https://orcid.org/0000-0002-1291-6783
Figures
Abstract
Soil-transmitted helminths, such as roundworms (Ascaris lumbricoides), whipworms (Trichuris trichiura) and hookworms (Necator americanus and Ancylostoma spp.), are gastrointestinal parasites that occur predominantly in low- to middle-income countries worldwide and disproportionally impact children. Depending on the STH species, health status of the host and infection intensity, direct impacts of these parasites include malnutrition, anaemia, diarrhoea and physical and cognitive stunting. The indirect consequences of these infections are less well understood. Specifically, gastrointestinal infections may exert acute or chronic impacts on the natural gut microfauna, leading to increased risk of post-infectious gastrointestinal disorders, and reduced gut and overall health through immunomodulating mechanisms. To date a small number of preliminary studies have assessed the impact of helminths on the gut microbiome, but these studies are conflicting. Here, we assessed STH burden in 273 pre-school and school-aged children in Tha Song Yang district, Tak province, Thailand receiving annual oral mebendazole treatment. Ascaris lumbricoides (107/273) and Trichuris trichiura (100/273) were the most prevalent species and often occurred as co-infections (66/273). Ancylostoma ceylanicum was detected in a small number of children as well (n = 3). All of these infections were of low intensity (<4,999 or 999 eggs per gram for Ascaris and Trichuris respectively). Using this information, we characterised the baseline gut microbiome profile and investigated acute STH-induced alterations, comparing infected with uninfected children at the time of sampling. We found no difference between these groups in bacterial alpha-diversity, but did observe differences in beta-diversity and specific differentially abundant OTUs, including increased Akkermansia muciniphila and Bacteroides coprophilus, and reduced Bifidobacterium adolescentis, each of which have been previously implicated in STH-associated changes in the gut microfauna.
Author summary
Soil-transmitted helminth infections exhibit a significant negative impact on population health worldwide. In particular in endemic regions sub-groups such as children suffer disproportionally from infection due to impoverished living conditions. Yet many of these regions have no or limited availability of infection prevalence data to inform intervention strategies. Application of low sensitivity diagnostic tools such as microscopy exacerbate this issue. Moving towards molecular tools is key in order to establish a more accurate and complete epidemiological profile that can serve as a reference standard for future studies. Recently, a number of studies investigated the microbiota as an important factor determining overall patient health. The gut microbiota can be altered through medication, lifestyle factors and co-inhabitation of the same environmental niche with STHs. However, these microbiota studies often lack a characterised baseline. The current study provides baseline epidemiology data for a cohort of pre-school and school-age Thai children using a molecular diagnostic technique. We estimate the STH infection prevalence and intensity and characterise the host gut microbiota profile at a single cross-sectional timepoint comparing infected with uninfected children. This data can serve as a starting point for future studies investigating the impact of environmental factors and parasitic infections on patient health.
Citation: Stracke K, Adisakwattana P, Phuanukoonnon S, Yoonuan T, Poodeepiyasawat A, Dekumyoy P, et al. (2021) Field evaluation of the gut microbiome composition of pre-school and school-aged children in Tha Song Yang, Thailand, following oral MDA for STH infections. PLoS Negl Trop Dis 15(7): e0009597. https://doi.org/10.1371/journal.pntd.0009597
Editor: Keke C. Fairfax, University of Utah, UNITED STATES
Received: March 16, 2021; Accepted: June 25, 2021; Published: July 26, 2021
Copyright: © 2021 Stracke et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All sequencing data files are available from the NCBI Sequence Read Archive under BioProject number PRJNA606654 (accession numbers SRR11085945 to SRR11086629, SRR11086522 to SRR11086470 and SRR11086467 to SRR11085968) All other relevant data are within the manuscript and its Supporting Information files.
Funding: This work, including the efforts of ARJ, was funded by a NHMRC Career Development Fellowship (APP1126395). KS, RJT and ARJ are supported by the Victorian State Government Operational Infrastructure Support (https://www.vic.gov.au/) and Australian Government National Health and Medical Research Council Independent Research Institute Infrastructure Support Scheme (https://www.nhmrc.gov.au/). HK was supported by a NHMRC Career Development Fellowship (APP1064772). KS was supported by a Melbourne Research Scholarship and the Riady Scholarship through the University of Melbourne (https://www.unimelb.edu.au/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Soil-transmitted helminths (STHs), namely roundworms (Ascaris spp.), whipworms (Trichuris trichiura) and hookworms (Ancylostoma spp. and Necator americanus), are among the most common parasitic causes of neglected tropical disease worldwide [1]. These helminthiases disproportionately affect children, in whom they cause a global estimated burden of 1.2 million disability adjusted life years (DALYs) [2]. Depending on the infective species, infection intensity and host nutritional and immunological status, symptoms include malnutrition, diarrhea, abdominal pain and anaemia, which may lead to stunting, wasting and impaired physical or cognitive development [3]. In school-aged children specifically, STH infections have been shown to cause cognitive and educational deficits [4].
Since 2012, in response to the UN Millennium Development Goals, there has been a concerted global effort to reduce STH burden in children through annual or biannual treatment with benzimidazoles treating >75% of at-risk, school-aged children in endemic regions [5]. These programs have reduced the intensity of infection and disease-related morbidity [6]. However, quantifying the magnitude of this change and its sustainability is limited by the availability of methods with adequate sensitivity to diagnose infection under conditions of low worm burden and low population prevalence [7]. As endemicity rates fall, there is a need to move from diagnostic tools such as the Kato-Katz thick smear (KKTS) method toward molecular-based methods such as quantitative PCR [8,9].
In addition to the direct consequences of infection, gastrointestinal pathogens may alter the host gut microbiome [10], and impact on bacterial diversity and abundance [11–13], brain function [14–16], digestive health [17,18], immune function [19–21], and development [17,18]. Although this impact is well studied for viral, bacterial and protistal causes of diarrhoeal disease, the effects of STH infections on the gut microbiome are not well characterised and appear complex [10]. Several studies indicate that STH increases bacterial diversity and richness [11–13]. But not all STH studies support these findings [22], and their potential pathology has not been determined [16]. One study found that gut microbiome composition was predictive of an STH infection [23]. However, ascribing cause and effect from this finding is not simple, as gut microbial composition may influence susceptibility to STH infection [24]. Additional studies of microbiome composition in helminth infections are needed. One challenge faced by such studies in highly endemic populations is that there is no data to differentiate acute from chronic effects of these parasites on gut microfauna, and little to indicate if uninfected individuals at the time of study have been affected by prior helminth infection or represent an appropriate ‘healthy control’ for microbiome characterisation.
