18S rDNA next-generation sequencing uncovers the biodiversity of Gastrointestinal parasites in Tibetan grazing ruminants in China

Abstract

Background

Free-range yak, Tibetan sheep and Tibetan goat, predominantly distributed across the Qinghai-Tibetan Plateau (QTP) in China, are highly susceptible to a wide range of parasite infections, resulting in underestimated economic losses. We aimed to investigate the biodiversity of gastrointestinal parasites in local ruminants based on 18 S SSU ribosomal DNA gene (18 S rDNA) using next-generation sequencing.

Methods

Following DNA extraction from 79 fecal samples collected from yak, Tibetan sheep and goat in the southeast part of QTP, we proceeded to amplify the V3-V4 fragments of the18S rDNA gene. Subsequently, we assessed the diversity of parasitic protozoa and helminths. To identify parasitic infection patterns, correlation studies were conducted in different factors, including ages, health conditions and seasons.

Results

A total of 192 operational taxonomic units (OTU) were identified, including 10 phyla and 27 genera. High prevalence was observed in Entamoeba (93.67%), Blastocystis (75.95%) and Trichostrongylus (68.35%). By phylogenetic analysis, we identified a potential new Entmoeba species, along with zoonotic species/subtypes, such as Trichostrongylus colubriformis and Blastocystis ST10, ST12, and ST14. Two rarely reported zoonotic protozoa, Colpoda and Colpodella, were particularly noted for their high prevalence of infection and potential association with diarrhea. Juveniles and adults shared the similar species of parasites. A significant reduction in helminth diversity and infection prevalence was documented during autumn.

Conclusions

This study provides critical insights into the diversity of gastrointestinal parasites in QTP ruminants, thereby enhancing our understanding of the infection risk in grazing livestock.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-025-04887-6.

Background

The Qinghai-Tibetan Plateau (QTP), situated in northwestern China, stands as the largest and highest plateau in the world, with an average elevation exceeding 4,000 m. Renowned as the “Roof of the World” or the “Third Pole” [1, 2], this region supports diverse free-ranging livestock, including yak (Bos grunniens), Tibetan sheep (Ovis aries), cattle (Bos taurus domestica), goats (Capra hircus), camels (Camelus bactrianus), donkeys (Equus asinus), and horses (Equus caballus) [3, 4]. Among these, yak and Tibetan sheep/goat are indigenous to the QTP and serve as primary daily needs for locals, providing essential resources such as meat, fuel (yak dung) and wool, significantly contributing in the local economy [5]. The southeastern QTP encompasses two autonomous prefectures, Aba and Ganzi, both characterized a distinctive Tibetan plateau climate. This climate feature prolonged winters, low humidity and altitudes ranging from 2,000 to 5,000 m where humans and livestock coexist.

Ruminant are highly susceptible to gastrointestinal (GI) parasites, including protozoa, nematodes and flukes. These parasites pose a significant risk of intestinal dysfunctions, causing impaired nutrient absorption, digestion disorder, stunted growth, reduced feed efficiency, diarrhea, anemia, and even death in severe cases [6–8]. Protozoan infections, particularly Cryptosporidium, Eimeria, and Giardia, are frequently relevant to diarrhea outbreaks [9, 10]. In addition, parasitic infections reduce the fertility and productivity of animals, degrade the quality of meat and milk, and increase zoonotic transmission risks to humans.

QTP ruminants are possibly infected through ingestion of contaminated water and grass containing parasite eggs while grazing. Once infected, untreated animals persistently excrete parasite eggs, facilitating cross-infection within free-range herds. Gastrointestinal parasite infections are endemic in grazing livestock of QTP, with a survey revealing an 80.3% overall prevalence of nematode infections in 2023 [11]. Specifically, prevalence reached 75.9% in yak, 86.0% in Tibetan sheep, and 98.9% in Tibetan goat, respectively. Furthermore, a prevalence of up to 57.7% of trematode infections was reported in ruminants in Qinghai [12]. Moreover, yak and Tibetan sheep were found previously to be infected with diverse nematodes such as Trichostrongylus, Teladorsagia, Oesophagostomum. Of particular public health concern are zoonotic including Cryptosporidium, Enterocytozoon, and Giardia in QTP ruminants [4].

Traditional diagnosis of parasites has relied on microscopy. However, morphological identification of parasites and their eggs/oocysts requires the professional expertise of individuals, which is not only time-consuming but also lack of accuracy. In contrast, next-generation sequencing (NGS) based on SSU rDNA genes has considered as a novel and effective tool for analyzing the population of eukaryotic microorganism, including parasites. For instance, a study comparing microscopy, sanger sequencing, and metagenomic approaches demonstrated that 18 S rDNA metagenomics significantly outperformed other methods in detecting helminth species diversity in wild rodents [13]. Additionally, further epidemiological investigations, control, and treatments can be carried out in a more effective and targeted manner [14–16].

