https://orcid.org/0000-0001-6340-4852
Figures
Abstract
A working hypothesis is that less common species of Campylobacter (other than C. jejuni and C. coli) play a role in enteric disease among children in low resource settings and explain the gap between the detection of Campylobacter using culture and culture independent methods. “Candidatus Campylobacter infans” (C. infans), was recently detected in stool samples from children and hypothesized to play a role in Campylobacter epidemiology in low- and middle-income countries (LMIC). This study determined the prevalence of C. infans in symptomatic and asymptomatic stool samples from children living in Iquitos, Peru. Stool samples from 215 children with diarrhea and 50 stool samples from children without diarrhea under the age of two were evaluated using a multiplex qPCR assay to detect Campylobacter spp. (16S rRNA), Campylobacter jejuni / Campylobacter coli (cadF gene), C. infans (lpxA), and Shigella spp. (ipaH). C. infans was detected in 7.9% (17/215) symptomatic samples and 4.0% (2/50) asymptomatic samples. The association between diarrhea and the presence of these targets was evaluated using univariate logistic regressions. C. infans was not associated with diarrhea. Fifty-one percent (75/146) of Campylobacter positive fecal samples were negative for C. jejuni, C. coli, and C. infans via qPCR. Shotgun metagenomics confirmed the presence of C. infans among 13 out of 14 positive C. infans positive stool samples. C infans explained only 20.7% of the diagnostic gap in stools from children with diarrhea and 16.7% of the gap in children without diarrhea. We posit that poor cadF primer performance better explains the observed gap than the prevalence of atypical non-C. jejuni/coli species.
Author summary
A potentially new species of Campylobacter, “Candidatus Campylobacter infans” has been recently identified using culture independent diagnostic techniques. This study determined its prevalence using qPCR in diarrhea and non-diarrheal samples of children under the age of two, and confirmed results using shotgun metagenomics. The presence of “Candidatus Campylobacter infans” was not associated with diarrhea in this population.
Citation: Garcia Bardales PF, Schiaffino F, Huynh S, Paredes Olortegui M, Peñataro Yori P, Pinedo Vasquez T, et al. (2022) “Candidatus Campylobacter infans” detection is not associated with diarrhea in children under the age of 2 in Peru. PLoS Negl Trop Dis 16(10): e0010869. https://doi.org/10.1371/journal.pntd.0010869
Editor: Abiola Senok, Mohammed Bin Rashid University of Medicine and Health Sciences, UNITED ARAB EMIRATES
Received: May 16, 2022; Accepted: October 5, 2022; Published: October 17, 2022
This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Data Availability: Short read data are available at NCBI SRA and are associated with BioProject PRJNA834762. All other relveant data are within the manuscript and its supporting information files.
Funding: Funding for this study was provided by the Bill and Melinda Gates Foundation (OPP1066146 and OPP1152146 to MNK), the National Institutes of Health of the United States (R01AI158576 and R21AI163801 to MNK and CP; D43TW010913 to MNK). This research was also supported in part by USDA-ARS CRIS project 2030-42000-055-00D ( to CP). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: NO authors have competing interests.
Introduction
Campylobacteriosis is a leading cause of diarrhea, enteropathy and stunting among children living in poverty [1–3]. The isolation and genomic characterization of these pathogens are limited in low- and middle-income countries (LMIC) where the burden of disease is highest. This is partly a result of a larger proportion of cases diagnosed using nucleic acid-based techniques or ELISA, which is higher in low-income settings in comparison to high-income settings and in part secondary to limited capacity and funds to sequence genomes that are isolated in LMIC settings [4,5]. The diagnostic deficiency of culturing is likely due to imperfect sensitivity of traditional culture methods, even for common Campylobacter species such as C. jejuni and C. coli [6,7]. Additionally, uncommon species of Campylobacter that have been shown to be causative agents of enteric disease among children in low resource settings are diverse and fastidious in nature, requiring special atmospheric gas mixture and nutrient requirements for culturing. These uncommon species also require the creation and validation of new assays for nucleic acid-based methods. The material for both culture and nucleic acid-based methods are especially difficult to obtain in LMIC [8–11]. Among uncommon Campylobacter species, Campylobacter upsaliensis, Campylobacter hyointestinalis and a potential new species of Campylobacter, “Candidatus Campylobacter infans” (C. infans), have been identified in stool samples from children and hypothesized to play a role in the epidemiology of Campylobacter infection within highly endemic communities [8,9,12].