Here, we undertook a cross-sectional study of STH infection and faecal microbiome composition in a population of pre-school and school-aged children in a remote community in Tha Song Yang district, Tak province, Thailand. Although Thailand has comparatively low national STH prevalence, the country has many rural and refugee communities, in which low-intensity infections remain highly endemic despite on-going oral MDA programs [25,26].
Methods
Ethics statement
Oral informed consent was received from all parents or legal guardians for participants under the age of 18 years. Ethics approval, including approval of oral informed consent, was provided by Mahidol University (FTM ECF-019-05) as well as by the Human Research Ethics Committee of the Walter and Eliza Hall Institute of Medical Research (HREC Project #16/10).
Study area, faecal sample collection and processing
A total of 273 faecal samples from 2- to 6-year-old pre-school and school-aged children were collected from the 28th to 30th of March 2017 among eleven day-care centres in the Mae Song subdistrict, Tha Song Yang district, Tak province, Thailand. In addition, the local field team recorded epidemiological information for each child, such as age, sex, school, date of birth, height and weight. An overview of the entire process can be found within the supporting information files (S1 Fig). Stool collection kits consisting of a faecal collection container, disposable gloves, a zip-locked bag and study information sheet were distributed to each child’s caregiver. Within 24 hours of distribution caregivers were requested to return a double-contained stool sample (30 mL max volume). For each child a de-identified participant ID, the date and time of stool collection and processing were recorded. Stool samples were returned within an average of 12 hours and 1 gram of sample was immediately examined for STH infections by direct duplicate Kato Katz thick smear performed by two independent microscopists. The remainder of each stool sample was transferred to the laboratory field site in Mae Sot district, Tak province, Thailand within 24 hours on wet ice. There, stools were pre-processed for international transport according to their classification using the Bristol Stool Chart [27]. Type 5–7 stools were centrifuged at 14,000 x g for 5 minutes, the supernatant discarded and part of the pellet stored in DESS at room temperature (1:1 sample to preservative ratio; 20% dimethyl sulfoxide, 0.25 M ethylenediaminetetraacetic acid, saturated sodium chloride) [28]. Type 1–4 stools were stored directly in DESS without the requirement for an additional centrifugation step. Preserved stools were transported to the main laboratory located at the Department of Helminthology, Faculty of Tropical Medicine, Mahidol University (Bangkok, Thailand) within 72 hours on wet ice, where they were split into two 1–1.5 gram aliquots in 2 mL universal Nunc tubes and stored at 4°C. Cold stored DESS preserved stools were shipped to the Walter and Eliza Hall Institute of Medical Research on cold packs. Upon arrival, stool samples were long-term stored at -20°C.
DNA extraction
Stool samples were thawed at RT, homogenized using a sterile wooden spatula and DESS preservative removed by resuspending each sample twice in 50 mL sterile water, centrifuging at 2,000 x g for 3 minutes and decanting the supernatant. Up to 150 mg of the faecal pellet was used for DNA extraction using the Bioline ISOLATE Fecal DNA Extraction kit according to the manufacturer’s instructions (Bioline, Australia). Extracted DNA was assessed for quality and quantity using the Qubit 2.0 fluorometer (Thermo Fischer Scientific, Australia).
STH infection diagnosis and microbiome characterisation
A previously published multiplexed-tandem qPCR assay [29] was used to qualitatively and quantitatively detect STH infections among all faecal samples. We used this test to screen for roundworm (Ascaris lumbricoides), whipworm (Trichuris trichiura) and hookworm (Ancylostoma spp. and Necator americanus) species following the manufacturer’s instructions (AusDiagnostics, Ltd. Py., Australia).
The faecal microbial community for DESS preserved samples was characterised by 16S rRNA gene sequencing. Each stool sample was sequenced in duplicate using the universal bacterial 16S V4 primers (515F 5’-CTGAGACTTGCACATCGCAGCGTGYCAGCMGCCGCGGTAA-3’ and 806R 5’-GTGACCTATGAACTCAGGAGTCGGACTACNVGGGTWTCTAAT-3’) on the Illumina MiSeq platform (Illumina, USA) [30,31]. Each 96-well PCR plate contained a negative (dH2O) and positive (ZymoBIOMICS microbial community DNA standard, Zymo Research, Integrated Sciences, Australia) control, with individual reactions conducted under the following conditions: 10 μl OneTaq master mix with standard buffer (2x) (New England Biolabs, USA), 0.4 μl of each primer (10 μM) and 2 μl DNA template made up to a total reaction volume of 20 μl with water were amplified for 3 minutes at 95°C, 45 seconds at 95°C, 60 seconds at 50°C and 90 seconds at 72°C in 20 cycles with a final extension time of 10 minutes at 72°C. Following first round amplification all PCR products were diluted 1:5 in molecular grade H2O and diluted products used as a template for a second PCR amplification using unique adapter barcodes (8-mer) for each sample. Each PCR reaction was conducted under the following conditions: 15 μl OneTaq master mix with standard buffer (2x) (New England Biolabs, USA), 1.5 μl of each primer (10 μM) and 10 μl of diluted PCR product made up to a total reaction volume of 30 μl using water were amplified for 3 minutes at 95°C, 45 seconds at 95°C, 60 seconds at 55°C and 90 seconds at 72°C in 25 cycles with a final extension time of 10 minutes at 72°C. Quality control was performed using a representative selection of PCR products from all rows and columns on each plate through size separation on a 1.5% agarose gel. Following amplification, 5 μl of each product was pooled into the final sequencing library and any artifacts removed using the NucleoMag NGS clean-up and size-select kit (0.8X) as per the manufacturer’s instructions (Machery-Nagel). Pooled libraries were eluted in 55 μl of sterile H2O and quantified on the Agilent 4200 TapeStation and amplicon sequenced on the Illumina MiSeq platform using the MiSeq Reagent Kit V3 2 x 300bp as per the manufacturer’s instructions (Illumina, USA).
Data analysis
STH Infection Prevalence and Intensity.
MT-PCR data were processed in Excel 16.13.1 (Microsoft, USA), Stata 12.1 (STATA Corp, USA), visualized using GraphPad Prism 7.0d (GraphPad Software Inc., USA) and stool samples deemed infection positive or negative as per MT Analysis Software output (AusDiagnostics Pty. Ltd., Sydney). Kappa statistics (interrater reliability), sensitivity, specificity and correlation with epidemiological variables were calculated to evaluate performance of the MT-PCR method compared to the gold standard KKTS using Stata 12.1 (STATA Corp, USA). Impacts of STH infections defined as stunting and wasting were calculated as height-for-weight, height-for-age and weight-for-age z-scores compared to the 2006 WHO child growth standard [32]. Anthropometric z-score calculations were performed in Stata 12.1 (STATA Corp, USA) using the “zscores06” command [33].
