Abstract
Background
The prevalence of enteric pathogens in hospital settings within the surrounding environment has been extensively studied and documented. However, there is a lack of knowledge regarding the presence of these pathogens in the general healthy community. Asymptomatic carriers may unknowingly harbor these pathogens and later develop infections or transmit them to vulnerable individuals. Therefore, our objective is to identify gastrointestinal pathogens associated with fecal carriage among healthy adults in different industries.
Methods
This cross-sectional study was conducted over one year to investigate the carriage of gastrointestinal pathogens among healthy adult staff at local restaurants and community hospitals. Stool samples were analyzed using a multiplex PCR panel to determine the pathogen detection rate and the incidence of co-carriage, with a focus on seasonal variations and differences between the two industry types.
Results
A total of 204 fecal samples were collected from a healthy population, with 147 from cater-related industries and 57 from non-cater-related industries, across all four seasons. Of these, 137 (67.2%) tested positive for pathogens. The most common pathogen was EAEC at 35.8%, followed by EPEC at 23.0%, P. shigelloides at 9.8%, C. difficile at 5.4%, ETEC at 4.4%, and both V. parahaemolyticus and Salmonella at 2.0% each. Co-carriages with two pathogens were found in 26 samples, and with three pathogens in 5 samples, with EPEC and ETEC being the most frequent combination. EAEC, EPEC, and single pathogen carriage were most prevalent in the elderly, while P. shigelloides and multiple pathogen carriages were highest in middle-aged individuals. The pathogens most commonly identified, such as EAEC, EPEC, ETEC, single and dual pathogen carriages were all found to be present in a positive state over a period of four months. C. difficile was detected exclusively in samples from catering-related industries.
Conclusions
EAEC, EPEC, P. shigelloides and C. difficile were most common enteric pathogens in single carriage while former three of which predominated in co-carriages. The exclusive colonization of C. difficile in cater-related industries may enhance its transmission. Middle-aged individuals exhibited a higher susceptibility to co-pathogen carriage, although positive samples were distributed evenly across all age groups. The incidence of pathogen carriage was associated with seasonal variations and temperature fluctuations.
Keywords: Healthy populations, Colonizing pathogen, Gastrointestinal panel, Rapid diagnostic assay
Introduction
The human microbiome, consisting predominantly of bacteria, viruses, and yeast, constitutes a complex ecosystem that is distributed throughout various anatomical regions of the body [1, 2]. The gastrointestinal (GI) tract, in particular, harbors highly diverse and abundant microbial populations, which possess a wide range of genes encoding enzymes and metabolites [3]. Variations in regional lifestyles and environmental factors contribute to distinct prevalence patterns of intestinal colonizing bacteria among healthy populations. The presence of drug-resistant bacteria within the healthy populations of a community is a significant concern, as these bacteria can be transmitted between individuals and the environment, leading to the development of infectious diseases. Individuals employed in the catering industry are particularly at risk of spreading GI pathogens [4, 5]. Therefore, it is crucial to have a comprehensive understanding of the epidemiological characteristics and pathogen spectrum within a specific locality in order to implement effective strategies for the prevention and control of GI infectious diseases, as well as to establish a scientific foundation for appropriate clinical drug utilization.
The utilization of polymerase chain reaction (PCR) technology has evolved from its initial applications in genome projects and forensics to facilitate the rapid diagnosis of infectious diseases. Several multiplex PCR-based gastrointestinal panels are now commercially available for the rapid detection of pathogens responsible for infectious diarrhea. These platforms typically employ cartridge-based, random-access systems capable of simultaneously detecting multiple bacterial, viral, and parasitic targets within a few hours. The pathogens targeted by such panels are primarily community-acquired and encompass various Escherichia coli pathotypes, among other enteric pathogens. Utilizing these comprehensive diagnostic tools, results can be obtained within approximately 90 min following sample processing in the laboratory.
This study conducted GI panels testing on fecal samples obtained from healthy individuals residing in communities in Ningbo city over the course of 2023. The primary objective was to evaluate the presence of GI pathogens within these communities, while also creating a comprehensive local database of colonizing intestinal flora as well as the prevalence trend in season and age. The findings of this study aim to provide a scientific foundation for the judicious utilization of antimicrobial agents, assessment of resistance risks, and strategies for disease prevention and control.