Campylobacter infans was first described in fecal samples of symptomatic and asymptomatic children under 1 year of age enrolled in the Global Enteric Multicenter Study (GEMS) [13]. This potential new species was identified from a single fecal sample associated with an infant experiencing prolonged diarrhea where Campylobacter spp. represented 83% of the fecal microbiome. Through assembly of shotgun metagenomic sequencing reads from this fecal sample, 75 contigs consisting of ~1.7 Mb were described as C. infans, which showed less than 75% similarity to the genomes of all other recognized Campylobacter species [12]. C. infans has been isolated once in a patient with chronic diarrhea living with HIV in Europe. In this instance, the detection of C. infans was not clearly associated with the chronic diarrhea reported, yet it represents the only report of its isolation [14,15]. Further query using both lpxA and atpA markers specific for C. infans in samples derived from the GEMS cohort identified the potential new Campylobacter species in 10% of fecal samples analyzed, all of which were positive for Campylobacter spp. by molecular diagnostics [12]. Because of this bias, the prevalence of this novel species in cases of diarrhea and in stools from asymptomatic children in a LMIC study, independent of Campylobacter status, has yet to be characterized.
The objective of this study was to compare the prevalence of C. infans in stool samples from children with acute diarrheal disease to stool samples from asymptomatic children living in a low resource community with established high rates of Campylobacter disease. Additionally, we set to determine if the presence of C. infans in these stool samples would explain the high discrepancy of the detection of Campylobacter between nucleic acid diagnostics and culture.
Methods
Ethics statement
Samples used in this study were collected as part of studies approved by the Institutional Review Boards of Asociacion Benefica Prisma (Lima, Peru) and Johns Hopkins Bloomberg School of Public Health. Parents or legal guardians of the participants of both studies provided a written consent to participate in the research and consented for future use of biological specimens that fell within the scope of this project.
Biological samples
Fecal samples were derived from children with diarrhea under two years of age seeking health care at local primary and tertiary care centers in Iquitos, Loreto, Peru. Stool samples from children who had not had diarrhea in the month prior to enrollment in a study of biomarkers of environmental enteropathy were analyzed as a population-based reference sample. This reference population lies within the population catchment area of recruitment for the study of acute diarrhea. All stools were collected between 2018–2021. Samples were collected from both groups of participants upon enrollment and stored at -70°C from case and reference populations.
To assess the hypothesis that C. infans may also be an oral bacterium, we evaluated its presence in saliva samples from children who had C. infans positive and C. infans negative fecal samples. Saliva samples from a random subset of the same participants were collected using Oracol S10 swabs (Malvern Medical Developments, Worcester, UK). Saliva samples were heated at 60°C for 30 minutes, centrifuged at 4000 rpm for 10 minutes and 500 μL of the supernatant were stored at -70°C until further processing
DNA extraction and qPCR
Fecal DNA was extracted from 0.2 grams of feces using the QIAamp DNA Stool Mini Kit (Qiagen, Carlsbald, CA), according to the manufacturer’s instructions. DNA was extracted from 200 μL of saliva using PureLink Genomic DNA mini kit (ThermoFisher Scientific, Massachusetts), according to the manufacturer’s instructions.
A negative control consisting of RNA and DNA free water was used for each extraction set. All samples were processed using a Taqman based multiplex assay to detect Campylobacter spp. (16S rRNA gene), Campylobacter jejuni / Campylobacter coli (cadF gene), C. infans (lpxA gene) and Shigella spp. (ipaH gene), using the primers and probes specified in Table 1. The final assay consisted of a 25 μL final reaction mixture with 12.5 μL of Environmental Master Mix (2X) (Applied Biosystems, Foster City, CA), forward and reverse primers (0.2 μM), probes (0.1 μM), 1 μL of DNA template and RNase and DNase free water (Ambion, Thermo Fisher Scientific, Waltham, MA, USA). The assays were performed on a QuantStudio 7 Flex (Applied Biosystems, Foster City, CA) using the following cycling conditions: 95°C for 10 minutes followed by 45 cycles of 95°C for 15 seconds and 60°C for 1 minutes. Custom manufactured double-stranded synthetic DNA fragments (gBlocks, Integrated DNA Technologies, Coralville, IA, USA) were used as positive controls (S1 Table). Negative template controls (RNase and DNase free water) were included in each amplification reaction. For quality control purposes, 10% of samples were run in duplicate.
Standard curves for each marker were prepared using 10-fold serial dilutions of synthetic positive controls (6.0 x 104–6.0 x 10°) gene copies/μL. A cut-off cycle threshold of 38 was used to determine positivity based on the assays limit of detection. Gene copy number of each qPCR marker per gram of feces were calculated and log(10) transformed for all fecal samples. Given that there are three copies of the 16S rRNA gene present in each Campylobacter genome, gene copy numbers for this target were adjusted accordingly. A single copy of the cadF gene (C.jejuni/ C.coli) or the lxpA gene (C. infans) is present per genome making this adjustment unnecessary for these gene targets.
Statistical analysis
Binary variables indicating the presence and absence of each qPCR target were created based on the established cycle threshold cut-off. A sample was positive if the detected cycle threshold was below the limit of detection. The presence and absence of Campylobacter spp., C. jejuni / C. coli, C. infans and Shigella spp. was tabulated. The association between diarrhea and the presence of Campylobacter spp., C. jejuni / C. coli, C. infans, and Shigella spp. was evaluated using univariate logistic regressions with 95% confidence intervals. The difference in the mean log(10) gene copy number per gram of symptomatic and asymptomatic fecal sample was assessed using an independent two-sample T-test. Statistical analysis and data visualization was performed in STATA 14 and R (version 4.1.1).