Parasite diversity significantly influences ecological dynamics, evolutionary processes, and epidemiological patterns. However, limited studies have reported the biodiversity of gastrointestinal parasites in QTP ruminants in China. In this study, we aimed to investigate the species diversity of gastrointestinal parasitic protists and nematodes in local ruminants using next-generation sequencing of 18 S SSU ribosomal DNA gene. The finding provides a foundational framework for further studies into epidemiology and ecology of parasites.

Methods

Ethics and consent to participate

All protocols were approved by the Ethics Committee of Southwest Minzu University in accordance with the recommendation of the Animal Care and Use Program Guidelines of Sichuan Province, China (No.SMU-202501117). We obtained the farmer’s consent, including the use of animals, fecal collection, and acquisition of relevant sample information.

Samples

A total of 79 fresh fecal samples were collected from yak and Tibetan sheep/goat from 12 free-range farms in Aba Tibetan and Qiang Autonomous Prefecture (specifically from Ruoergai and Hongyuan counties) and Ganzi Tibetan Autonomous Prefecture, including Daocheng, Ganzi, Xiangcheng, Litang, Derong and Shiqu counties (Fig. 1A, B and C). Six to nine samples were randomly collected from each farm. In particular, 45 samples were from yak and 34 samples were from Tibetan sheep/goat. For yak, fresh feces were immediately collected into sterile 50 mL conical tubes after observed defecation during grazing monitoring, with only the superficial layer retained to minimize environmental contamination. For small ruminants, a soft bag was gently attached to the anus for hours to collect fresh fecal samples. All samples were documented with information, including the location, host age, health status and collection. The season during which each fecal sample was tacked was classified as spring (February through April), summer (May through July), and autumn (August through October). The samples were flash-frozen in dry ice during field transport and then stored at -20 ℃ in the lab. Map material was sourced from DataV.GeoAtlas (https://datav.aliyun.com).

Fig. 1.

Geographical location of samples. Colors represent sampling counties, and stars represent the exact sampling location. Maps are downloaded at the https://datav.aliyun.com. (A) Sampling sites in northwest Sichuan, southeast of QTP, China. (B) Sampling sites in Aba Tibetan and Qiang autonomous prefecture and Ganzi Tibetan Autonomous Prefecture

DNA extraction

Prior to DNA isolation, the samples were pretreated by employing a method from Han et al. [14] with minor modifications. Briefly, each sample was centrifuged at 5,000 rpm for 10 min in a high-speed centrifuge, and the supernatant was discarded. The final precipitate was then used for DNA isolation. Genomic DNA was extracted using EasyPure^® Stool Genomic DNA kit (TransGen Biotech, Beijing, China) according to the manufacturer’s instructions.

PCR and illumina PE300 sequencing

DNA (50 ng) was sent to Shanghai Majorbio Bio-pharm Technology Co.,Ltd (Shanghai, China) for sequencing. The 18 S ribosomal DNA gene fragments in the V3-V4 variable regions were amplified using primers (F: CCAGCASCYGCGGTAATTCC and R: ACTTTCGTTCTTGATYRA) with barcodes [17]. The PCR mixture comprised 10 µL 2 × Pro Taq, 0.8 µL forward primer (5 µM), 0.8 µL reverse primer (5 µM), 10 ng/µL template DNA, and ddH₂O to 20 µL. The PCR cycling conditions were as follows: 95 °C for 3 min, 35 cycles of 95 °C for 30 s for denaturation, 55 °C for 30 s for annealing, and 72 °C for 45 s for extension, and a final elongation at 72 °C for 10 min. The PCR products were visualized via 2% agarose gel electrophoresis and recovered using the AxyPrepDNA Gel Recovery Kit (AXYGEN Inc., Silicon Valley, US). PCR products were quantified by QuantiFluor™ -ST Blue Fluorescence Quantification System (Promega, Madison, USA). Finally, the PCR products were mixed in the appropriate proportions to meet the sequencing volume required for each sample.

Purified amplicons were pooled in equimolar amounts and paired-end sequenced on an Illumina PE300 platform (Illumina, San Diego, USA), following standard protocols provided by Shanghai Majorbio Bio-Pharm Technology Co. Ltd. (Shanghai, China). The raw sequencing reads were deposited in the NCBI Nucleotide Sequence database (NT) (BioProject: PRJNA1207782, web link: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1207782/). The datasets generated and/or analysed during the current study are available in the NCBI GenBank repository (Accession numbers: SAMN46143987-SAMN46144065).

Data processing

Raw FASTQ files were de-multiplexed using an in-house perl script, then quality-filtered by fastp version 0.19.6 (https://github.com/OpenGene/fastp) [18] and merged by FLASH version 1.2.11 (http://www.cbcb.umd.edu/software/flash) [19]. The optimized sequences were clustered into operational taxonomic units (OTU) using USEARCH11-uparse (http://drive5.com/uparse/) with 97% sequence similarity level. The most abundant sequence for each OTU was selected as a representative sequence. The number of 18 S rDNA gene sequences from each sample were rarefied to 20,000, which still yielded an average Good’s coverage of 99.09%.