Gut microbiome characterisation of the V4 16S rRNA gene.
Following comparative analysis of three-way sample preservation as described elsewhere [34], we examined STH infection prevalence and intensity based on DESS preserved stools only. For microbiome characterisation, we tested for sequence batch effects in the initial 48 and subsequent 225 sequenced DESS preserved samples. We did this by merging both datasets before the OTU clustering step in vsearch and plotted alpha- (observed richness p-value 0.9654; inverted Simpson p-value 0.9088) and beta-diversity (p-value 0.001). Because the intra-sample diversity showed no significant change among sequencing runs, we combined the data for all subsequent analyses.
The microbial community diversity and composition was analysed using an established protocol [35]. A QIIME1 mapping file containing metadata for each replicate according to their unique index barcode was generated [36], followed by merging of paired-end reads using PEAR [37] with the following parameters: minimum overlap 100 bp, maximum assembly length 600 bp and minimum assembly length 80 bp. Resulting sequences were demultiplexed, orientation adjusted (p = 0.90, Phred quality score cut-off 29, base call accuracy>99.9%) and the 16S V4 rRNA gene universal primers trimmed (https://github.com/PapenfussLab/Jocelyn_tools/blob/master/amplicon_tools/trim_fasta_amplicons.py). Using Mothur 1.39.5 the trimmed sequences were aligned to the Silva database, the alignment cut and filtered to remove overhangs at both ends [38]. Next, sequences were deduplicated, clustered into operational taxonomy units (OTUs), a reference generated, and chimeras filtered using vsearch (minimum sequence length 64 bp). Taxonomy was assigned using the Greengenes database [39]. A phylogenetic tree was generated in QIIME1 using the make_phylogeny.py script by aligning all sequences to the reference in Mothur. Finally, the metadata, taxonomy and phylogeny information were compiled into a biom file with all quality filtered sequences. The full pipeline is available online (https://github.com/PapenfussLab/RothSchulze_microbiome).
In RStudio 1.1.453 technical replicates were merged and data (a) rarefied for alpha-diversity and differential abundance analysis, or (b) normalised using the cumulative sum squaring in QIIME1 for beta-diversity analysis, using phyloseq 1.26.1 [40]. Alpha-diversity measures were estimated by plotting observed richness, inverted Simpson and Shannon estimated diversity indexes using the plot_richness function in phyloseq 1.26.1 and visualized with microbiomeSeq 0.1 (https://github.com/umerijaz/microbiomeSeq). Statistical analysis was performed with pairwise analysis of variance (ANOVA) tests on a fitted, linear and releveled regression model on observed richness data (estimate_richness function in phyloseq 1.26.1). Relative and differential taxonomic abundance analysis were performed by estimating the mean proportion, fitting a linear model and applying a pairwise ANOVA test in RStudio 1.1.453, and the ‘DESeq2_nbinom’ algorithm in QIIME1, respectively. Beta-diversity measures were estimated using the ordinate and distance function with Bray Curtis measure for PCoA and weighted UniFrac for NMDS in phyloseq 1.26.1. Statistical analysis was performed with Euclidian distance and 999 permutations using the adonis function in the vegan package 2.5–4 and pairwise.perm.manova function in RVAideMemoire package 0.9–73. A p-value threshold of <0.05 was used for statistical significance following correction for multiple testing by the Benjamini-Hochberg false discovery rate (FDR) method for all tests. All data were visualised using the phyloseq 1.26.1 and ggplot 3.1.0 packages in RStudio 1.1.453 (RStudio, Inc., USA).
Results
Cohort epidemiology
All 273 participants (133 male and 132 female) included in this study were pre-school and school-aged children as follows: 3 years (18 female, 27 male), 4 years (45 female, 38 male), 5 years (35 female, 35 male), 6 years (24 female, 24 male) and 27 individuals with no age information (10 female, 9 male). Eight individuals had no sex information provided. Participants were from 11 schools from Tha Song Yang district, Tak province in Thailand, namely: Mae Song, Thi Mo Ko Tha, Mae Salid Khi, Mae Salid Luang, Mae Salid Noi, Krae Khi, Mae Kho, Mae Nil, Mae Nil Khi, Huay Manhok and Huay Manhok Khi. Stool samples were collected from the 28th to 30th of March 2017 as part of an ongoing local field study (S1 Table).
Child growth measures were available for 246 (90.11%, aged 0–5 years) of the 273 children with average measures as follows: mean age 59.2 completed months (36–82), mean weight 15.8 kg (8.2–21.7) and height 103.5 cm (78–122) (S2 Table). Of this subset, 27 (11.0%) children were stunted (height-for-age < -2 standard deviation from median) including 15 with any STH infection, six (2.4%) were wasted (weight-for-height < -2 standard deviation from median) including two with any STH infection and 17 (6.9%) were underweight (weight-for-age < -2 less than standard deviation from median) including nine with any STH infection. Further, four (1.6%) children were deemed too tall for their age (height-for-age > 2 standard deviation from median) including two with any STH infection and 1 (0.4%) had a weight-for-height measure above two standard deviations from median. We found no association between any of these metrices and bacterial (alpha-/beta-) diversity measures.
Total infection prevalence of any helminth species by microscopy was 49.3% by KKTS (Table 1). Infection intensity as determined by microscopic egg count ranged from 1 –>1,000 As. lumbricoides fertilized/unfertilized eggs (mean egg count 595.89) and 1–190 T. trichiura eggs (mean egg count 21.23). We note that 51 (46.8%) and 15 (17.4%) As. lumbricoides KKTS positive samples had egg densities reaching a threshold of 1,000 and 500 eggs per gram at which counting ceased, respectively (S2 Fig). Hookworm prevalence was not assessed as it was not feasible to process samples within one hour after drop-off [41]. Although not part of this study, each sample was additionally assessed for other parasitic infections via field-based microscopy, with the results as follows: 2 Enterobius vermicularis, 41 Giardia duodenalis, 5 Entamoeba histolytica, 69 Entamoeba coli, 29 Blastocystis spp., 5 Iodamoeba bushlii, 53 Endolimax nana, 10 Chilomastix mesnili and 1 Cystoisospora bellii infections.
Interrater reliability measure or kappa values are classified as follows: κ 0.0–0.2 non to slight, 0.2–0.4 fair,0.4–0.6 moderate, 0.6–0.8 substantial, 0.8–1.0 almost perfect [42]. Sensitivity is classified as the rate of true positive samples and specificity as the rate of true negative samples compared to a known gold standard (Kato Katz thick smear). Epidemiological and microscopy data for 5 individuals were missing.
STH infection prevalence and intensity.