Shotgun metagenomic confirmation of C. infans
Sequencing of metagenomic DNA.
Shotgun metagenomics was conducted on DNA from a subset of fecal samples with positive qPCR signals for C. infans by sequencing on an Illumina MiSeq sequencer. The libraries were prepared using Illumina DNA Prep Tagmentation kit (Illumina, San Diego, CA), following the manufacturer’s instructions except for changes that increased library insert size to a median of 631 bp and a size range between ~375–1100 bp. This was done by decreasing the 1st and 2nd volume of Sample Purification Beads to 40 μl and 11 μl, respectively. The increase was necessary since standard manufacturer’s instructions resulted in inserts mostly below 300 bp. Libraries had a final elution of 10 μl Illumina resuspension buffer. Illumina-DNA/RNA UD Indexes Plate A, B, C and D dual index adapters were ordered from Integrated DNA Technologies (Coralville, IA) and used at 1 μM final concentration. Instead of pooling equal volume, individual libraries were quantified using the KAPA Library Quantification Kit (Roche), since we found qPCR to be a more accurate quantification than using equal volume. Libraries were quantified in 10 μl volume reactions and 90-s annealing/extension PCR, and then pooled and normalized to 4nM. Pooled libraries were re-quantified by ddPCR on a QX200 system (Bio-Rad, Hercules, CA), using the Illumina TruSeq ddPCR Library Quantification Kit and following the manufacturer’s protocols. Libraries were sequenced using a 2 x 250 bp paired end v2 reagent kit on a MiSeq instrument (Illumina) at 16 pM, following the manufacturer’s protocols. Short read data are available at NCBI SRA and are associated with BioProject PRJNA837236.
Detection of C. infans.
Detection of C. infans was performed using the reference assembler within Geneious Prime v2021.2.2 (Biomatters, Ltd., Auckland, New Zealand). Illumina paired sequence reads from fourteen metagenomic samples with the number of reads per sample ranging from 392,074 to 10,720,574 reads were assembled using the Geneious Mapper with low sensitivity settings (<10% mismatch between read and reference) to “Candidatus Campylobacter infans” strain 19S00001 chromosome (CP049075.1). The number of reads assembled from the different samples ranged from 0 and 68,948.
Detection of other campylobacter species.
Detection of Campylobacter species was also performed using the reference assembler within Geneious Prime v2021.2.2 (Biomatters, Ltd., Auckland, New Zealand). Illumina paired-end reads >100 nt generated from an individual fecal sample were simultaneously mapped to 28 Campylobacter chromosomes including: (1) Candidatus Campylobacter infans str. 19S00001 (CP049075.1), (2) C. avium str. LMG 24591 (CP022347.1), C. canadensis str. LMG 24001 (CP035946.1), C. coli str. 14983A (CP017025.1), C. coli plasmid pCC14983A-1 (CP017026.1), C. concisus str. ATCC 33237 (CP012541.1), C. corcagiensis str. LMG 27932 (CP053842.1), C. curvus str. ATCC 35224 (CP053826.1), C. fetus str. NCTC 10354 (CP043435.1), C. gracilis str. ATCC 33236 (CP012196.1), C. helveticus str. ATCC 51209 (CP020478.1), C. hepaticus str. HV10 (CP031611.1), C. hominis str. ATCC BAA-381 (CP000776.1), C. hyointestinalis str. CHY5 (CP053828.1), C. iguaniorum str. RM11343 (CP015577.1), C. insulaenigrae str. NCTC 12927 (CP007770.1), C. jejuni str. NCTC 11168 (AL111168.1), C. lanienae str. NCTC 13004 (CP015578.1), C. lari str. RM2100 (CP000932.1), C. mucosalis str. ATCC 43264 (CP053831.1), C. pinnipediorum str. RM17261 (CP012547.1), C. rectus str. ATCC 33238 (CP012543.1), C. showae str. ATCC 51146 (CP012544.1), C. sputorum str. LMG 7795 (CP043427.1), C. subantarcticus str. LMG 24377 (CP007773.1), C. upsaliensis str. NCTC 11541 (LR134372.1), C. ureolyticus str. RIGS 9880 (CP012195.1), C. volucrus str. LMG 24380 (CP043428.1), and C. vulpis str. 251/13 (CP041617). As described for the C. infans analysis, Geneious Mapper was run with low sensitivity settings, which only map reads with <10% mismatch between reads and references. When <50 reads mapped to a particular genome in a sample, all of these reads were analyzed via BLASTn of NCBI nr/nt database to determine that the reads matched only a single species at >95% identity.
BLASTn analysis of the cadF gene in a global dataset.