The taxonomy of each OTU representative sequence was analyzed by RDP Classifier version 2.11 (http://rdp.cme.msu.edu/) [20] against the 18 S rDNA gene database (nt_v20210917) using confidence threshold of 0.7.

OTU screening and sequence analysis

The original OTU were screened based on genus, leaving only parasitic protozoa and helminths, from which species were screened on OTU_Taxon_Origin to obtain a new post-taxon leveling OTU data for subsequent analyses. The analyses of subsequent diversity were based on screened OTU data.

Bioinformatic analysis was carried out using a cloud platform (https://cloud.majorbio.com). rarefaction curves and alpha diversity indices including observed OTUs, Chao1 richness, Shannon index and Good’s coverage were calculated with Mothur v1.30.1 (http://www.mothur.org/wiki/Calculators) based on the OTUs [21]. Rank-Abundance curve, Venn diagrams and Circos diagrams, which are used to characterize the specific species, composition of communities and relative abundance contained in the samples, are produced using R language tools. The similarity among the parasite communities in different samples was determined by principal coordinate analysis (PCoA) based on Bray-curtis dissimilarity using Vegan v2.5-3 package. Sample hierarchical clustering analysis was performed using Qiime to calculate the beta diversity distance matrix, and then the dendrograms were plotted using R language. The linear discriminant analysis (LDA) effect size (LEfSe) [22] (http://huttenhower.sph.harvard.edu/LEfSe) was performed to identify the significantly abundant taxa (genus to genus) of parasites among the different groups (LDA score > 3.5, P < 0.05).

The OTU identified as Entamoeba spp. and Blastocystis spp. were individually selected for further analysis. Phylogenetic trees for these OTU were constructed using Neighbor-joining (NJ) method in MEGA 11, with Bootstraps values calculated based on 1,000 replicates.

Statistical analysis

Statistical analyses were performed using IBM SPSS Statistics 27.0.1 (SPSS Inc., Chicago, IL, USA) software. The mean abundance of each genus was calculated as the ratio of total sequence counts per genus to the number of samples testing positive for that genus. The Chi-square test was used to access differences in terms of species, ages, health condition, and seasons. Differences were considered statistically significant at P < 0.05.

Results

Parasite biodiversity

In current study, the 18 S rDNA V3-V4 fragment was successfully amplified. After filtering, the sequencing data yielded 1,531,471 valid tags (average length: 369 bp). By OTU screening of parasitic protozoa and helminths, a total of 192 OTU was identified in all samples, spanning 10 phyla, 13 classes, 16 orders, 26 families, and 27 genera. Genus-level rank-abundance showed that the samples RH1, HD4 and HD6 from yak exhibited the highest species diversity of 12 distinct genera, whereas sample SL_L2 exhibited minimal diversity in a Tibetan sheep, containing only two genera (Fig.S1).

In this study, 13 protozoan and 14 helminth genera were identified with a prevalence was 98.73% (Table 1). The dominant genera were Entamoeba (93.67%), Blastocystis (75.95%), Trichostrongylus (68.35%), Colpoda (50.63%), Colpodella (49.37%). The hierarchical clustering tree indicated limited parasite community conservation between yak and Tibetan sheep/goat (Fig. 2). Entamoeba was the predominant genus across all samples, demonstrating both the highest prevalence and mean abundance, followed by Trichostrongylus. Additionally, Simplicimonas also exhibited significant abundance levels.

Table 1.

Mean abundance, prevalence, and identified species of each parasite genus

	Phylum	Genus	Mean abundance*	Prevalence (%)/positive samples (n)	Species
Protozoon	Ciliophora	Colpoda	167	50.63 (40)	C. elliotti, C. steini, Colpoda spp.
		Buxtonella	333	20.25 (16)	B. sulcata
		Dasytricha	12	6.33 (5)	D. ruminantium
	Parabasalia	Simplicimonas	7028	41.77 (33)	S. similis
		Tetratrichomonas	879	35.44 (28)	T. sp. _MA3, T. buttreyi, T. sp. _BUVK, T. sp._ZUBR
		Hypotrichomonas	342	15.19 (12)	H. acosta, H. imitans, H. sanderai
	Apicomplexa	Eimeria	162	24.05 (19)	E. hirci, E. vermiformis, Eimeria spp.
	Evosea	Entamoeba	8440	93.67 (74)	CS-2010, RL2, RL3, RL4, RL8, E. cf._bovis, E. bovis, E. polecki, E. suis, Entamoeba spp.
	Fornicata	Enteromonas	1266	18.99 (15)	E. hominis
	Microsporidia	Enterocytozoon	3	1.27 (1)	E. bieneusi
	Discosea	Acanthamoeba	50	46.84(37)	A. genotype_T2/6C, A. sp._Nl2, A. castellanii, A. sp._Sar45, A. sp._CJY/S2, A. sp._Tib128, Acanthamoeba spp.
	Unclassified	Blastocystis	2054	75.95 (60)	ST10, ST12, ST14, ST21, ST22, ST24, ST26, ST30, Blastocystis spp.
		Colpodella	183	49.37 (39)	C. sp._RRJ-2016, C. sp._HLJ, C. tetrahymenae, Colpodella spp.
Helminths	Nematoda	Trichostrongylus	6238	68.35 (54)	T. colubriformis
		Cylicocyclus	374	41.77 (33)	C. insigne
		Oesophagostomum	3199	39.24 (31)	O. muntiacum
		Parelaphostrongylus	900	26.58 (21)	P. tenuis
		Mammomonogamus	90	26.58 (21)	M. sp._3_BC-2018,
		Chabaudstrongylus	284	20.25 (16)	C. ninhae
		Haemonchus	5	3.80 (3)	H. contortus
		Trichuris	55	3.80 (3)	T. leporis
		Toxocara	61	2.53 (2)	T. vitulorum
		Dictyocaulus	179	2.53 (2)	D. viviparus, D. filaria
		Capillaria	2	2.53 (2)	C. bursata
		Aonchotheca	33	1.27 (1)	A. musimon
		Strongyloides	4	1.27 (1)	S. papillosus
	Platyhelminthes	Paramphistomum	1770	3.80 (3)	P. cervi