Based on molecular testing, STH prevalence was 39.2% (n = 107), 36.6% (n = 100) and 1.1% (n = 3) for As. lumbricoides, T. trichiura and An. ceylanicum, respectively (Table 1). Diagnostic target gene copy number for STH positive samples ranged from 39–4,711,749 for As. lumbricoides (mean copy number 272,931.8 and Ct value 23.8), 85–5,251 An. ceylanicum (mean copy number 3,058.3 and Ct value 28.9) and 33–6,343 T. trichiura (mean copy number 709.47 and Ct value 30.9) as determined by MT-PCR concentration (S1 Table). For the 51 As. lumbricoides samples containing >1,000 eggs per gram, target copy number ranged from 0–4,711,749.0 (mean copy number 505,851.5).
Diagnostic agreement between KKTS and MT-PCR was 91.8% and 88.4% for roundworm and whipworm. Diagnostic sensitivity (microscopy gold standard) was 89.0% for roundworm and 89.5% for whipworm with a diagnostic specificity of 93.7% and 87.9%, respectively. Interrater reliability (kappa) values ranged from 0.745 to 0.829 with confidence intervals from 0.770 to 0.864 (Table 1). Sixty-six infected individuals (46.8%) had co-infections with As. lumbricoides and T. trichiura by MT-PCR. Two individuals were infected with As. lumbricoides, T. trichiura and An. ceylanicum; and one with T. trichiura and An. ceylanicum. We found no correlation between schools and STH infection status, except for one school in Mae Kho having the significantly highest number of infected children (p-value <0.001) (S6 Table). We found no correlation between sex and STH infection status (p-values 0.281, 0.204, 0.143), MT-PCR Ct value (p-values 0.387, 0.208, 0.113) and MT-PCR gene copy number (p-values 0.799, 0.351, 0.685) for As. lumbricoides, An. ceylanicum or T. trichiura, respectively. Overall, we found a relatively even distribution of species-specific infections among all age groups: 16 As. lumbricoides, 1 An. ceylanicum and 15 T. trichiura among 3-year old’s; 30 As. lumbricoides, 0 An. ceylanicum and 28 T. trichiura among 4-year old’s; 29 As. lumbricoides, 0 An. ceylanicum and 31 T. trichiura among 5-year old’s; and 27 As. lumbricoides, 2 An. ceylanicum and 21 T. trichiura among 6-year old’s.
Gut microbiome characterisation.
We explored the acute effects of STH infections on gut microbial health comparing children with (“infected”; n = 141) and without (“uninfected”; n = 132) STH infection at the time of sampling. Information on the prior infection history of children in our study was not available, and we cannot make inference on the longer-term impacts that STH infection may have on microbial development in the gut. Overall, Firmicutes, Bacteriodetes, Proteobacteria and Actinobacteria were the most abundant bacterial phyla across the complete cohort (Fig 1 and S3 Table). The majority (56.5%) of operational taxonomic units (OTUs) assigned to bacterial genera were classified as Prevotella, Faecalbacterium, Succinivibrio and Catenibacterium. Before characterising differences in the microbiome associated with STH infection, we examined the data at a cohort level, considering participant sex, age and geographic location (Fig 1). We found no significant differences at a higher taxonomic level between male and female participants. However, two OTUs (OTU 65 Bacteroides coprophilus, OTU 9 Mollicutes) were more and six OTUs (OTU 214 Prevotella, OTU 84 Parabacteroides, OTU 89 Bacteroides uniformis, OTU 23 Bacteroides fragilis, OTU 200 Ruminococcus and OTU 20 Lactococcus garvieae) statistically significantly less abundant comparing females to males (Fig 2 and S5 Table; p-value < 0.05). Further, we observed no significant differences in alpha-diversity or beta-diversity based on participant sex and age (Figs 3 and 4 and S4 Table).
Infection intensity classification is depicted in MT-PCR gene copy number output and cycle threshold (Ct) values separated after species-specific infections: Ascaris lumbricoides (Alu), Necator americanus (Nam), Ancylostoma ceylanicum (Ace), Ancylostoma duodenale (Adu) and Trichuris trichiura (Ttr) (from left to right). Scale bar represents evolutionary distance. Relative abundance is visualised in percentage of all bacterial phyla (B) and the top 50 bacterial genera (C). Abbreviations within the figure for schools are KK: Krae Khi, MN: Mae Nil, MNK: Mae Nil Khi, HM: Huay Manhok, HMK: Huay Manhok Khi, MSK: Mae Salid Khi, MK: Mae Kho, MSN: Mae Salid Noi, MS: Mae Song, MSL: Mae Salid Luang and TMKT: Thi Mo Ko Tha; and for diagnostics K: Kato Katz thick smear, M: MT-PCR, G: gene copy number and C: Ct value.
Abundance of significantly increased and decreased operational taxonomic units (OTU) as per log fold change influenced by soil-transmitted helminth (STH) infection status estimated by multiplexed-tandem qPCR (MT-PCR) (A) for Ascaris lumbricoides (a) and Trichuris trichiura (aa) and sex (B). Green or orange OTUs are found to be significantly more abundant and purple or blue OTUs significantly less abundant (ns = not significant). For STH infection status (A) OTU 91 Akkermansia muciniphila, OTU 214 Prevotella, OTU 65 Bacteroides coprophilus, OTU 118 Ruminococcaceae, OTU 9 Tenericutes are more and OTU 527 Bifidobacterium adolescentis is less abundant. For sex (B) OTU 65 Bacteroides coprophilus, OTU 9 Mollicutes, OTU 214 Prevotella, OTU 84 Parabacteroides, OTU 89 Bacteroides uniformis, OTU 23 Bacteroides fragilis are more and OTU 200 Ruminococcus, OTU 20 Lactococcus garvieae are less abundant.
Geographical location of some schools correlated with inverted Simpson alpha-diversity, with children from Mae Nil Khi and This Mo Ko Tha having significantly lower alpha-diversity compared to children from Huay Manhok (p-value < 0.05); and children from Mae Nil Khi showing a lower alpha-diversity than those from Mae Kho and Mae Song (Fig 3). Beta-diversity also significantly differed (p-value 0.032) among schools (Fig 4 and S4 Table). These differences were apparent at a taxonomic level, with children from Huay Manhok Khi having significantly more Actinobacteria (p-value 0.0217) and those from Mae Salid Noi, Mae Nil Khi and Mae Kho having significantly less Eubacterium (p-values 0.0311, 0.0385, 0.0433).
Statistical analysis was performed using a p-value cut-off of 0.05 (*0.05 **0.005 ***0.0005) for soil-transmitted helminth (STH) infection status as estimated by multiplexed-tandem qPCR (MT-PCR) (0 uninfected, 1 infected) (A), age (3 to 6 years) (B), school (C) and sex (female, male) (D).