Methods
Sample collection
A total of 204 fecal samples were collected from 204 healthy individuals in different age groups and industries throughout March, June, September and November in 2023 with equal representation of males and females. The target sample size was initially set at 200, based on an estimated pathogen detection rate and statistical power considerations. During the actual collection phase, 246 samples were obtained. These samples then underwent strict quality control screening based on pre-defined criteria, including sample volume, storage conditions, personal information, and adherence to inclusion criteria. After this screening process, 204 qualified samples were retained for final analysis. Each participants provided one fecal sample stored in a disposal fecal tube which is a clean, sterile, and dry containers without any transport or preservation medium. The study participants were divided into three age groups: a youth group aged 16–30 years (55 participants), a middle-aged group aged 31–50 years (74 participants) and an elderly group aged 51–70 years (75 participants). Metabolism disorder such as hypertension and diabetes were exclude. In the meantime all subjects were without diarrhea, cold, fever, runny nose, cough, vaccine and antibiotics. Verbal informed consent has been provided by the participants.
Multiple-pathogen detection
Gastrointestinal (GI) panels designed by Tianlong technology company were conducted as per the manufacturer’s instructions, with internal control and positive control for nucleic acid extraction and PCR performance. A valid run was confirmed if both controls passed. The panels were run on the Panall 8000 platform (Tianlong technology) which completed DNA extraction, qPCR amplication and results analysis with a streamlined sample-in-result-out design for about 90 min, detecting 18 pathogens including Enteroaggregative E.coli (EAEC), Enteropathogenic E.coli (EPEC), Enterotoxigenic E.coli (ETEC), Enteroinvasive E.coli (EIEC), Enterohemorrhagic E.coli (EHEC), Shigalle spp., Aeromonas hydrophila (A.hydrophila), Vibrio cholerae (V. cholerae), Vibrio parahaemolyticus (V. parahaemolyticus), Salmonella, Clostridioides difficile (C. difficile), Vibrio fluvialis (V. fluvialis), Cronobacter sakazakii, Plesiomonas shigelloides (P. shigelloides), Campylobacter fetus (C. fetus), Campylobacter jejuni (C. jejuni), Campylobacter coli (C. coli), Yersinia enterocolitica.
A parallel study was conducted using an additional GI panel (XABT, China). Nucleic acids were extracted from 200 mg fecal samples with pre-treatment utilizing the Qiagen QIAcube HT system following the manufacturer’s instructions. Quantitative PCR (qPCR) amplifications were carried out in accordance with the manufacturer’s protocol. The samples were analyzed utilizing both the gastrointestinal panels on the Panall 8000 platform (Tianlong Technology) and the AB Q5 system.
Traditional stool culture
All tests in which Shigella and Salmonella were identified in stool samples were promptly subjected to stool culture. Following TTB enrichment and culture on SS agar, suspect colonies of Salmonella and Shigella were identified by MALDI-TOF mass spectrometry (Ewai incorporation) and subsequently serotyped using diagnostic serum (SSI, Denmark).
Data analysis
All data were performed by GraphPad Prism software. The criteria of statistical significance was set as a p-value < 0.05 or adjust p-value < 0.05. The adjust p value was calculated by the Benjamini-Hochberg correction and Chi-square test was used to analyze the categorical variables.
All figures were generated with the R software (http://www.R-project.org; Version 4.2.1). The criteria of statistical significance was set as a p-value < 0.05 or adjust p-value < 0.05. The parametric test of Student’s t-test and non-parametric of Mann–Whitney U test were performed to compare the differences between two groups. The adjust p value was calculated by the Benjamini-Hochberg correction and Chi-square test was used to analyze the categorical variables.
Results
Distribution of enteric pathogens in the study population
A total of 204 stool specimens were collected for GI testing, comprising 147 samples from cater-related industries such as local restaurants, and 57 samples from non-cater-related industries such as community hospitals. Data down below were double confirmed by two methods (panall 8000 and qPCR). Carriage rates were observed to be numerically higher in the elderly group (73.3%) and among females (68.4%) than in males (66.0%). The incidence of carriages in non-cater-related industries (83.0%) was observed to be higher than in cater-related industries (63.7%), as shown in Table 1.