Nucleic acid diagnostics in global multisite studies including MALED and GEMS have historically used custom array cards for the detection of multiple enteropathogens [16]. Among these, the detection of C. jejuni and C. coli has been based on the utilization of the following primers and probe targeting the cadF gene: Fw: 5’- CTG CTA AAC CAT AGA AAT AAA ATT TCT CAC -3’, Rv: 5’- CTT TGA AGG TAA TTT AGA TAT GGA TAA TCG -3’, and probe: 5’- CAT TTT GAC GAT TTT TGG CTT GA -3’. These targets were selected using standard genomic material including Campylobacter coli ATCC 43473, Campylobacter jejuni ATCC 33291. We performed a BLASTn analysis of the qPCR cadF forward and reverse primers using over 3,000 publicly available Campylobacter genomes in the PubMLST database.
Results
Stool samples from 215 children with diarrhea as well as 50 randomly selected stool samples from children in a diarrhea free interval under the age of two were examined in this study. Among patients with diarrhea, 48% (103/215) were female and 52% were male (112/215). The median age of symptomatic children was 14 months (IQR: 9 months– 19 months). Among asymptomatic patients, 54% (27/50) were female and 46% were male (23/50). The median age of asymptomatic children was 7.5 months (IQR: 5 months– 13 months).
qPCR
Fecal samples were queried for Campylobacter spp., C. jejuni, C. coli, C. infans, and Shigella spp. using qPCR. The qPCR results (Table 2) indicated that overall, 55.1% (146/265) of fecal samples were positive for Campylobacter 16S rRNA. Of these, 35.6% (52/146) were positive for C. jejuni and/or C. coli, 13.0% (19/146) were positive for C. infans, and 51.4% (75/146) were negative for C. jejuni, C. coli, and C. infans.
Sixty percent (131/215) of the diarrheal samples were positive for Campylobacter spp. and approximately 23% (49/215) positive for C. jejuni /C. coli. All C. jejuni/ C. coli positive samples were positive for the 16S rRNA gene. The results from stool samples from asymptomatic children showed 30% (15/50) were positive for Campylobacter species and 6% (3/50) positive for C. jejuni / C. coli. C. infans was detected in 7.9% (17/215) symptomatic samples and 4.0% (2/50) asymptomatic samples. All C. infans positive samples were positive for the 16S rRNA gene. A single sample among diarrheal samples was positive for both the C. jejuni/ C. coli gene and C. infans by qPCR. Non-C. jejuni / C. coli and non-C. infans positive samples were identified in 30.2% (65/215) of symptomatic fecal samples and 20% (10/50) of asymptomatic fecal samples. C. infans explained 20.7% (17/82) of the diagnostic gap in samples from children with diarrhea and 16.7% (2/12) of the gap in children who had asymptomatic carriage.
Diarrhea was not associated with the presence of C. infans (OR: 2.06; 95% CI (0.46–9.22)). In comparison, diarrhea was significantly associated with the presence of Campylobacter spp. (OR: 3.64; 95% CI:1.87–7.07), C. jejuni / C. coli (OR: 4.62; 95% CI:1.38–15.51) and Shigella spp. (OR: 6.35; 95% CI: 1.48–27.14). (Table 2). The difference in the quantity of each qPCR target detected per gram of feces was not statistically different between symptomatic and asymptomatic fecal samples for C. jejuni, C. coli, or C. infans (S1 Fig).
DNA from twelve saliva samples associated with C. infans positive stools and twelve saliva samples associated with C. infans negative stools were further queried for Campylobacter spp., C. jejuni, C. coli, C. infans and Shigella spp. using qPCR. Four saliva samples were positive for Campylobacter spp. However, C. jejuni, C. coli, and C. infans were not detected in any saliva samples.
Metagenomics
The C. infans qPCR assay identified 19/265 (7.2%) samples with a Ct value less than 38. The results of qPCR for C. infans were validated for 14 stool samples using shotgun metagenomic sequencing. The Ct values for C. infans in these 14 samples ranged from 37.16–19.97, which is approximately 105−1010 gene copies/g of feces. The metagenomic sequence reads were mapped against the genomes of C. infans and 27 other Campylobacter species. C. infans sequencing reads were identified in 13 of the 14 samples using shotgun metagenomic sequencing (Table 3). All samples with a Ct value below 26.3 (>109 gene copies/g of feces) had more than 1,000 reads that mapped to the C. infans genome. One sample that had a Ct value of 34.23 (<106 gene copies/g of feces) had only 1 set of paired reads that mapped to the C. infans genome, and the sample with the highest Ct value of 37.16 (<105 gene copies/g of feces) had no reads. The number of reads matching to C. infans correlated with the quantity of C. infans calculated using the qPCR standard curve (r(12) = 0.75, p-value <0.05)
Shotgun metagenomic analysis identified reads for several Campylobacter species and showed many samples possessed multiple Campylobacter species (Table 3). Eight C. infans positive samples were co-infected with at least one non-C. jejuni / C. coli additional Campylobacter species identified from the metagenomic reference assemblies including 7 samples with C. concisus, one with C. upsaliensis, one with C. gracilis and one with C. hominis.