Beta-diversity measure as calculated by principal coordinates analysis (PCoA) with Bray-Curtis distance clustering (A) and non-metric multi-dimensional scaling (NMDS) using weighted UniFrac distance measure (B) of the complete cohort of faecal samples preserved in DESS (n = 273). PCoA with Bray-Curtis distance clustering for sex (C), soil-transmitted helminth (STH) infection status (D), age (E) and school (F) are shown (p-values 0.571; 0.021; 0.778; 0.032).
We found no significant difference in bacterial alpha-diversity between STH infected and uninfected study participants (Fig 3 and S4 Table). However, their faecal microbiomes did differ significantly in beta-diversity (Fig 4, p-value 0.021). Although, we found no significant changes at higher taxonomic levels, there were statistically significant (p-value < 0.05) changes in differential abundance at the OTU level (S5 Table). Five OTUs, one Verrumicrobia (OTU 91, Akkermansia muciniphila), two Bacteriodetes (OTU 124, Prevotella; OTU 65, Bacteroides coprophilus), one Firmicutes (OTU 118, Ruminococcaceae) and one Tenericutes (OTU 9) were significantly more abundant and one OTU (OTU 527, Bifidobacterium adolescentis) was less abundant comparing uninfected versus infected children (Fig 2 and S5 Table). Interestingly, when comparing differential OTU abundance between only As. lumbricoides positive (n = 41) and uninfected participants we found a large number of OTUs (n = 16) to be less abundant compared to three more abundant. The same is true for only T. trichiura positive samples (n = 33) (25 less and 2 more abundant) (Fig 2 and S5 Table).
Discussion
In this study, we characterised the molecular STH infection status of Thai pre-school and school-aged children as well as their baseline gut microbiome profile. A large proportion of co-infections with As. lumbricoides and T. trichiura in this subpopulation is consistent with global STH-endemic estimates in other regions [43]. Using the highly sensitive MT-PCR we were able to identify three An. ceylanicum infections that were not detected by microscopy. We investigated the association between infection status and health metric (weight, height), but found no significant difference to uninfected children.
We also explored the acute effects of current STH infection on the faecal microbiome. Overall, the predominant bacterial phyla, with Bacteriodetes, Firmicutes, Proteobacteria and Actinobacteria being most abundant, were consistent with similar studies of enteric bacteria elsewhere [44–46]. A multitude of factors are able to shape the gut microbiome composition. Besides infection [10,47], this can include diet [48], age [49], caesarean versus vaginal birth [50], medication, particularly antibiotic usage [51], and numerous other factors [52]. In our study, we noted statistically significant differences in alpha-diversity with school location, possibly reflecting dietary differences. Noting these host factors, we found no evidence for an association between sex, age or school and STH infection and thus, are able to consider the effect of infection despite the confounding influence they may have had on microbial composition. Although a small proportion of children were stunted, wasted and underweight for their age, we found this did not impact microbial diversity compared to healthy children.
Numerous studies have explored the impact of STH infections on the gut microbial community, and in turn on the host immune system [53,54], child development and the risk of chronic post-infectious gastrointestinal disorders, as has been seen for parasitic protists, such as Giardia [55]. The results of these studies are highly variable, have been reviewed in detail elsewhere [56,57], and highlight the complexity of this topic. The lack of uninfected, community-based controls, or rather, how these controls are defined is one major challenge. In our study, we assessed the faecal microbiome of children with, at the time of sampling, patent STH infections and compared this to samples collected from uninfected children from the same community and at the same point in time. However, it is important to recognize that our observations are based on a snapshot in time and the prior infection history of our study participants is not available. This point is important in considering current studies on this field. Studies of helminth infection in mouse models have found the most consistent evidence for helminth-induced reprofiling of the gut microbial community [56], showing a loss in alpha-diversity and changes in the relative abundance of key microbial phyla, including reductions in Firmicutes and Bacteroidetes, and statistically significant shifts in abundance of a variety of specific OTUs. Studies comparing experimentally infected human volunteers to uninfected controls in non-endemic regions generally yield comparable results, showing altered alpha-diversity, species richness and the relative abundance of specific taxa, such as species of Bacteroides and Turibacter [57–59]. However, to date, field-based studies using cross-sectional surveillance, have produced more variable results [56,57], which are likely affected by the STH species and other complex biological, technical and environmental factors [57]. Recently, field studies conducted in Malaysia, Liberia and Indonesia found STH infections correlated with an increase in the host gut microbial diversity and richness [11,12], but another in Ecuador found no effect [22].
Here, we found no difference in alpha-diversity or relative abundance with STH infection. This is largely consistent with other field-based studies [56,57]. We did see differences in bacterial beta-diversity with STH infection. This too is consistent with a previous study of STH infections in Sri Lanka [46], but has not been observed in other field studies [22,60], and may depend on the infective STH species [57]. We did not see major changes in the relative abundance of bacterial phyla, but we did see specific changes in OTU composition. In our study, STH infection was associated with a statistically significant increase in abundance of Akkermansia muciniphila. A recent meta-analysis of published studies on the impact of helminths on gut microbiomes identified a 3-fold increase in the relative abundance of Akkermansia in rodent models upon helminth infection [56]. This increase has been described also in primates infected with T. trichiura [61]. The authors of the meta-analysis [56] noted that Akkermansia species are associated with increased mucin degradation; it is worth noting that Trichuris species are known for their capacity to secrete a rich cocktail of mucin-degrading proteases [62,63]. To our knowledge, ours is the first study to note this change in humans. We also found a statistically significant decrease in Bifidobacterium, which is consistent with prior observations in rodent models [56]. Interestingly, we saw a statistically significant increase in the relative abundance of Bacteroides coprophilus with STH infection. Although a previous study noted an increase in pro-inflammatory Bacteroides vulgatus following deworming treatment in endemic individuals [64], recent studies of gut microbiome changes associated with inflammatory conditions, including multiple sclerosis [65], and during hepatitis-c infection [66], identify decreases in both B. coprophilus and A. mucinphila in the diseased state. Overall a reduction in OTUs correlating with A. lumbricoides and T. trichiura infections is notable. It is possible, although highly speculative, that helminths manipulate both pro- and anti-inflammatory microbes during infection as part of their well-documented efforts to manipulate the vertebrate immune response, particularly through repression of Th1/Th17 and promotion of Th2 type responses [67,68]. Clearly, this requires further study.
