Preplanned Studies: Epidemiological Insights into Foodborne Pathogens Through qPCR Exploration of Prevalence — Beijing Municipality, China, January 2022–April 2023

Foodborne illnesses pose a persistent threat to global health, commonly manifesting as acute gastroenteritis due to infections spread via contaminated food or water (1). With the increasing globalization and complexity of our food networks, there is an imperative need for rapid and precise pathogen detection methods (2–3). This is especially true in Beijing Municipality, where the distinctive demography and environmental factors underscore the importance of employing advanced diagnostic techniques (4–6). In our investigation, we collected 1,011 stool specimens from patients with presumed foodborne illnesses at 28 health facilities within the city. Utilizing quantitative polymerase chain reaction (qPCR), we identified and enumerated 35 different foodborne pathogens. The findings revealed a significant incidence of Clostridium perfringens, Salmonella enterica, enterotoxigenic Escherichia coli (ETEC), and adenovirus. Remarkably, 71.22% of the samples exhibited multiple concurrent infections. It is crucial for public health officials to consider culture-independent diagnostic tests (CIDTs) for disease identification and the prevalence of co-infections, which will notably improve the monitoring, prevention, and management of foodborne diseases in metropolitan areas. From January 2022 to April 2023, we amassed a total of 1,011 stool specimens from patients diagnosed with foodborne diseases in 28 different hospitals across Beijing. These patients were identified as having a foodborne disease based on symptoms that included recurring watery stool, mucus-laden or bloody stool, or vomiting, occurring three or more times within a 24-hour span, and reported as potentially linked to food consumption. We categorized patients by age: children (≤5 years old), adolescents (6–17 years old), adults (18–64 years old), and seniors (≥65 years old).

Each patient provided a fresh fecal sample weighing 5 mg, preserved in Cary-Blair transport medium CM0935 (Oxoid, Basingstoke, Hampshire, United Kingdom) at 4 °C. The samples were then transported to a designated laboratory within 24 hours for nucleic acid extraction. Nucleic acids were extracted from the fecal samples at the laboratory using a rapid nucleic acid extraction instrument NE-02-K-96 (Guangzhou Baybio Bio-tech Co., Ltd. Guangzhou, Guangdong, China) and a commercially available extraction kit STNM-48-K (Guangzhou Baybio Bio-tech Co., Ltd. Guangzhou, Guangdong, China). Detection of foodborne pathogens was carried out using single qPCR, with specific primers and probes obtained from literature or custom-designed for this study. Details of the pathogens detected, along with their primer and probe sequences, qPCR cycling conditions, and templates are listed in Supplementary Table S1 .

Statistical analysis was conducted using SPSS software (version 20.0; IBM SPSS, Chicago, IL, USA). The frequencies of different pathogens among patients in various age groups were compared using χ² and Fisher’s exact tests for dichotomous variables. A P-value of <0.05 was considered statistically significant.

A total of 1,011 eligible stool samples were collected, and nucleic acid extraction was successful for all samples. The detection rate for foodborne pathogens overall was 92.48% (935/1,011).

Clostridium perfringens had the highest positivity rate at 52.03% among the samples analyzed (Figure 1A), followed by Salmonella enterica, ETEC, and adenovirus with rates of 20.67%, 20.97%, and 19.88%, respectively. Enteropathogenic Escherichia coli (EPEC) and enteroaggregative Escherichia coli (EAEC) were also prevalent, detected in 19.49% and 15.13% of the samples. Pathogens found in 5% to 15% of the samples included Staphylococcus aureus (S. aureus), Campylobacter jejuni, Bacteroides fragilis, Clostridium difficile, rotavirus, Vibrio parahaemolyticus, Shigella/Enteroinvasive Escherichia coli. (EIEC), Cronobacter spp., Aeromonas spp., norovirus, and Vibrio cholerae. Co-infections were present in 71.22% (720/1,011) of the samples (Table 1). Most infections involved one, two, or three pathogens, with rare cases having up to nine pathogens detected. Some cases of co-infections involved seven to nine pathogens, as detailed in Table 1 along with the onset time of these cases. Pathogen combinations for all samples are presented in Table 1. Pathogens were undetectable in 7.52% of the samples.

Figure 1. 

Prevalence of 35 pathogens in patients with acute diarrhea from Beijing. (A) Frequency distribution of 35 pathogens detected among 1,011 patients with acute diarrhea; (B) Seasonal distribution of Staphylococcus aureus, Aeromonas spp., and norovirus in 1,011 patients with acute diarrhea.

Abbreviation: ETEC=enterotoxigenic Escherichia coli; EPEC=enteropathogenic Escherichia coli; EAEC=enteroaggregative Escherichia coli; STEC=Shiga toxin-producing Escherichia coli; EIEC=Enteroinvasive Escherichia coli.

In spring, the prevalence of S. aureus was relatively low, increasing from summer onwards to peak at 33.33% in December (Figure 1B). Aeromonas spp. exhibited a higher positive rate during winter, whereas norovirus showed increased rates in winter and spring, except for December due to limited samples. Seasonal variations were not observed in other pathogens.

An analysis of pathogen positivity rates across different age groups revealed significant differences (Figure 2). Notably, children showed a higher positivity rate for adenovirus compared to adolescents and the elderly. EPEC presented elevated positivity rates in both children and adults when contrasted with elderly populations. S. aureus was more frequently detected in children and adolescents rather than in adult and elderly groups. C. difficile displayed increased positivity in both children and elderly individuals relative to adults. In contrast, V. cholerae was less commonly identified in children than in adults, and C. coli was found to have lower positivity rates in children as opposed to the other three age cohorts.

Figure 2. 

Isolation rates (%) of six pathogens across different age groups: (A) adenovirus, (B) ETEC, (C) Staphylococcus aureus, (D) Clostridium difficile, (E) Vibrio cholerae, (F) Campylobacter coli.

Note: Because age data was missing for some patients during data collection, only 883 samples were included in this analysis.

* P<0.05.

** P<0.01.

*** P<0.001.