*Mean abundance = total abundance of each genus / the number of positive samples

Fig. 2.

The Hierarchical clustering tree at the genus level. The length of branches represents the distance between samples. Red branches represent yak samples and green branches represent samples of Tibetan sheep/goats. The colored blocks represent mean abundance of different species at the genus level; Relative abundance < 0.01 categorized as others

In yak, 21 distinct genera were identified, consisting of 12 protozoa and 9 helminths, with the prevalence of 100% and 80.00%, respectively (Table 2). Entamoeba was the dominant species with the prevalence of 100% followed by Blastocystis at 77.78% (Table S1). Tibetan sheep and goat harbored 23 genera, consisting of 11 protozoa and 12 helminths, with the prevalence of 88.24% and 67.65%, respectively (Table 2). Hereinto, Entamoeba and Blastocystis remained predominant with the percentage of 85.29% and 73.53%, respectively (Table S1). Notably, the prevalence of protozoa in yak were significantly higher than in Tibetan sheep and goat (χ² = 5.64, df = 1, P < 0.05) (Table 2).

Table 2.

Number and prevalence of protozoa and helminths categorized by hosts, health conditions, ages and seasons

Categories	Protozoon genus (n)	Protozoon Prevalence (%)	Chi-square, p value	Helminth genus (n)	Helminth Prevalence (%)	Chi-square, p value
Host
Yak	12	100 (45/45) *	χ2 = 5.64, df = 1, P < 0.05	9	80.00 (36/45)
Tibetan sheep/goat	11	88.24 (30/34) *		12	67.65 (23/34)
Health condition
Health	13	92.86 (52/56)		13	69.64 (39/56)
Diarrhea	12	100 (14/14)		7	78.57 (11/14)
Age
Adult	12	94.44 (51/54)		13	77.78 (42/54) *	χ2 = 4.66, df = 1, P < 0.05
Juvenile	12	93.75 (15/16)		9	50.00 (8/16) *
Season
Spring	12	100 (27/27)		9	88.89 (24/27) ***	χ2 = 15, df = 1, P < 0.001
Summer	11	88.24 (30/34)		12	82.35 (28/34) ***	χ2 = 12.5, df = 1, P < 0.001
Autumn	12	100 (18/18)		6	33.33 (6/18)

^*P < 0.05, ^**P < 0.01, ^***P < 0.001; both spring and summer are compared to autumn

In healthy group, a total of 26 genera were identified, consisting of 13 protozoa and 13 helminths with the prevalence of 92.86% and 69.64%, respectively (Table 2). Among these, Entamoeba was the dominant (91.07%) followed by Blastocystis (80.36%) (Table S1). In contrast, diarrhea animals demonstrated reduced genus diversity with 19 total genera, consisting of 12 protozoa and 7 helminths. In particular, the prevalence of protozoa and helminths were 100% and 78.57%, respectively (Table 2). Here, Entamoeba was the dominant with 100% positive, followed by Colpodella at 92.86% prevalence (Table S1). However, comparative statistical analysis revealed no significant difference of prevalence between healthy and diarrhea animals (Table 2).

Adults harbored 25 genera, consisting of 12 protozoa and 13 helminths, with the prevalence of 94.44% and 77.78%, respectively (Table 2). Juvenile showed reduced diversity with 21 genera, consisting of 12 protozoa and 9 helminths, with the prevalence of 93.75% and 50.00%, respectively (Table 2). Hereinto, both adults and juveniles shared common protozoan parasites, with Entamoeba and Blastocystis being the most predominant (Table S1). Adults had significantly more infections of helminths than juveniles (χ² = 4.66, df = 1, P < 0.05) (Table 2).