Table 1.
Display of the distribution and prevalence of positive numbers in fecal samples collected throughout the year 2023 (Total number n = 204)
| Features | Number | Positive number (rate%) |
|---|---|---|
| Males | 106 | 70 (66.0%) |
| Females | 98 | 67 (68.4%) |
| March | 68 | 36 (52.9%) |
| June | 52 | 29 (55.8%) |
| September | 43 | 35(81.4%) |
| November | 41 | 37 (90.2%) |
| Youth group (16–30 years) | 55 | 30 (54.5%) |
| Middle-aged group (31–50 years) | 74 | 52 (70.3%) |
| Elderly group (51–65 years) | 75 | 55 (73.3%) |
| Cater-related industries | 147 | 98 (63.7%) |
| Non-cater-related industries | 57 | 39 (83.0%) |
Note: The positive numbers indicate the quantity of fecal samples that tested positive for one or more pathogens across various characteristics. The numbers in parentheses represent the rate of positive samples
GI tests identified at least one pathogen in 137 samples (67.2%). The most commonly identified pathogen on the panel was EAEC at 35.8% (73/204), followed by EPEC at 23.0% (47/204), P. shigelloides at 9.8% (20/204), C. difficile at 5.4% (11/204), ETEC at 4.4% (9/204), V. parahaemolyticus at 3.0% (6/204), and Salmonella at 2.0% (4/204) (Table 3). Furthermore, four Salmonella isolates were obtained, with three identified as S. kentucky and one as S. give. Drug sensitivity testing revealed that three S. kentucky strains exhibited resistance to nalidixic acid, ciprofloxacin, and ampicilin. Additionally, S. give demonstrated resistance to nalidixic acid and ampicilin, but was found to be intermediate to ciprofloxacin as per Clinical and Laboratory Standards Institute guidelines (data not presented).
Table 3.
Distribution of pathogens and co-carriages in 137 positive samples by gender and age
| Pathogen / Carriage type | Total | Gender | Age group | |||
|---|---|---|---|---|---|---|
| n(%)1 | Male (n = 1.6) |
Female (n = 98) |
Youth (18–30 y, n = 55) |
Middle-age (31–50 y, n = 74) |
Elderly (51–70 y, n = 75) |
|
| Positive samples | 137 (67.2) | 70 (66.0) | 67 (68.4) | 30 (54.5) | 52 (70.3) | 55 (73.3) |
| EAEC | 73 (35.8) | 33 (31.1) | 40 (40.8) | 16 (29.1) | 27 (36.5) | 30 (40.0) |
| EPEC | 47 (23.0) | 18 (17.0) | 29 (29.6) | 10 (18.2) | 18 (24.3) | 19 (25.3) |
| P. shigelloides | 20 (9.8) | 11 (10.4) | 9 (9.2) | 7 (12.7) | 12 (16.2) | 1 (1.3) |
| Single carriage | 106 (52.0) | 50 (47.2) | 56 (57.1) | 24 (43.6) | 38 (51.4) | 44 (58.7) |
|
Co-carriages (2 pathogens) |
26 (12.7) | 16 (15.1) | 10 (10.2) | 5 (9.1) | 10 (13.5) | 11 (14.7) |
|
Co-carriages (3 pathogens) |
5 (2.5) | 4 (3.8) | 1 (1.0) | 1 (1.8) | 4 (5.4) | 0 (0.0) |
Notes: 1Percentages are calculated based on the total population (N = 204) for the Total column, and based on subgroup sizes for gender and age columns
Table 2 displays the distribution of detected organisms. Co-carriages involving two pathogens were identified in 26 out of 137 positive samples, while co-carriages with three pathogens were observed in 5 samples (Table 2). Among the co-carriages, the most commonly identified pathogens were EPEC (61.3% [19/31]), EAEC (48.4% [15/31]), and P. shigelloides (38.7% [12/31]). The combination of EPEC and ETEC occurred most frequently followed by EPEC + P. shigelloides, EPEC+EAEC and EPEC + P. shigelloides.
Table 2.