Much of the uncertainty associated with studies to date on the impacts of STH infection on the gut microbiome likely relates to the complexity of the interaction and technical aspects of the study design or analytical approach. As noted here, study design must consider the impact of sample collection and preservation, and our hope is that our evaluation of DESS as a low-cost preservative for STH and microbiome studies will assist in overcoming this challenge. In addition, sample size, particularly in relation to studies in remote and resource-poor populations, will affect resolution and limits study design. We have been deliberate in distinguishing our capacity to assess acute impacts of current STH infections on the gut microbiome, relative to endemic controls, from efforts to assess longer term or more universal impacts of STH infections overall. The latter requires either a complex longitudinal cohort study, or, at least, community-matched controls from non-endemic populations or with a known infection history. Appropriate matched controls with no prior history of STH infection are difficult to identify, especially in endemic regions where STH prevalence typically exceeds 50% of the population. This issue likely contributes to the lack of congruence between field-based microbiome studies of STH infections (all of which are realistically limited to observations of the acute effects of STH infections) from observations in mouse models or volunteer patients in non-endemic populations. Studies of the impact of STHs on the gut microbial community must, in our view, be equally aware of the complexity that infection intensity may play on the study outcome. Our study considers primarily low-intensity infections, and we cannot infer the potential acute or chronic consequences of higher intensity infections; although it appears reasonable to speculate that both infection intensity and frequency will influence the extent to which STH infections might cause reprofiling of the gut microfauna, as has been shown for other gastrointestinal pathogens [69].
Supporting information
S1 Fig. Stool collection workflow including sample collection, processing, storage and shipping information after the Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines [70].
STH: soil-transmitted helminths; PSC: pre-school children; SAC: school-aged children; DESS: DMSO, EDTA and NaCl; PD: 2.5% potassium dichromate, FF: fresh frozen; MT-PCR: multiplexed-tandem qPCR.
https://doi.org/10.1371/journal.pntd.0009597.s001
(TIFF)
S2 Fig. Statistical analysis of Ascaris lumbricoides positive individuals with more or less than 1,000 eggs by Kato Katz thick smear in relation to multiplexed-tandem qPCR (MT-PCR) cycle threshold (Ct) value (A) and gene copy number (GCN) (B).
https://doi.org/10.1371/journal.pntd.0009597.s002
(TIFF)
S1 Table. Metadata table including epidemiological data from Thai pre-school and school-aged children, sample collection data and STH infection prevalence and intensity data via microscopy (Kato Katz thick smear) and multiplexed-tandem qPCR.
All patient samples have been de-identified using a unique sample ID. A. lum: Ascaris lumbricoides; N. ame: Necator americanus; A. cey: Ancylostoma ceylanicum; A. duo: Anceylostoma duodenale; T. tri: Trichuris trichiura; Conc: Concentration in gene copy number; Ct: cycle threshold value.
https://doi.org/10.1371/journal.pntd.0009597.s003
(XLSX)
S2 Table. WHO-recommended height-for-weight, height-for-age and weight-for-age z- score analysis.
Patients older than 5 years of age were not included due to no available reference standard. MT-PCR: multiplexed-tandem qPCR; Ct: cycle threshold value; BMI: body mass index.
https://doi.org/10.1371/journal.pntd.0009597.s004
(XLSX)
S3 Table. Relative abundance data of bacterial phyla and genera including statistical analysis.
https://doi.org/10.1371/journal.pntd.0009597.s005
(XLSX)
S4 Table. Operational taxonomic unit (OTU) data table for alpha- and beta-diversity measures (n = 273).
OTU: operational taxonomic unit; NA: not available.
https://doi.org/10.1371/journal.pntd.0009597.s006
(XLSX)
S5 Table. Differential operational taxonomic unit (OTU) abundance analysis comparing any soil-transmitted helminth (STH) infection, Ascaris lumbricoides infection, Trichuris trichiura infection (uninfected versus infected), and sex (male versus female) (n = 273).
https://doi.org/10.1371/journal.pntd.0009597.s007
(XLSX)
S6 Table. Participant data per soil-transmitted helminth (STH) infection and school.
A.lum: Ascaris lumbricoides; T. tri: Trichuris trichiura; A. cey: Ancylostoma ceylanicum; N. ame: Necator americanus; A.duo: Ancylostoma duodenale; MT-PCR: multiplexed-tandem qPCR; GCN: gene copy number; Ct: cycle threshold.
https://doi.org/10.1371/journal.pntd.0009597.s008
(XLSX)
Acknowledgments
We would like to thank the Mae Song sub-district administration office and the Tha Song Yang district health office for their support with this study. We are also grateful for the continuous efforts of the local Thai field team, the study participants and their parents or guardians.
References
- 1. Jourdan PM, Lamberton PH, Fenwick A, Addiss DG. Soil-transmitted helminth infections. Lancet. 2018;10117:252–65 pmid:28882382
- 2. Vlaminck J, Cools P, Albonico M, Ame S, Ayana M, Bethony J, et al. Comprehensive evaluation of stool-based diagnostic methods and benzimidazole resistance markers to assess drug efficacy and detect the emergence of anthelmintic resistance: A Starworms study protocol. PLOS Negl Trop Dis. 2018;12(11):e0006912. pmid:30388108
- 3.
Montresor A, Crompton DW, Gyorkos TW, Savioli L. Helminth control in school-age children: a guide for managers of control programmes. World Health Organization. 2002.
- 4. Pabalan N, Singian E, Tabangay L, Jarjanazi H, Boivin MJ, Ezeamama AE. Soil-transmitted helminth infection, loss of education and cognitive impairment in school-aged children: A systematic review and meta-analysis. PLOS Negl Trop Dis. 2018;12(1):e0005523. pmid:29329288
- 5.
World Health Organization. Soil-Transmitted Helminthiases. Eliminating Soil-Transmitted Helminthiases as a Public Health Problem in Children: Progress Report 2001–2010 and Strategic Plan 2011–2020. World Health Organization, Geneva, Switzerland. 2012.