Due to the difficulties of sampling and transportation, no sample was collected in winter unfortunately. Therefore, further analysis was done across the three seasons. In spring, 21 genera were identified in animals, consisting of 12 protozoa and 9 helminths, with the prevalence of 100% and 88.89%, respectively (Table 2). In summer, 23 genera were identified, consisting of 11 protozoa and 12 helminths, with the prevalence of 88.24% and 82.35%, respectively (Table 2). In autumn, 18 genera were identified, consisting of 12 protozoa and 6 helminths, with the prevalence of 100% and 33.33%, respectively (Table 2). Statistical analysis showed highly significant differences between spring and autumn (χ² = 15, df = 1, P < 0.001), as well as summer and autumn (χ² = 12.5, df = 1, P < 0.001) (Table 2). Entamoeba, Blastocystis, and Trichostrongylus were prevalent in spring and summer whereas the present of Trichostrongylus was significantly low in autumn (Table S1).

Parasite community differences between Yak and Tibetan sheep/goat

Rarefaction curves for both Sobs and Shannon diversity tended to flat, indicating adequate sequencing data, depth, and sample size (Fig.S2). Alpha diversity analysis revealed significantly great taxonomic abundance (P < 0.01) and species diversity in yak compared to Tibetan sheep/goat at the OTU level (Fig. 3A). PCoA analysis demonstrated a distinct discrepancy between two hosts (P = 0.001) at the genus level (Fig. 3B). Host-specific genera analysis identified five genera exclusive to yak and six unique to small ruminants. Notably, Enteromonas (66.58%) was the most abundant yak-specific genus, whereas Parelaphostrongylus was predominant in Tibetan sheep/goat with the percentage of 99.68% abundance (Table 3).

Fig. 3.

Comparation of gastrointestinal parasites biodiversity between yak and Tibetan sheep/goat. (A) Statistical differences of mean abundance between yak and Tibetan sheep/goat were evaluated using Wilcoxon rank-sum test, based on Sobs and Shannon index at the OTU level; ^NSP > 0.05, ^*P < 0.05, ^**P < 0.01, ^***P < 0.001. (B) The principal component analysis (PCoA) based on genus level, with circles presented as confidence ellipses. (C) The Circos plots revealed the distribution proportion of high abundance genera. Relative abundance < 0.01 categorized as others

Table 3.

Common and unique genera categorized by hosts, health conditions, ages and seasons

	Categories	Common genera (n)	Unique genera (n)	Unique genera (percentage of abundance)
Host	Yak	17	4	Enteromonas (66.58%), Paramphistomum (18.62%), Hypotrichomonas (14.37%), Toxocara (0.43%),
	Tibetan sheep/goat	17	6	Parelaphostrongylus (99.68%), Aonchotheca (0.17%), Haemonchus (0.08%), Strongyloides (0.02%), Capillaria (0.02%), Enterocytozoon (0.02%)
Health condition	Health	18	8	Parelaphostrongylus (97%), Dictyocaulus (1.84%), Trichuris (0.85%), Aonchotheca (0.17%), Haemonchus (0.08%), Strongyloides (0.02%), Capillaria (0.02%), Enterocytozoon (0.02%)
	Diarrhea	18	1	Toxocara (100%)
Age	Adult	19	6	Hypotrichomonas (90.81%), Dictyocaulus (7.93%), Aonchotheca (0.73%), Haemonchus (0.35%), Capillaria (0.09%), Strongyloides (0.09%)
	Juvenile	19	2	Toxocara (96.05%), Enterocytozoon (3.95%)
Season	Spring	16	3	Dictyocaulus (98.09%), Strongyloides (1.09%), Enterocytozoon (0.82%)
	Summer	16	4	Toxocara (69.71%), Aonchotheca (18.86%), Haemonchus (9.14%), Capillaria (2.29%)
	Autumn	16	1	Dasytricha (100%)

The number of common and unique genera and the percentage of abundance were analyzed based on Venn diagram

Comparative analysis revealed distinct host-specific abundance patterns among dominant genera. Entamoeba was more abundant in yak (54%) than in Tibetan sheep/goat (46%) (Fig. 3C). Trichostrongylus exhibited striking host preference, constituting 80% in small ruminants versus merely 20% in yak.

Parasite community differences between healthy and diarrheic ruminants

In this study, nine samples with unknown healthy status were included only in PCoA analysis due to incomplete sampling information. Alpha diversity analysis showed no significant variation between healthy and diarrhea animals at the OTU level (Fig. 4A), whereas a highly significant difference was observed at the genus level (P=0.01) (Fig. 4B). Nine health-associated genera were identified, dominated by Parelaphostrongylus (97%), while only Toxocara was exclusively found in diarrheic samples (Table 3).

Fig. 4.