Different combinations of 31 co-carriages detected in 137 positive stool samples from healthy populations throughout the year of 2023
| Two Pathogens | Number |
|---|---|
| EPEC+ETEC | 5 |
| EAEC + P. shigelloides | 3 |
| EPEC+EAEC | 3 |
| EPEC + P. shigelloides | 3 |
| EPEC+Salmonella | 2 |
| EAEC + C. difficile | 2 |
| EAEC+ETEC | 2 |
| EAEC+Salmonella | 1 |
| EPEC + V. parahaemolyticus | 1 |
| EPEC + C. difficile | 1 |
| C. difficile + P. shigelloides | 1 |
| C. difficile + V. parahaemolyticus | 1 |
| ETEC + P. shigelloides | 1 |
| Total | 26 |
| Three pathogens | Number |
|---|---|
| EPEC+EAEC + C. difficile | 1 |
| EPEC+EAEC+Salmonella | 1 |
| EPEC+EAEC + P. shigelloides | 1 |
| EPEC+ETEC + P. shigelloides | 1 |
| EPEC + V. parahaemolyticus + P. shigelloides | 1 |
| Total | 5 |
Note: The numbers indicate the quantity of fecal samples that tested positive for multiple pathogens
Distribution of enteric pathogens in age and gender
Regarding the distribution of positive samples by age, 54.5% (30/55) were from the youth group aged 16–30 years, 70.3% (52/74) were from the middle-aged group aged 31–50 years, and 73.3% (55/75) were from elderly group aged 51–70 years (Table 1). Among the 137 positive samples, the positive rates of the most common agent EAEC were 29.1% (16/55), 36.5% (27/74), and 40.0% (30/75) for the youth, middle-aged and elderly groups respectively. Our study investigated the prevalence of co-carriages across different age groups and found that 9.1% of individuals in the youth group exhibited co-carriages with two pathogens. This percentage increased to its highest in the elderly group, reaching 14.7%, which also had the highest percentage of single carriage at 58.7%. Furthermore, co-carriages involving three pathogens were identified in four individuals from the middle-aged and male group, compared to only one individual from the youth and female group (Table 3). Notably, it was unexpected to find that the prevalence of certain pathogens, such as EPEC, P. shigelloides, and co-carriages with two or three pathogens, was generally higher in males than in females, whereas the opposite trend was observed for EAEC and single carriage (Table 3).
Distribution of enteric pathogens in seasonality
The monthly positive detection rates for March, June, September, and November were 52.9%, 55.8%, 81.4%, and up to 90.2%, respectively (Table 1). The seasonality distribution of all pathogens was systematically analyzed in Fig. 1. The most common pathogens EAEC, EPEC and ETEC were found to predominate in four specific months, with EPEC exhibiting the highest detection rates in September and the other pathogens in November (Fig. 1A, B and C). EHEC was only found in November (Fig. 1D). C. difficile and Salmonella exhibited same trend which decreased from March to September, disappearing in November (Fig. 1E and H). The positive rates of P. shigelloides and V. parahaemolyticus were higest both in September, lowest in March while detected none in November (Fig. 1F and G).The rate of single pathogen carriage increased from June to November (Fig. 1I), whereas double pathogen carriage was highest in March (Fig. 1J), and triple pathogen carriage peaked in September (Fig. 1K).
Fig. 1.
Seasonly distribution of most frequently detected pathogens in stool samples from 204 adults in healthy populations. Real lines stand for the number of positive samples while dotted lines stand for the rate of positive samples. A: EAEC; B: EPEC; C: ETEC; D:EHEC; E: C. difficile; F: P. shigelloides; G: V. parahaemolyticus; H: Salmonella; I: single carriage; J: double carriages; K: triple carriages
Distribution of enteric pathogens in non/cater-related industries
Upon comparing the two groups within the healthy population, the results indicate statistically significant differences in the presence of C. difficile and P. shigelloides (P < 0.05), as demonstrated in Table 4. Notably, C. difficile was detected exclusively in samples from catering-related industries. Interestingly, the prevalence of P. shigelloides was higher in samples from non-catering-related industries compared to those from catering-related industries. The prevalence of EAEC, EHEC, Salmonella and single carriage was elevated in industries associated with catering, with EHEC and Salmonella exclusively identified in these sectors. Conversely, the occurrence of EPEC, ETEC, V. parahaemolyticus, and co-carriages (two and three pathogens) was higher in industries not related to catering; however, these differences were not statistically significant.