- 6. Murray CJ, Barber RM, Foreman KJ, Ozgoren AA, Abd-Allah F, Abera SF, et al. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990–2013: quantifying the epidemiological transition. Lancet. 2015;386(10009):2145–91. pmid:26321261
- 7. Becker SL, Liwanag HJ, Snyder JS, Akogun O, Belizario V Jr, Freeman MC, et al. Toward the 2020 goal of soil-transmitted helminthiasis control and elimination. PLOS Negl Trop Dis. 2018;12(8):e0006606. pmid:30106975
- 8. Basuni M, Muhi J, Othman N, Verweij JJ, Ahmad M, Miswan N, et al. A pentaplex real-time polymerase chain reaction assay for detection of four species of soil-transmitted helminths. Am J Trop Med Hyg. 2011;84(2):338–43. pmid:21292911
- 9. Nikolay B, Brooker SJ, Pullan RL. Sensitivity of diagnostic tests for human soil-transmitted helminth infections: a meta-analysis in the absence of a true gold standard. Int J Parasitol. 2014;44(11):765–74. pmid:24992655
- 10. Gause WC, Maizels RM. Macrobiota—helminths as active participants and partners of the microbiota in host intestinal homeostasis. Curr Opin Microbiol. 2016;32:14–8. pmid:27116368
- 11. Rosa BA, Supali T, Gankpala L, Djuardi Y, Sartono E, Zhou Y, et al. Differential human gut microbiome assemblages during soil-transmitted helminth infections in Indonesia and Liberia. Microbiome. 2018;6(1):33. pmid:29486796
- 12. Lee SC, San Tang M, Lim YA, Choy SH, Kurtz ZD, Cox LM, et al. Helminth colonization is associated with increased diversity of the gut microbiota. PLOS Negl Trop Dis. 2014;8(5):e2880. pmid:24851867
- 13. Gordon CA, Krause L, McManus DP, Morrison M, Weerakoon KG, Connor MC, et al. Helminths, polyparasitism, and the gut microbiome in the Philippines. Int J Parasitol. 2020;50(3):217–25 pmid:32135180
- 14. Guernier V, Brennan B, Yakob L, Milinovich G, Clements AC, Magalhaes RJS. Gut microbiota disturbance during helminth infection: can it affect cognition and behaviour of children? BMC Infect Dis. 2017;17(1):58. pmid:28073356
- 15. Taylor-Robinson DC, Maayan N, Soares-Weiser K, Donegan S, Garner P. Deworming drugs for soil-transmitted intestinal worms in children: effects on nutritional indicators, haemoglobin and school performance. Cochrane Database Syst Rev. 2012;11.
- 16. Glendinning L, Nausch N, Free A, Taylor DW, Mutapi F. The microbiota and helminths: sharing the same niche in the human host. Parasitology. 2014;141(10):1255–71. pmid:24901211
- 17. Pflughoeft KJ, Versalovic J. Human microbiome in health and disease. Annu Rev Pathol. 2012;7:99–122. pmid:21910623
- 18. Holmes E, Li JV, Athanasiou T, Ashrafian H, Nicholson JK. Understanding the role of gut microbiome–host metabolic signal disruption in health and disease. Trends Microbiol. 2011;19(7):349–59. pmid:21684749
- 19. Cooper PJ. Interactions between helminth parasites and allergy. Curr Opin Allergy Clin Immunol. 2009;9(1):29. pmid:19106698
- 20. Brosschot TP, Reynolds LA. The impact of a helminth-modified microbiome on host immunity. Mucosal Immunol. 2018;11(4):1039. pmid:29453411
- 21. Maizels RM. Regulation of Immunity and allergy by helminth parasites. Allergy. 2020;75(3):524–34. pmid:31187881
- 22. Cooper P, Walker AW, Reyes J, Chico M, Salter SJ, Vaca M, et al. Patent human infections with the whipworm, Trichuris trichiura, are not associated with alterations in the faecal microbiota. PLOS One. 2013;8(10):e76573. pmid:24124574
- 23. Rubel MA, Abbas A, Taylor LJ, Connell A, Tanes C, Bittinger K, et al. Lifestyle and the presence of helminths is associated with gut microbiome composition in Cameroonians. Genome Biol. 2020;21(1):1–32. pmid:32450885
- 24. Zaiss M, Harris N. Interactions between the intestinal microbiome and helminth parasites. Parasite Immunol. 2016;38(1):5–11. pmid:26345715
- 25. O’Connell EM, Mitchell T, Papaiakovou M, Pilotte N, Lee D, Weinberg M, et al. Ancylostoma ceylanicum Hookworm in Myanmar Refugees, Thailand, 2012–2015. Emerg Infect Dis. 2018;24(8):1472.
- 26. Piangjai S, Sukontason K, Sukontason KL. Intestinal parasitic infections in hill-tribe schoolchildren in Chiang Mai, Northern Thailand. Southeast Asian J Trop Med Public Health. 2003;34:90–3. pmid:19230577
- 27.
Ilce A. Fecal Incontinence: Causes, Management and Outcome. Fecal incontinence. 1st ed. Rijeka: InTechOpen; 2014.
- 28. Yoder M, De Ley IT, King IW, Mundo-Ocampo M, Mann J, Blaxter M, et al. DESS: a versatile solution for preserving morphology and extractable DNA of nematodes. Nematology. 2006;8(3):367–76.
- 29. Stracke K, Clarke N, Awburn CV, Nery SV, Khieu V, Traub RJ, et al. Development and validation of a multiplexed-tandem qPCR tool for diagnostics of human soil-transmitted helminth infections. PLOS Negl Trop Dis. 2019;13(6):e0007363. pmid:31206520
- 30. Apprill A, McNally S, Parsons R, Webe L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat Microb Ecol. 2015;75:129–137
- 31. Parada AE, Needham DM, Fuhrman JA. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ Microbiol. 2015;18(5):1403–14. pmid:26271760
- 32. World Health Organization. WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age: methods and development. 2006.
- 33. Leroy J. ZSCORE06: Stata module to calculate anthropometric z-scores using the 2006 WHO child growth standards. Econ Pap. 2011.