Despite C. jejuni and C. coli being scored as absent by qPCR (cadF) for 13 of the 14 samples, metagenomic analysis also identified four samples with C. jejuni and five with C. coli. This suggests that the cadF qPCR assay has a lower sensitivity than previously recognized. The qPCR cadF primers and probes were designed from a limited number of cadF sequences from C. jejuni and C. coli strains isolated in the US and/or Europe [4,17]. To determine the sequence diversity in the primer binding sites, we performed BLASTn analysis of the qPCR cadF forward and reverse primers (Table 1) against 3,076 C. jejuni and C. coli whole genome sequences (WGS) in the pubMLST database. There were 41% (1254/3076) of the strains that did not have 100% identity at one or both primer binding sites (S2 Table). Although most differences were only a single mismatch in a single primer, it is possible that the presence of multiple strains of C. jejuni and C. coli in a sample with differing mismatches may prevent proper amplification at a single cadF locus. It is also possible that Campylobacter jejuni and Campylobacter coli in LMIC may exhibit additional sequence variation in and around the cadF gene as more than 90% of the publicly available whole genomes on Campylobacter global genome databases are derived from the United States and Europe. Despite the low number of metagenomic reads that mapped to C. jejuni and C. coli, four reads in two samples mapped to the cadF gene. One read from sample 2678 included the cadF-Fw primer-binding site with no mismatches. Unfortunately, this fact does not provide a reason for the negative cadF qPCR result.
Discussion
There has been a consistent gap in detection and definitive identification of Campylobacter species in the clinical setting. To some extent this is a consequence of an inability to culture Campylobacters due to their fastidious nature. The acceptance of culture independent diagnostics (CIDT), such as ELISA and PCR, have led to some improvement in detection of Campylobacter from clinical samples. In fact, since 2013, Campylobacter has re-established as the leading cause of foodborne disease in the United States [18,19] and expanded its role as a major health issue worldwide. Despite the detection improvement of CIDT, detection gaps still exist due to the inability to identify certain Campylobacters due to the high variability of antigens targeted by ELISA, DNA sequence variation between species, and/or DNA variation within certain species at PCR primer/probe binding sites. The detection gap is especially pronounced in LMIC settings where culturing requirements including special gas mixtures are not easily obtainable and CIDT modifications can take months to develop and validate.
In the Peruvian Amazon, Campylobacter infections are endemic and have been detected using CIDT and culture-dependent genomic sequencing. Specifically, qPCR-based detection for Campylobacter species uses a specific, broadly reactive 16S rRNA gene target and for C. jejuni / C. coli uses a cadF gene target. In many cases, the qPCR results are validated by culture-dependent sequencing of C. jejuni and/or C. coli [20]. However, there are many samples that are positive for Campylobacter species (16S rRNA) while negative for C. jejuni / C. coli (cadF). Elimination of the other Campylobacters, as defined as Campylobacter 16S rRNA positive but cadF negative samples, would eliminate 24.9 percent of diarrhea cases in Peru, almost twice the attributable fraction of C. jejuni and C. coli [8]. Recently, a probable new species, C. infans was identified among infant stool samples from the GEMS study [12] and among patient samples in the Peruvian Amazon by metagenomic sequencing [21]. From these data, we modified the multiplex qPCR assay for detecting Campylobacter species and C. jejuni / C. coli to also detect C. infans using the lpxA gene.
The application of this multiplex qPCR assay was completed using a designed approach to include samples from health care attended cases of diarrhea as well as community-based controls. This study found the C. infans qPCR assay identified 19/265 (7.2%) samples with a Ct value less than 38, whereas shotgun metagenomic analysis of 14 of these samples, identified sequence reads that mapped to the C. infans genome in 13/14 (92.9%) samples. The single sample that had no reads had a Ct value of 37.16 and may indicate that a reduction of the positive Ct value is necessary for detection using shotgun metagenomics.
The validation of the C. infans qPCR assay using shotgun metagenomic sequencing not only demonstrated the presence of C. infans in positive samples but also demonstrated the presence of additional Campylobacter species that were not part of the qPCR assay. While 35.6% of the samples positive for Campylobacter species by qPCR were identified as positive for C. jejuni / C. coli in both the symptomatic and asymptomatic samples, the C. infans qPCR assay only increased the identification of the Campylobacter species to 48.6% of the samples. C. infans explained 20.2% of the diagnostic gap in samples from children with diarrhea and 16.7% of the gap in children who had asymptomatic carriage. Thus a large proportion of 16S rRNA gene positive samples were not attributed to either C. jejuni, C. coli or C. infans. This leaves a rather large qPCR diagnostic gap between 16S rRNA positive Campylobacter samples and specific species identification. Here, the shotgun metagenomic sequencing of C. infans qPCR positive samples identified additional Campylobacter species within these samples including C. jejuni, C. coli, C. concisus, C. gracilis, C. hominis, and C. upsaliensis. In our initial shotgun metagenomic study to examine samples that were qPCR positive for Campylobacter species but negative for C. jejuni / C. coli, we also identified C. jejuni, C. coli, C. concisus, C. upsaliensis, C. helveticus and C. curvus. It is possible that new qPCR assays should be developed or validated in highly endemic settings to account for these other Campylobacter species. Despite previous studies evaluating the co-occurrence of multiple Campylobacter species in the human gut using shotgun metagenomics [9,11], these have yet to report a prevalence of C. infans in fecal samples.