Table 4.
The prevalence of pathogens occurring to non/cater-related industries
| Pathogen/ Carriage type | Total (N = 204) |
Non-catering industry (n = 57) |
Catering industry (n = 147) |
P value1 |
|---|---|---|---|---|
| EAEC | 73 (35.8) | 17 (29.8) | 56 (38.1) | 0.346 |
| EPEC | 47 (23.0) | 16 (28.1) | 31 (21.1) | 0.380 |
| ETEC | 9 (4.4) | 4 (7.0) | 5 (3.4) | 0.269 |
| EHEC | 2 (1.0) | 0 (0.0) | 2 (1.4) | >0.999 |
| C.difficile | 11 (5.4) | 0 (0.0) | 11 (7.5) | 0.037 |
| P.shigelloides | 20 (9.8) | 14 (24.6) | 6 (4.1) | <0.001 |
| V. parahaemolyticus | 6 (2.9) | 3 (5.3) | 3 (2.0) | 0.352 |
| Salmonella | 4 (2.0) | 0 (0.00) | 4 (2.7) | 0.578 |
| Single carriage | 106 (52.0) | 26 (45.6) | 80 (54.4) | 0.330 |
| Co-carriages (2 pathogens) | 26 (12.7) | 10 (17.5) | 16 (10.9) | 0.296 |
| Co-carriages (3 pathogens) | 5 (2.5) | 3 (5.3) | 2 (1.4) | 0.1342 |
Note: Data are presented as n (%). P values were calculated using 1Pearson’s chi-square test, except where indicated. 2Fisher’s exact test. Values in bold indicate statistical significance (p < 0.05)
Discussion
This study was aimed to reveal the epidemiology of pathogen colonized in 204 healthy people who underwent stool test by GI panel in the course of 2023.
Molecular detection have greatly increased the sensitivity of pathogen detection as well as expanding the involvement as colonized agents [6], which cannot yield an isolate but can find nucleic acids from non-viable microorganism. Conventional detection includes nucleic acids extraction and PCR performance which may take several hours to get the results sometimes may manifesting negative outcomes. PCR assays not only present limitation in finding the true etiologic agent in case of multiple detection which need to further conduct culture isolation and antibiotics sensitivity experiments but greatly rely on laboratory examiners’ judgement and technique.
GI panels has been used in our study with the goal of limiting the conventional methods in light of its high sensitivity and reproducibility [7, 8]. In our study population, 67.2% of the samples tested positive, a finding that is consistent with previous reports [7, 8]. GI panel detected a higher frequency of single carriage (52.0%) caused by bacteria, which is consistent with literature data [9]. Of the positive samples, the most prevalent organism was EAEC (35.8%), followed by EPEC (23.0%) and P. shigelloides (9.8%) (Table 4), C. difficile (5.4%), ETEC (4.4%), V. parahaemolyticus (2.9%), Salmonella (2.0%) (Fig. 1A).
Diarrhoeagenic Escherichia coli (DEC) can be classified into five distinct pathotypes, including ETEC, EAEC, EPEC, EIEC and EHEC, based on the presence of specific virulence markers located on plasmids and/or chromosomal islands. ETEC, EAEC, and EPEC have been identified as causative agents of diarrhoeal illness in young children residing in low to middle income countries [10]. EAEC and EPEC were identified as the most commonly detected pathogens which is coherent to our results, although their precise etiological roles remain uncertain [11, 12]. Murphy et al.. determined that EPEC was the predominant analyte in patients with diarrhea [13]. Research conducted by Vu Thuy Duong [14] et al.. utilizing surveillance data from children in Vietnam indicated that EPEC was the predominant pathogen, followed by EAEC. Another study found that EAEC was more frequently detected than EPEC in healthy children under 10 years of age, with children under 2 years of age being particularly susceptible to DEC infection [15].
