In the sequence analysis of the T. britovi labora- tory strain performed in this study, a low but significant proportion of generated reads was initially assigned to T. murrelli, implying this laboratory strain possesses lower-frequency ITS-1 alleles with higher homology to T. murrelli than to the T. britovi reference. Although this could be reduced to negligible levels by increasing the overlap identity range value at the sequence classi- fication step of the data analysis workflow, future incor- poration of an additional marker region with higher sequence variation between these Trichinella spp. might better facilitate their reliable differentiation by the NGS approach. The efficacy of a marker in delineating species bounda- ries also depends on the existence of a clear-cut differ- ence between inter- and intraspecific variability [39]. The data generated in this study demonstrated high intraspe- cific conservation of the ITS-1 marker among T. nativa and Trichinella T6 isolates from Canadian wildlife. This was substantiated by the following observation. The Classify Sequences plugin in the data analysis workflow assigns quality-filtered reads with minimum overlap identity for references in the database lower than the set threshold into the unclassified reads category. In this study, the proportions of such unclassified reads for all L1 samples, including those isolated from wildlife, were comparatively low, with over 90% of merged reads con- sistently mapping to one or more reference sequences at the 99% identity threshold, even with only a single refer- ence ITS-1 sequence of each taxon in the database. For L1 pools with known composition, such as prepa- rations of mixed laboratory strains of Trichinella, the ratio of reads mapped to an ITS-1 reference of a non-tar- get genotype was consistently very low (≤ 0.03%). Poten- tial sources of such background in DNA metabarcoding using the Illumina platform include assigning incorrect reads to samples during demultiplexing because of cross- talk caused by misread bases within index sequences and sample carryover from the previous sequencing runs per- formed on the same instrument [40]. The ability to sequence large numbers of pooled librar- ies simultaneously or sample multiplexing can offset oth- erwise comparatively high costs of NGS. Although NGS costs continue to decline, processing low library num- bers might still be considered impractical. However, we demonstrated in this study that an adequate sequencing depth could be achieved using the MiSeq Reagent Kit v2 with a ’nano’ flow cell, representing a cost-efficient choice when small to moderate sample sizes must be processed. The high coverage depth providing sufficient resolution for determining marker allele composition and frequency is an added value of amplicon NGS, which was previously utilized in genotyping multi-clonal malaria infections [41]. We demonstrated differences in lower abundance ITS-1 variants (within 15–20% of total quality-filtered merged reads) between T. chanchalensis isolates from wolverine and American marten. However, this finding should be interpreted cautiously, as distinguishing true haplotypes from sequencing errors may require a more robust approach, including sequencing samples in dupli- cate [41]. In future studies, we will continue evaluating this feature of the NGS method with more isolates of T. chanchalensis and other Trichinella taxa. Page 12 of 13Lobanov et al. Parasites & Vectors (2023) 16:466 Conclusions We developed and evaluated a method based on deep sequencing of a variable ITS-1 fragment of Trichinella spp. on the Illumina platform. The method enabled accu- rate determination of Trichinella taxa composition in larval pools isolated from various host species. We dem- onstrated excellent overall agreement between the NGS assay and mPCR on genotyping a representative num- ber of L1 isolated from various wildlife hosts. However, the NGS method demonstrated enhanced resolution for detecting underrepresented genotypes in larval pools, including the novel species T. chanchalensis not identifi- able by mPCR. The performance of the NGS method was demonstrated in this study using strains and isolates of eight of the 13 known Trichinella taxa, focusing on those known or most likely to be present in North America, the location of our reference laboratory. However, analysis of sequence data available in GenBank for the other remain- ing taxa, T. zimbabwensis, T. papuae, T. patagoniensis and Trichinella T8 and T9, suggests that the ITS-1 prim- ers will also amplify the marker fragment of these taxa enabling their differentiation by the NGS method. Abbreviations Bp Base pairs ITS-1 Internal transcribed spacer 1 L1 First-stage larvae NGS Next-generation sequencing PCR Polymerase chain reaction mPCR Multiplex PCR spp Species (plural) Supplementary Information The online version contains supplementary material available at https:// doi. org/ 10. 