Analysis of similarities and differences between healthy and diarrheic animals. (A) Statistical differences of mean abundance between healthy and diarrheic animals were evaluated using Wilcoxon rank-sum test, based on Sobs and Shannon index at the OTU level; ^NSP > 0.05, ^*P < 0.05, ^**P < 0.01, ^***P < 0.001. (B) The principal component analysis (PCoA) based on genus level, with circles presented as confidence ellipses. (C) The Circos plots revealed the distribution proportion of high abundance genera. Relative abundance < 0.01 categorized as others. (D) Linear discriminant analysis effect size (LEfSe) identifies characteristic species with significantly different abundances within groups. Only species with LDA thresholds > 3 are shown; larger LDA scores indicate greater influence on differential effects

Comparative abundance profiling highlighted elevated levels of Simplicimonas and Oesophagostomum in diarrheic animals relative to healthy animals (Fig. 4C). By the analysis of LDA thresholds, Trichostrongylus, Parelaphostrongylus, and Paramphistomum were highly enriched in healthy samples, whereas Oesophagostomum, Acanthamoeba, Colpoda, Colpodella, Buxtonella, Toxocara were enriched in diarrheic samples (Fig. 4D).

Age-associated differences in parasite communities

Nine samples with unknown age information were included only in PCoA analysis. There was no significant difference of mean abundance between juveniles and adults in OTU level (P > 0.05), although both Sobs and Shannon index showed adults were slightly higher than juveniles (Fig. 5A). PCoA analysis revealed no significant difference among all age groups (Fig. 5B). Two juveniles-specific genera were identified, with Toxocara predominating at 96.05% abundance. Adults contained seven unique genera, predominating by Hypotrichomonas at 90.81% abundance (Table 3). The Circos plots revealed that both adults and juveniles shared similar parasite profiles, with Entamoeba as the dominant genus (Fig. 5C).

Fig. 5.

Analysis of similarities and differences between juveniles and adults. (A) Statistical differences of mean abundance between juveniles and adults were evaluated using Wilcoxon rank-sum test, based on Sobs and Shannon index at the OTU level; ^NSP > 0.05, ^*P < 0.05, ^**P < 0.01, ^***P < 0.001. (B) The principal component analysis (PCoA) based on genus level, with circles presented as confidence ellipses. (C) The Circos plots revealed the distribution proportion of high abundance genera. Relative abundance < 0.01 categorized as others

The difference of parasite communities in seasons

The Kruskal-Wallis H test was employed to analyze differences among three seasons based on Sobs and Shannon index. Sobs index revealed significant difference between spring-summer and summer-autumn (P < 0.01), whereas all season groups showed significantly different by Shannon index (P < 0.05) (Fig. 6A). PCoA analysis further confirmed significant intergroup differences among the three seasons (P = 0.001) (Fig. 6B).

Fig. 6.

Analysis of similarities and differences among seasons. (A) Statistical differences of mean abundance among seasons were evaluated using Wilcoxon rank-sum test, based on Sobs and Shannon index at the OTU level; ^NSP > 0.05, ^*P < 0.05, ^**P < 0.01, ^***. P < 0.001. (B) The principal component analysis (PCoA) based on genus level, with circles presented as confidence ellipses. (C) The Circos plots revealed the distribution proportion of high abundance genera. Relative abundance < 0.01 categorized as others

Four unique genera were identified in both spring and summer, contrasting with only one unique genus in autumn. Specifically, Dictyocaulus was the most abundant in spring, Toxocara characterized in summer, while Dasytricha emerged as autumn exclusive genus (Table 3). Entamoeba demonstrated a seasonal abundance gradient of peaking in spring, declining through autumn, and reaching minimal in summer. Trichostrongylus followed a parabolic trend with spring initiation, summer zenith, and autumn collapse. In contrast, Simplicimonas was predominantly found in autumn (Fig. 6C).

Sequence alignment and phylogenetic analysis of Entamoeba spp. and Blastocystis spp.

The species of Entamoeba identified via Nucleotide Sequence Database (NT) library alignment were CS-2010, RL3, RL4, E. cf._bovis, E. bovis, E. polecki, E. suis, and Entamoeba spp. Further blasting in NCBI GenBank. Analysis of Entamoeba spp. revealed two novel species: RL2 and RL8. OTU 2358 shared the highest homology with a pathogenic Entamoeba bangladeshi strain 8111 (90.61% with 78% coverage, GenBank: KR025411.1). OTU 2274 shared the highest identity with E. suis L01015_Esuis_97 (94.29% with 59% coverage, GenBank: MK801441.1). OTU 2023 shared the highest homology with Entamoeba sp. voucher K0818005-IV (94.83% with 100% coverage, GenBank: OM900059.1). OTU 2327 shared the highest homology with a pathogenic E. moshkovskii EM_IND/42 (92.08% with 57% coverage, Genbank: ON965424.1). OTU 2143 shared the highest homology with E. moshkovskii MV2-MAbr (92.16% with 75% coverage, GenBank: MN536494.1). Phylogenetic analysis revealed that OTU2358, OTU2327, OTU2143, and OTU2274 did not cluster with known Entamoeba species, while OTU2023 grouped with Entamoeba sp. voucher K0818005-IV, suggesting the discovery of potential new Entamoeba subtypes (Fig. 7).

Fig. 7.