P. shigelloides, a Gram-negative enterobacterium, is the second most prevalent pathogen found in various freshwater sources, including streams and lakes, as well as in human, animal, and environmental samples [16, 17]. Despite its widespread distribution, P. shigelloides has received less attention compared to other common foodborne pathogens such as Salmonella, V. parahaemolyticus, and diarrheal E. coli [18]. The low detection rate of P. shigelloides in sentinel hospitals suggests that this pathogen may be easily overlooked in clinical settings [19]. Greenlees [20] et al.. demonstrated a correlation between increased reported cases of P. shigelloides during warmer months with elevated water temperatures, which promote their proliferation through sewage contamination. In our city, spring (March to May) sees temperatures rise from 10 °C to 20 °C and increased rainfall and humidity. Summer (June to August) is the hottest and wettest time, with temperatures over 28 °C and frequent rain, including heavy downpours from the Meiyu front and occasional typhoons. Autumn (September to October) is the most pleasant season, with comfortable temperatures and less rain. Our study similarly found a peak detection rate of P. shigelloide in September, consistent with Greenlees’ findings. Risk factors for exposure to P. shigelloides include contact with contaminated food, foreign travel [21], immunocompromised individuals [22], low socioeconomic status, and poor hygiene practices [23]. Our study revealed that individuals in non-cater-related industries (29.8%) exhibited a higher susceptibility to colonization by P. shigelloides compared to those in cater industries (3.8%). This finding is challenging to interpret, particularly considering that individuals in cater industries are more likely to come into contact with contaminated food. Further investigation is warranted to determine if the virulence genes present in the gut microbiota of healthy individuals differ from those found in patients with diarrhea.
C. difficile is a Gram-positive anaerobic spore-forming bacillus known to induce toxin-mediated infection and inflammation in the colon. The disruption of the physiological intestinal microbiome by antibiotics is a common predisposing factor for C. difficile infection [24]. The potential role of C. difficile colonized patients as sources of transmission has been a subject of interest. Our data analysis revealed a predominance of C. difficile in the months of March and June, with a higher prevalence observed in March (14.7%) compared to June (1.9%). The relatively low temperature and humidity in September and October, as compared to March and June, may affect the proliferation rate. It is noteworthy that all identified carriers of C. difficile in our study were associated with the catering industry. The high frequency of transient colonization by C. difficile indicates a substantial risk of exposure to the bacterium within healthy community populations. Asymptomatic carriers and the subsequent shedding of spores often remain undetected due to the absence of regular screening, thereby potentially contributing to the transmission of C. difficile to both the environment and other individuals. While transmission events from individual asymptomatic carriers may be infrequent, as demonstrated in a limited study [25], asymptomatic carriers may still play a significant role in the spread of the disease, given their potentially higher numbers compared to symptomatic C. difficile infection (CDI) patients.
The genus Vibrio, comprising halophilic, gram-negative bacteria, encompasses approximately twelve human pathogenic species that are commonly found in estuaries worldwide [26]. Interactions with vectors of pathogenic Vibrio spp. are frequently integrated into the traditional practices of coastal communities, such as the city of Ningbo, which are inherently connected to aquatic ecosystem services. Key components of coastal culture, including the consumption of raw shellfish (e.g., oysters), fishing, and food processing, may entail contact with Vibrio spp. vectors. The presence of coastal Vibrio spp. is influenced by hydrographic factors [27], including temperature (≥ 20 °C) [28], salinity ranges of 5–20 ppt and 15–36 ppt for V. vulnificus [29, 30] and V. parahaemolyticus. Our study revealed that the highest detection rate of V. parahaemolyticus occurred in September (7.0%), potentially due to dietary habits and temperature fluctuations. The rise in the carriage rate of V. parahaemolyticus in September is likely linked to increased seafood consumption following the end of the fishing ban. The subsequent decline in carriage rates may be attributable to the inhibitory effect of lower environmental temperatures and humidity in autumn and winter. Winter (November to February) is cold and comparatively dry, with the lowest humidity of the year. Mean temperatures range from 4 °C to 8 °C. The carriers of V. parahaemolyticus were found to be predominantly above the age of 38, indicating a potential susceptibility of the elderly population to Vibrio spp. infection.