The presence of C. jejuni / C. coli in several of these samples suggests that the C. jejuni / C. coli cadF qPCR assay may miss a subset of C. jejuni / C. coli strains. In fact, we also identified these two species by shotgun metagenomics in numerous similar stool samples that were determined to be positive for Campylobacter species but negative for C. jejuni / C. coli by qPCR [21]. BLASTn analysis of the primer binding sites for the cadF product in over 3,000 C. jejuni / C. coli genomes demonstrated that approximately 40% of the strains had at least one mismatch.
The cadF gene is considered a virulence factor and core genomic feature, but virulence profiling studies of C. jejuni /C. coli strains including several from South America report the absence of the cadF gene within C. jejuni / C. coli strains using PCR based detection [22–24]. Furthermore, BLASTn analysis of WGS contigs at 90% identity level over 90% of the gene length can also result in failure to detect the cadF gene, yet the presence of the cadF gene in all complete genomes of C. jejuni / C. coli supports its current identity as a core gene. Therefore, it is less likely that the shotgun metagenomics analysis is identifying C. jejuni / C. coli that are cadF negative, but PCR-based assays can occasionally fail to detect it in certain stool samples. Further shotgun metagenomic analysis of samples that are Campylobacter positive by 16S rRNA qPCR but C. jejuni / C. coli negative by cadF qPCR will be required to clarify this point.
As mentioned above, C. concisus was identified in 7 of the 13 samples in which C. infans was confirmed by shotgun metagenomic sequencing. C. concisus is an anaerobic or microaerophilic Campylobacter species that has been predominantly isolated from the human oral cavity [25,26]. The presence of oral bacteria, such as C. concisus, in the infant gut, has been previously described as microbiome decompartmentalization of the gastrointestinal tract and is associated with childhood stunting [27]. As a result of these facts and due to the many co-infections of C. concisus and C. infans, we hypothesized that C. infans may also be an oral bacterium. Therefore, we performed qPCR in 24 randomly selected saliva samples associated with C. infans positive and C. infans negative fecal samples. Although this assay identified Campylobacter spp. in four saliva samples, this assay failed to identify C. infans in any saliva samples. Further studies are still needed to rule out the focalization of C. infans in the human gastrointestinal tract.
Based on the qPCR findings of symptomatic versus asymptomatic samples, certain types of infections are more likely to be associated with diarrhea. The odds ratios for C. jejuni / C. coli infections and Shigella infections demonstrate an association with diarrhea. However, in this study, the odds ratio for C. infans infections suggest that C. infans infection is not associated with diarrhea. Overall, our findings delineate C. infans as having a relatively low prevalence and no important role in the etiology of diarrheal illness in this LMIC population.
Conclusion
“Candidatus Campylobacter infans” was detected by CIDT in symptomatic and asymptomatic fecal samples from children in the Peruvian Amazon. Analysis determined that the presence of this potentially new species of Campylobacter was not associated with diarrhea in this population. Twenty-nine percent of Campylobacter qPCR positive fecal samples were not attributed to C. jejuni, C. coli or C. infans. Shotgun metagenomic analysis demonstrated the presence of other Campylobacter species and also suggested that qPCR detection of C. jejuni and/or C. coli using cadF failed to detect all samples that were positive for C. jejuni and/or C. coli. Further studies are needed to determine if the targeted section of the cadF gene that is widely used for the detection of C. jejuni and/or C. coli can be improved for the detection of strains present in LMICs.
Supporting information
S1 Table. gBlock Gene Fragments sequences used as positive controls.
https://doi.org/10.1371/journal.pntd.0010869.s001
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S2 Table. Highlighted Campylobacter isolates possess at least 1 mismatch at the forward or reverse primer binding sites.
https://doi.org/10.1371/journal.pntd.0010869.s002
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S1 Fig. Gene Copy Number (Log10) of qPCR Targets Per Gram of Feces in Symptomatic and Asymptomatic Fecal Samples.
Box and whiskers blot showing no statistical differences in the quantity of (Log10) of each qPCR target between symptomatic and asymptomatic samples. Quantitative data shown below:
https://doi.org/10.1371/journal.pntd.0010869.s003
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S1 Data. Demographic, specimen type and qPCR data of individual samples.
https://doi.org/10.1371/journal.pntd.0010869.s004
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References
- 1. Lee G, Pan W, Penataro Yori P, Paredes Olortegui M, Tilley D, Gregory M, et al. Symptomatic and asymptomatic Campylobacter infections associated with reduced growth in Peruvian children. PLoS Negl Trop Dis. 2013;7(1):e2036. pmid:23383356; PubMed Central PMCID: PMC3561130.