Phylogenetic tree of five OTU of Entamoeba spp. based on 18 S rDNA gene sequences. Nucleotide sequences were aligned with the Clustal W algorithm and phylogenetic analysis was performed using the Neighbor-Joining (NJ) method. The GenBank accession numbers follow the taxon names. Bootstrapping with 1,000 replicates was used to support the clades. Bar: 0.20 substitutions per site. The black filled circles represent 5 identified OTU

The subtypes ST10, ST12, ST14, ST21, ST22, ST24, ST26, ST30 of Blastocystis, and Blastocystis spp. were identified according to the 18 S rDNA gene database (nt_v20210917). The Blastocystis spp. were blasted on NCBI GenBank that two additional subtypes, ST24 and ST26, were identified with 99.72% and 100% homology, respectively.

Discussion

In this study, we employed NGS to investigate the biodiversity of parasitic protozoa and helminths in fecal samples from free-ranging livestock on the QTP of China. We focused on the 18 S rDNA gene, a common genetic marker containing both well-conserved and variable regions (V1-V9), is widely used for eukaryotic identification and diversity analysis [13, 23]. Although NGS has been applied to study eukaryotic population in water (e.g., sewage) and soil [24, 25], few studies have explored parasite diversity in feces [26].

Recent studies have highlighted the popularity of the highly variable V4 and V9 regions of 18 S rDNA for diversity analysis [15]. Furthermore, the V4 region has showed better accuracy of taxon identification than V9 region [17, 24, 27]. In this study, we analyzed the biodiversity of gastrointestinal parasites in yak and Tibetan sheep/goat by sequencing the V3-V4 regions of 18 S rDNA using Illumina. Most importantly, 18 S rDNA-based NGS has been proved superior to traditional methods for studying parasites in free-ranging livestock, which generally carry heavier parasite loads than captive livestock [28, 29]. In this study, 192 OTU were defined at a 97% sequence similarity threshold. Thirteen genera of protozoa and fourteen helminths were identified at the genus level. The highest mean relative abundance and prevalence were recorded for three genera: Entamoeba, Blastocystis and Trichostrongylus.

In the analysis of 18 S rDNA sequences, Entamoeba emerged as the predominant protozoan genus. The most of identified Entamoeba were of bovine-derived, with Entamoeba bovis previously established as the primary species in yak from Qinghai province [30]. However, Entamoeba sp. CS-2010, originally isolated from Capreolus capreolus [31] presented the highest abundance in this study. Entamoeba sp. RL2 and RL8 were distinguished through BLAST analysis, showing < 95% sequence homology and no clustering with known species, suggesting potential novel subtypes [32]. Consistent with previous studies, high abundance of Entamoeba was observed in healthy animals compared to diarrheic animals [33, 34]. While its pathogenicity remains controversial, Entamoeba histolytica was considered as pathogenic and mainly reported in humans [29, 35], was absent in this study but found in Iraq cattle [36]. Entamoeba polecki, infecting both human and animals, was found for the first time in Tibetan ruminants. E. polecki is generally considered non-pathogenic but may worsen disease when co-infected with bacteria [37]. Therefore, these findings highlight the need to evaluate QTP ruminants as potential reservoirs for Entamoeba transmission between animal and human.

The prevalence of Blastocystis infection on the QTP had previously been reported as low [38–40], however, a high percentage of 75.95% was observed in the present study. NGS has high sensitivity in detecting low-abundance subtypes [16]. The identified subtypes included ST10, ST12, ST14, ST21, ST22, ST24, ST26, ST30 and Blastocystis spp. ST10 was the dominant subtype, aligning with previous reports in China [38, 41, 42]. Thereinto, ST10, ST12, and ST14 are classified as zoonotic [35]. Despite the pathogenicity of Blastocystis remains controversial, its high prevalence has been consistently documented in healthy ruminants [33, 34, 43].

Trichostrongylus, a highly prevalent and pathogenic gastrointestinal nematode, mainly infects small ruminants. Severe clinical manifestations including enteritis, weight loss, and metabolic disruptions (e.g., altered short-chain fatty acids and reduced bone density) have been well-documented in infected hosts [33, 34]. Trichostrongylus colubriformis, a zoonotic parasite [44], was identified with high prevalence and abundance in this study. This contrasts with epidemiological patterns reported from other regions of QTP in China, where T. colubriformis has rarely been found in ruminants. For instance, a comprehensive survey of gastrointestinal nematode infections on the Tibetan Plateau reported only 0.8% prevalence of T. colubriformis in Tibetan sheep [11].

Significant differences in parasite diversity were observed between host species, with yak demonstrating markedly higher species diversity compared to Tibetan sheep/goat (P<0.05). Five unique genera were identified in yak, while six unique genera were detected in Tibetan sheep/goat, potentially attributed to host-specific species. PCoA analysis revealed significant differences between two host groups. Parelaphostrongylus tenuis (known as brain worm), has been reported in ungulate animals. Small ruminants are recognized as accidental hosts, typically becoming infected through incidental consumption of intermediate hosts (terrestrial gastropods) during grazing [45]. In this study, Parelaphostrongylus was found exclusively in Tibetan sheep/goat, with an infection percentage of 61.76%, despite its occurrence remains uncommon in cattle [46].