- 34. Stracke K, Adisakwattana P, Phuanukoonnon S, Yoonuan T, Poodeepiyasawat A, Dekumyoy P, et al. Effective low-cost preservation of human stools in field-based studies for helminth and microbiota analysis. Int J Parasitol. 2021. pmid:33774039
- 35. Penington JS, Penno MA, Ngui KM, Ajami NJ, Roth-Schulze AJ, Wilcox SA, et al. Influence of fecal collection conditions and 16S rRNA gene sequencing at two centers on human gut microbiota analysis. Sci Rep. 2018;8(1):4386. pmid:29531234
- 36. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335. pmid:20383131
- 37. Zhang J, Kobert K, Flouri T, Stamatakis A. PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics. 2013;30(5):614–20. pmid:24142950
- 38. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75(23):7537–41. pmid:19801464
- 39. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006;72(7):5069–72. pmid:16820507
- 40. McMurdie PJ, Holmes S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLOS One. 2013;8(4):e61217. pmid:23630581
- 41. Martin LK, Beaver PC. Evaluation of Kato thick-smear technique for quantitative diagnosis of helminth infections. Am J Trop Med Hyg. 1968;17(3):382–91. pmid:5690644
- 42. McHugh ML. Interrater reliability: the kappa statistic. Biochem Med. 2012;22(3):276–82. pmid:23092060
- 43. Brooker S, Clements ACA, Bundy DAP. Global Epidemiology, Ecology and Control of Soil-Transmitted Helminth Infections. Adv Parasitol. 2006;62:221–61. pmid:16647972
- 44. Lozupone CA, Stombaugh JI, Gordon JI, Jansson JK, Knight R. Diversity, stability and resilience of the human gut microbiota. Nature. 2012;489(7415):220–30. pmid:22972295
- 45. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L, Sargent M, et al. Diversity of the human intestinal microbial flora. Science. 2005;308(5728):1635–8. pmid:15831718
- 46. Jenkins TP, Rathnayaka Y, Perera PK, Peachey LE, Nolan MJ, Krause L, et al. Infections by human gastrointestinal helminths are associated with changes in faecal microbiota diversity and composition. PLOS One. 2017;12(9):e0184719. pmid:28892494
- 47. Berrilli F, Di Cave D, Cavallero S, D’Amelio S. Interactions between parasites and microbial communities in the human gut. Front Cell Infect Microbiol. 2012;2:141. pmid:23162802
- 48. De Filippo C, Cavalieri D, Di Paola M, Ramazzotti M, Poullet JB, Massart S, et al. Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa. Proc Natl Acad Sci. 2010;107(33):14691–6. pmid:20679230
- 49. Odamaki T, Kato K, Sugahara H, Hashikura N, Takahashi S, Xiao J-z, et al. Age-related changes in gut microbiota composition from newborn to centenarian: a cross-sectional study. BMC Microbiol. 2016;16(1):90. pmid:27220822
- 50. Bokulich NA, Chung J, Battaglia T, Henderson N, Jay M, Li H, et al. Antibiotics, birth mode, and diet shape microbiome maturation during early life. Sci Transl Med. 2016;8(343):343ra82–ra82. pmid:27306664
- 51. Blaser MJ. Antibiotic use and its consequences for the normal microbiome. Science. 2016;352(6285):544–5. pmid:27126037
- 52. Debelius J, Song SJ, Vazquez-Baeza Y, Xu ZZ, Gonzalez A, Knight R. Tiny microbes, enormous impacts: what matters in gut microbiome studies? Genome Biol. 2016;17(1):217. pmid:27760558
- 53. Reynolds JM, Lee Y-H, Shi Y, Wang X, Angkasekwinai P, Nallaparaju KC, et al. Interleukin-17B antagonizes interleukin-25-mediated mucosal inflammation. Immunity. 2015;42(4):692–703. pmid:25888259
- 54. Rapin A, Harris NL. Helminth–bacterial interactions: cause and consequence. Trends Immunol. 2018;39(9):724–33. pmid:29941203
- 55. Hanevik K, Dizdar V, Langeland N, Hausken T. Development of functional gastrointestinal disorders after Giardia lambliainfection. BMC Gastroenterol. 2009;9(1):27.
- 56. Scotti R, Southern S, Boinett C, Jenkins TP, Cortés A, Cantacessi C. MICHELINdb: a web-based tool for mining of helminth-microbiota interaction datasets, and a meta-analysis of current research. Microbiome. 2020;8(1):10. pmid:32008578
- 57. Cortés A, Peachey LE, Jenkins TP, Scotti R, Cantacessi C. Helminths and microbes within the vertebrate gut–not all studies are created equal. Parasitology. 2019;146(11):1371–8. pmid:31258097
- 58. Giacomin P, Zakrzewski M, Jenkins TP, Su X, Al-Hallaf R, Croese J, et al. Changes in duodenal tissue-associated microbiota following hookworm infection and consecutive gluten challenges in humans with coeliac disease. Sci Rep. 2016;6(1):1–10. pmid:28442746
- 59. Jenkins TP, Formenti F, Castro C, Piubelli C, Perandin F, Buonfrate D, et al. A comprehensive analysis of the faecal microbiome and metabolome of Strongyloides stercoralis infected volunteers from a non-endemic area. Sci Rep. 2018;8(1):1–13. pmid:29311619
- 60. Easton AV, Quiñones M, Vujkovic-Cvijin I, Oliveira RG, Kepha S, Odiere MR, et al. The impact of anthelmintic treatment on human gut microbiota based on cross-sectional and pre-and postdeworming comparisons in Western Kenya. mBio. 2019;10(2):e00519–19. pmid:31015324
- 61. Broadhurst MJ, Ardeshir A, Kanwar B, Mirpuri J, Gundra UM, Leung JM, et al. Therapeutic helminth infection of macaques with idiopathic chronic diarrhea alters the inflammatory signature and mucosal microbiota of the colon. PLOS Pathog. 2012;8(11). pmid:23166490
- 62. Foth BJ, Tsai IJ, Reid AJ, Bancroft AJ, Nichol S, Tracey A, et al. Whipworm genome and dual-species transcriptome analyses provide molecular insights into an intimate host-parasite interaction. Nat Genet. 2014;46(7):693–700. pmid:24929830
- 63. Jex AR, Nejsum P, Schwarz EM, Hu L, Young ND, Hall RS, et al. Genome and transcriptome of the porcine whipworm Trichuris suis. Nat Genet. 2014;46(7):701. pmid:24929829
- 64. Ramanan D, Bowcutt R, Lee SC, San Tang M, Kurtz ZD, Ding Y, et al. Helminth infection promotes colonization resistance via type 2 immunity. Science. 2016;352(6285):608–12. pmid:27080105
- 65. Mirza A, Forbes JD, Zhu F, Bernstein CN, Van Domselaar G, Graham M, et al. The multiple sclerosis gut microbiota: A systematic review. Mult Scler Relat Disord. 2019;37:101427. pmid:32172998
- 66. Pérez-Matute P, Íñiguez M, Villanueva-Millán MJ, Recio-Fernández E, Vázquez AM, Sánchez SC, et al. Short-term effects of direct-acting antiviral agents on inflammation and gut microbiota in hepatitis C-infected patients. Eur J Intern Med. 2019;67:47–58. pmid:31221551
- 67. Maizels RM, Yazdanbakhsh M. Immune regulation by helminth parasites: cellular and molecular mechanisms. Nat Rev Immunol. 2003;3(9):733–44. pmid:12949497
- 68. McSorley HJ, Hewitson JP, Maizels RM. Immunomodulation by helminth parasites: defining mechanisms and mediators. Int J Parasitol. 2013;43(3–4):301–10. pmid:23291463
- 69. Guerrant RL, DeBoer MD, Moore SR, Scharf RJ, Lima AA. The impoverished gut—a triple burden of diarrhoea, stunting and chronic disease. Nat Rev Gastroenterol Hepatol. 2013;10(4):220. pmid:23229327
- 70. Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM, et al. Towards complete and accurate reporting of studies of diagnostic accuracy: the STARD initiative. Radiology. 2003;226(1):24–8. pmid:12511664