- 2. Lee G, Paredes Olortegui M, Penataro Yori P, Black RE, Caulfield L, Banda Chavez C, et al. Effects of Shigella-, Campylobacter- and ETEC-associated diarrhea on childhood growth. Pediatr Infect Dis J. 2014;33(10):1004–9. pmid:25361185.
- 3. Amour C, Gratz J, Mduma E, Svensen E, Rogawski ET, McGrath M, et al. Epidemiology and Impact of Campylobacter Infection in Children in 8 Low-Resource Settings: Results From the MAL-ED Study. Clin Infect Dis. 2016;63(9):1171–9. pmid:27501842.
- 4. Platts-Mills JA, Liu J, Gratz J, Mduma E, Amour C, Swai N, et al. Detection of Campylobacter in stool and determination of significance by culture, enzyme immunoassay, and PCR in developing countries. J Clin Microbiol. 2014;52(4):1074–80. pmid:24452175; PubMed Central PMCID: PMC3993515.
- 5. Buss SN, Leber A, Chapin K, Fey PD, Bankowski MJ, Jones MK, et al. Multicenter evaluation of the BioFire FilmArray gastrointestinal panel for etiologic diagnosis of infectious gastroenteritis. J Clin Microbiol. 2015;53(3):915–25. Epub 20150114. pmid:25588652; PubMed Central PMCID: PMC4390666.
- 6. Buss JE, Cresse M, Doyle S, Buchan BW, Craft DW, Young S. Campylobacter culture fails to correctly detect Campylobacter in 30% of positive patient stool specimens compared to non-cultural methods. Eur J Clin Microbiol Infect Dis. 2019;38(6):1087–93. pmid:30783889.
- 7. Fitzgerald C, Patrick M, Gonzalez A, Akin J, Polage CR, Wymore K, et al. Multicenter Evaluation of Clinical Diagnostic Methods for Detection and Isolation of Campylobacter spp. from Stool. J Clin Microbiol. 2016;54(5):1209–15. Epub 20160309. pmid:26962088; PubMed Central PMCID: PMC4844741.
- 8. Francois R, Yori PP, Rouhani S, Siguas Salas M, Paredes Olortegui M, Rengifo Trigoso D, et al. The other Campylobacters: Not innocent bystanders in endemic diarrhea and dysentery in children in low-income settings. PLoS Negl Trop Dis. 2018;12(2):e0006200. pmid:29415075.
- 9. Chen D, McKune SL, Singh N, Yousuf Hassen J, Gebreyes W, Manary MJ, et al. Campylobacter Colonization, Environmental Enteric Dysfunction, Stunting, and Associated Risk Factors Among Young Children in Rural Ethiopia: A Cross-Sectional Study From the Campylobacter Genomics and Environmental Enteric Dysfunction (CAGED) Project. Front Public Health. 2020;8:615793. Epub 20210121. pmid:33553097; PubMed Central PMCID: PMC7862945.
- 10. St Jean DT, Herrera R, Perez C, Gutierrez L, Vielot NA, Gonzalez F, et al. Clinical Characteristics, Risk Factors, and Population Attributable Fraction for Campylobacteriosis in a Nicaraguan Birth Cohort. Am J Trop Med Hyg. 2021;104(4):1215–21. Epub 20210125. pmid:33534747; PubMed Central PMCID: PMC8045609.
- 11. Terefe Y, Deblais L, Ghanem M, Helmy YA, Mummed B, Chen D, et al. Co-occurrence of Campylobacter Species in Children From Eastern Ethiopia, and Their Association With Environmental Enteric Dysfunction, Diarrhea, and Host Microbiome. Front Public Health. 2020;8:99. Epub 20200415. pmid:32351922; PubMed Central PMCID: PMC7174729.
- 12. Bian X, Garber JM, Cooper KK, Huynh S, Jones J, Mills MK, et al. Campylobacter Abundance in Breastfed Infants and Identification of a New Species in the Global Enterics Multicenter Study. mSphere. 2020;5(1). pmid:31941810
- 13. Levine MM, Kotloff KL, Nataro JP, Muhsen K. The Global Enteric Multicenter Study (GEMS): impetus, rationale, and genesis. Clinical infectious diseases: an official publication of the Infectious Diseases Society of America. 2012;55 Suppl 4(Suppl 4):S215–S24. pmid:23169934.
- 14. Flipse J, Duim B, Wallinga JA, De Wijkerslooth LRH, Graaf-Van Bloois LVD, Timmerman AJ, et al. A Case of Persistent Diarrhea in a Man with the Molecular Detection of Various Campylobacter species and the First Isolation of candidatus Campylobacter infans. Pathogens. 2020;9(12):1003. pmid:33265947
- 15. Duim B, van der Graaf-van Bloois L, Timmerman A, Wagenaar JA, Flipse J, Wallinga J, et al. Complete Genome Sequence of a Clinical Campylobacter Isolate Identical to a Novel Campylobacter Species. Microbiol Resour Announc. 2021;10(7). Epub 20210218. pmid:33602730; PubMed Central PMCID: PMC7892663.