No significant age-related differences in parasite diversity were observed, with Entamoeba being identified as the dominant genus in both adults and juveniles. This likely attributed to shared living environments, uniform dietary practices, and fecal-oral transmission routes.

Three health-related genera and six diarrhea-related genera were identified through Circos and LEfse analysis. In particular, two Strongylida and one Paramphistomum were strongly correlated with healthy animals. In this study, only T. colubriformis was identified in the genera of Trichostrongylus. Interestingly, it was linked to healthy ruminants whereas it has been historically associated to diarrheal outbreaks in grazing sheep [47]. In the study, T. colubriformis showed the highest mean abundance in all samples. While no diarrhea was observed in sheep experimentally infected with 2,500 larvae/day over 12 weeks [48], significant feed intake reductions were documented post infection. Therefore, T. colubriformis may be a neglected economic threat through growth impairment in livestock, while Tibetan ruminants could serve as reservoir hosts for zoonotic transmission to locals. On the contrary, Oesophagostomum muntiacum (a Strongylida nematode) was identified as diarrhea-related parasite, showing 39.24% prevalence in this study.

Two unusual protozoan parasites associated with diarrheal infections were identified as noteworthy: Colpoda (phylum Ciliophora) and Colpodella (phylum Apicomplexa). Previously classified as free-living organisms, both genera have recently been implicated pathogenic in human and animal [49–53]. Interestingly, most of studies suggested Colpodella is transmitted via blood, however, our finding revealed exceptionally high abundance (the highest is 3089) and prevalence (49.37%) of Colpodella especially in diarrheic fecal samples. Our findings suggested a potential novel transmission route for Colpodella, a recently recognized tick-borne parasite. Colpodella has been unexpectedly found in the stools of dogs and cats in a recent study [54]. These findings may indicate an alternative fecal-oral transmission route of Colpodella. Colpodella has also been found in biting flies, and even in urine [50]. Unfortunately, its host-parasite interaction and transmission mechanism remain poorly understood that warrants further investigation.

Seasons analysis revealed similar taxonomic patterns dominated throughout the year, though significantly reduced diversity of OTU was observed during summer based on Sobs and Shannon index. In particular, helminth infection was decreased distinctly to 33.33% in autumn, potentially influenced by suboptimal environmental conditions, as average temperature in southeastern QTP ranging from 3 °C to 17 °C during autumn, hindering the infectivity of helminth egg. Additionally, Trichostrongylus dominanted in summer but declined in autumn, possibly linked to the diapause habitat of nematodes. In this study, Entamoeba was the dominant genus in spring and autumn, contrasting with Ren et al. [30], who reported peak Entamoeba infection during summer coinciding with E. histolytica transmission risks [55]. This discrepancy may be attributed to regional variations in climate, altitude, or sample size.

Conclusion

This study amplified the V3-V4 region of 18 S rDNA using next-generation sequencing, aiming to analyze the biodiversity of gastrointestinal parasites in ruminants from southeastern QTP, China. Following sequence screening, 192 OTU was identified, encompassing 13 protozoan and 14 helminth genera. Entamoeba, Blastocystis and Trichostrongylus were the most common genera based on both mean relevant abundance and prevalence. Simplicimonas and Oesophagostomum showed elevated abundance in diarrheic hosts, while rare genera, Colpoda and Colpodella, exhibited significantly high prevalence in diarrhea hosts. The diversity and abundance of helminths declined significantly in the autumn compared to both spring and summer. This study offers preliminary insights into the diversity of gastrointestinal parasites in, highlighting infection risks in grazing ruminants in the QTP yak and Tibetan sheep/goat. The implemented NGS approach demonstrates efficacy for regional parasite surveillance. Future efforts targeting phylum-specific genetic markers are recommended to optimize detection sensitivity and taxonomic resolution.

Electronic supplementary material

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Author contributions

Siran Wu: Writing– original draft, Investigation, Formal analysis, Methodology, Validation, Data curation. Ying Zhong: Methodology, Investigation, Validation. Haitao Li: Resources, Investigation, Formal analysis. Chen Tang: Resources, Investigation, Supervision. Bin Zhang: Writing– review & editing, Resources, Investigation. Runhui Zhang: Writing– review & editing, Conceptualization, Visualization, Methodology, Investigation, Validation, Supervision, Project Administration.

Funding

This research was financially supported by Sichuan Science and Technology Program (2024NSFSC1275), the Program Sichuan Veterinary Medicine and Drug Innovation Group of China Agricultural Research System under Grant (SCCXTD-2025-18) and Southwest Minzu University Double World-Class Project (XM2023014).

Data availability

The data supporting this study is provided within the article, including the accession numbers of representative sequences submitted in the GenBank database (BioProject: PRJNA1207782, Accession numbers: SAMN46143987-SAMN46144065, web link: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA1207782/).

Declarations

Ethics approval and consent to participate

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Not applicable.

Competing interests

The authors declare no competing interests.