1186/ s13071- 023- 06035-1. Additional file 1. Reference sequences of the ITS-1 marker fragment of Trichinella spp. Additional file 2: Table S1. Comparison of genotyping results generated by mPCR and NGS for selected larval pools isolated from wildlife. Additional file 3: Table S3. ITS-1 fragment identity matrix. Additional file 4: Table S4. Comparison of NGS genotyping results gen- erated using two different types of flow cell. Additional file 5: Table S5. Trichinella genotype-specific agreement between mPCR and NGS for the 107 L1 samples from wildlife. Acknowledgements We appreciate the excellent technical assistance that Yunxiu Dai, Jenna Oakley and Robyn Ostrander (CFAP) provided for this study. We thank Dr. Irina M. Odoevskaya (All-Russian Research Institute of Experimental Veterinary Medicine named after K.I. Skriabin and Y.R. Kovalenko, Moscow, Russia) for providing samples of Trichinella L1 isolated from various host species in Russia and Dr. Maria Angeles Gomez Morales (Instituto Superiore di Sanita, Rome, Italy) for providing L1 samples from the ITRC repository. We are grateful to Helen Schwantje, Cait Nelson, Maeve Winchester (British Columbia Ministry of Forests, Lands and Natural Resource Operations), Audrey Simon (Faculty of Veterinary Medicine, University of Montreal), Pierre Canac-Marquis, Michel Larouche (Fur Institute of Canada), Nic Larter, Brett Elkin (Environment and Natural Resources, Government of Northwest Territories), Kathleen Brown (Canadian Wildlife Health Cooperative-Quebec), Josephine Kush (CFIA, Leth- bridge Laboratory), Michael Pawlik (British Columbia Ministry of Agriculture) and Muhammad Morshed (British Columbia Center for Disease Control, Public Health Laboratory) for providing muscle samples of Canadian wildlife from which L1 pools used in this study were originally isolated. We thank Dr. Sarah Parker (Centre for Applied Epidemiology, Western College of Veterinary Medicine, University of Saskatchewan) for guidance on the statistical analysis. The authors are also grateful to Laura Lalonde and Dr. Camila Queiroz (CFAP) for their critical review of the manuscript and thoughtful suggestions for improvement. This work was funded by the Canadian Food Inspection Agency (internal projects N-000159 and N-000353). Author contributions VL: conceptualisation, methodology, investigation, formal analysis, validation, visualisation, project administration, funding acquisition, writing–original draft. KK: investigation, formal analysis, data curation, writing–review & editing. WBS: resources, project administration, writing–review & editing, EJ: resources, writing–review & editing. All authors have read and approved the final manuscript. Availability of data and materials The raw NGS data generated in this study were deposited at NCBI under BioProject PRJNA911791. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. 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Identification of Trichinella taxa by ITS-1 amplicon next-generation sequencing with an improved resolution for detecting underrepresented genotypes in mixed natural infections Abstract Background Methods Results Conclusions Background Methods Parasite material DNA extraction for the NGS library preparation Genotyping of Trichinella L1 by mPCR ITS-1 fragment amplification and NGS library preparation NGS data analysis workflow Statistical data analysis Results Analysis of interspecific variation of the ITS-1 reference sequences Performance of the NGS genotyping assay with preparations of mixed laboratory strains of Trichinella Assessment of the sequence representation bias in the NGS assay Identification of available Trichinella spp. with the highest homology of the ITS-1 fragment by the NGS assay Comparing the performance of NGS assay to mPCR using archived L1 samples from 17 different species of wild carnivores Detecting T. chanchalensis in two wild mustelids in Canada by NGS Discussion Conclusions Anchor 24 Acknowledgements References