- 16. Liu J, Gratz J, Amour C, Nshama R, Walongo T, Maro A, et al. Optimization of Quantitative PCR Methods for Enteropathogen Detection. PLoS One. 2016;11(6):e0158199. Epub 20160623. pmid:27336160; PubMed Central PMCID: PMC4918952.
- 17. Cunningham SA, Sloan LM, Nyre LM, Vetter EA, Mandrekar J, Patel R. Three-Hour Molecular Detection of Campylobacter, Salmonella, Yersinia, and Shigella Species in Feces with Accuracy as High as That of Culture. Journal of Clinical Microbiology. 2010;48(10):2929–33.
- 18. Kaakoush NO, Castano-Rodriguez N, Mitchell HM, Man SM. Global Epidemiology of Campylobacter Infection. Clin Microbiol Rev. 2015;28(3):687–720. Epub 2015/06/13. pmid:26062576; PubMed Central PMCID: PMC4462680.
- 19. Scallan E, Hoekstra RM, Angulo FJ, Tauxe RV, Widdowson MA, Roy SL, et al. Foodborne illness acquired in the United States—major pathogens. Emerg Infect Dis. 2011;17(1):7–15. pmid:21192848; PubMed Central PMCID: PMC3375761.
- 20. Pascoe B, Schiaffino F, Murray S, Meric G, Bayliss SC, Hitchings MD, et al. Genomic epidemiology of Campylobacter jejuni associated with asymptomatic pediatric infection in the Peruvian Amazon. PLoS Negl Trop Dis. 2020;14(8):e0008533. Epub 2020/08/11. pmid:32776937; PubMed Central PMCID: PMC7440661.
- 21. Parker CT, Schiaffino F, Huynh S, Paredes Olortegui M, Peñataro Yori P, Garcia Bardales PF, Pinedo Vasquez T, Curico Huansi GE, Manzanares Villanueva K, Shapiama Lopez WV, Cooper KK, Kosek MN. Shotgun metagenomics of fecal samples from children in Peru reveals frequent complex co-infections with multiple Campylobacter species. PLoS Negl Trop Dis. 2022 Oct;16(10):e0010815.
- 22. Lluque A, Riveros M, Prada A, Ochoa TJ, Ruiz J. Virulence and Antimicrobial Resistance in Campylobacter spp. from a Peruvian Pediatric Cohort. Scientifica (Cairo). 2017;2017:7848926. pmid:29130018; PubMed Central PMCID: PMC5654289.
- 23. de Melo RT, Dumont CF, Braz RF, Monteiro GP, Takeuchi MG, Lourenzatto ECA, et al. Genotypical Relationship Between Human and Poultry Strains of Campylobacter jejuni. Curr Microbiol. 2021;78(8):2980–8. Epub 20210605. pmid:34089354.
- 24. Rossler E, Olivero C, Soto LP, Frizzo LS, Zimmermann J, Rosmini MR, et al. Prevalence, genotypic diversity and detection of virulence genes in thermotolerant Campylobacter at different stages of the poultry meat supply chain. Int J Food Microbiol. 2020;326:108641. Epub 20200425. pmid:32371295.
- 25. Petersen RF, Harrington CS, Kortegaard HE, On SL. A PCR-DGGE method for detection and identification of Campylobacter, Helicobacter, Arcobacter and related Epsilobacteria and its application to saliva samples from humans and domestic pets. J Appl Microbiol. 2007;103(6):2601–15. Epub 20071003. pmid:17916160.
- 26. Zhang L, Budiman V, Day AS, Mitchell H, Lemberg DA, Riordan SM, et al. Isolation and detection of Campylobacter concisus from saliva of healthy individuals and patients with inflammatory bowel disease. J Clin Microbiol. 2010;48(8):2965–7. Epub 20100602. pmid:20519479; PubMed Central PMCID: PMC2916630.
- 27. Vonaesch P, Morien E, Andrianonimiadana L, Sanke H, Mbecko JR, Huus KE, et al. Stunted childhood growth is associated with decompartmentalization of the gastrointestinal tract and overgrowth of oropharyngeal taxa. Proc Natl Acad Sci U S A. 2018;115(36):E8489–E98. Epub 2018/08/22. pmid:30126990; PubMed Central PMCID: PMC6130352.
- 28. Vu DT, Sethabutr O, Von Seidlein L, Tran VT, Do GC, Bui TC, et al. Detection of Shigella by a PCR assay targeting the ipaH gene suggests increased prevalence of shigellosis in Nha Trang, Vietnam. J Clin Microbiol. 2004;42(5):2031–5. Epub 2004/05/08. pmid:15131166; PubMed Central PMCID: PMC404673.