Salmonella, a Gram-negative bacterial genus within the enterobacteriaceae family, exhibits strong pathogenicity and is capable of causing cross-infection between humans and animals. Foodborne illnesses affect approximately 1 in 10 individuals annually, with one in four cases of diarrheal illness attributed to Salmonella infection. In the United States, Salmonella ranks as the second most common foodborne pathogen [31]. The consumption of “ready-to-eat”, raw, or undercooked foods may contribute to the high incidence of Salmonella infections in our community. Our study revealed that Salmonella was most commonly detected in March (4.4%), with a decrease in June (1.9%) (Fig. 1H). Subsequently, we identified three S. kentucky and one S. give isolate from cater-related industries. Drug sensitivity tests indicated that S. kentucky isolates were resistant to nalidixic acid (quinolones), ampilicin and ciprofloxacin but S. give exhibited intermediate resistance to ciprofloxacin, consistent with findings by Karraouan.et al. [32]. Asymptomatic carriers may serve as potential reservoirs for the transmission of these foodborne pathogens.
The use of the GI panel has improved our ability to detect infectious agents that may cause gastroenteritis. Despite the increased costs, the implementation has simplified our menu of infectious gastroenteritis tests, improved turnaround times, and allowed us to detect more pathogens. Healthy population may not present any symptoms but it may be a great reservoir containing various pathogens and resistant plasmids which can potentially transmit person to person. Moreover our findings help to dig out the epidemiology of potential agents in healthy population. Further studies are needed in order to determine the drug sensitivity of isolates from stool.
The interpretations of our findings are subject to certain limitations. The modest sample size may affect the generalizability of the results. Although a broad-range multiplex PCR panel was used for detection, the study did not include cultural confirmation from the original samples to recover viable isolates of detected pathogens, such as diarrheagenic E. coli, V. parahaemolyticus, C. difficile, and P. shigelloides. Consequently, this precluded further essential phenotypic and strain-specific analyses, including antimicrobial susceptibility testing.
Conclusion
Our study identified EAEC, EPEC, and P. shigelloides as the most prevalent enteric pathogens in both single and co-carriage states within an asymptomatic cohort. Notably, Salmonella and C. difficile were exclusively detected among individuals working in the catering industry, highlighting this group as a significant reservoir for diverse pathogens. These findings suggest a considerable risk of asymptomatic transmission within the community, emphasizing the need for increased vigilance, particularly among occupational groups such as those in the catering sector. The detection of key pathogens across seasons indicates their ongoing circulation in healthy populations. Future longitudinal studies are warranted to investigate carriage dynamics, transmission mechanisms, and the genetic virulence profiles of these strains.
Acknowledgements
We extend our thanks to Haishu District Center for Disease Control and Prevention for helping in samples collection.
Abbreviations
- EAEC
Enteroaggregative E.coli
- EPEC
Enteropathogenic E.coli
- ETEC
Enterotoxigenic E.coli
- EIEC
Enteroinvasive E.coli
- EHEC
Enterohemorrhagic E.coli
- A.hydrophila
Aeromonas hydrophila
- V. cholerae
Vibrio cholerae
- V. parahaemolyticus
Vibrio parahaemolyticus
- C. difficile
Clostridioides difficile
- V. fluvialis
Vibrio fluvialis
- P. shigelloides
Plesiomonas shigelloides
- C. fetus
Campylobacter fetus
- C. jejuni
Campylobacter jejuni
- C. coli
Campylobacter coli
Author contributions
HS, DB and KX developed the methodology and designed whole study. KX and DB conducted the lab-experiments. HS and GP carried out the data analysis. HS, DB, KX contributed to the manuscript. WY, HB, GP and WW were involved in reviewing and editing the manuscript. All authors approved the submitted version.
Funding
Research reported in this publication was supported by Zhejiang Science and Technology Plan for Disease Prevention and Control (Project No. 2025JK266) and Traditional Chinese Medicine Science and Technology plan project of Zhejiang Provincial Health Commission (Grant No. 2024ZL934) and Special Fund for Clinical Research of Zhejiang Medical Association (Grant No. 2022ZYC-A163). This study was also supported by Project of Ningbo Leading Medical & Health Discipline (No.2022-F19).
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.
Declarations
Ethics approval and informed consent
This study was approved by the Ningbo Municipal Center of Disease Control Ethics Committee, Ningbo, Zhejiang Province, China (Approval No. 202403) and verbal informed consent has been provided by the participants. This article does not contain any studies with animals performed by any of the authors. All procedures involving human participants were performed in accordance with the ethical standards of the Declaration of Helsinki - Principles For Medical Research Involving Human Participants.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Hui Su and Dingyi Bo contributed equally to this work.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.