Identification and differentiation of Campylobacter species by high-resolution melting curve analysis

Campylobacter prevalence from food, animals, human and environmental samples in Iran: a systematic review and meta-analysis

BACKGROUND

Campylobacter regarded as a major cause of foodborne gastroenteritis in humans. The present study aimed to determine the prevalence of campylobacter in food, animal and human samples of Iran.

RESULTS

Quantitative synthesis was performed from 119 articles. White meat had the highest pooled prevalence of Campylobacter spp. (43.9%). Pooled prevalence of 7.9% and 5.5% for Campylobacter, respectively, were determined for red meat and eggs from Iran. Campylobacter was seen in 14.9% of environmental samples and 8.4% of human samples. In most of the samples C. jejuni had higher frequency than C. coli. Most of the isolated Campylobacter harbored several of the known virulence related genes of this pathogen.

CONCLUSION

Chicken was identified as the Campylobacter reservoir. As such preventive strategies in all stages of poultry production until consumption are necessary to control foodborne human infection with Campylobacter in Iran.

Simultaneous Detection of Foodborne Pathogens Using a Real-Time PCR Triplex High-Resolution Melt Assay

Foodborne pathogens pose risks to populations all over the world. Pathogens can be used as bioterrorism agents, causing an outbreak that affects many individuals through the consumption of a commonly affected food or beverage. A PCR assay can be used to identify pathogens through their unique melting points using a high-resolution melt assay. Assays can be used to detect the bacteria individually or from a mixture using species-specific primers. An assay was developed to detect and identify three pathogens that routinely cause multistate foodborne outbreaks, as documented by the U.S. Centers for Disease Control and Prevention, Campylobacter jejuni (C. jejuni), Escherichia coli (E. coli), and Salmonella enterica (S. enterica), in single bacterium assays and a multiplex. The primers were targeted to specific and unique gene sequences of each pathogen, including cadF, yedN, and hilA, respectively. Each pathogen was identified by its unique melting temperature in single assays: 78.10 ± 0.58 °C for C. jejuni, 81.96 ± 0.42 °C for E. coli, and 87.55 ± 0.37 °C for S. enterica. The multiplex successfully detected and identified all three of the pathogens with the distinctly separated melt peaks. The PCR high-resolution melt assay also proved to be specific, reproducible, fast, and sensitive in experiments.

Development of high-resolution melting (HRM) assay to differentiate the species of Shigella isolates from stool and food samples

Shigella species, a group of intracellular foodborne pathogens, are the main causes of bacillary dysentery and shigellosis in humans worldwide. It is essential to determine the species of Shigella in outbreaks and food safety surveillance systems. The available immunological and molecular methods for identifying Shigella species are relatively complicated, expensive and time-consuming. High resolution melting (HRM) assay is a rapid, cost-effective, and easy to perform PCR-based method that has recently been used for the differentiation of bacterial species. In this study, we designed and developed a PCR-HRM assay targeting rrsA gene to distinguish four species of 49 Shigella isolates from clinical and food samples and evaluated the sensitivity and specificity of the assay. The assay demonstrated a good analytical sensitivity with 0.01–0.1 ng of input DNA template and an analytical specificity of 100% to differentiate the Shigella species. The PCR-HRM assay also was able to identify the species of all 49 Shigella isolates from clinical and food samples correctly. Consequently, this rapid and user-friendly method demonstrated good sensitivity and specificity to differentiate species of the Shigella isolates from naturally contaminated samples and has the potential to be implemented in public health and food safety surveillance systems.

Convolutional neural network analysis of recurrence plots for high resolution melting classification

BACKGROUND AND OBJECTIVE

High resolution melting (HRM) analysis is a rapid and correct method for identification of species, such as, microorganism, bacteria, yeast, virus, etc. HRM data are produced using real-time polymerase chain reaction (PCR) and unique for each species. Analysis of the HRM data is important for several applications, such as, for detection of diseases (e.g., influenza, zika virus, SARS-Cov-2 and Covid-19 diseases) in health, for identification of spoiled foods in food industry, for analysis of crime scene evidence in forensic investigation, etc. However, the characteristics of the HRM data can change due to the experimental conditions or instrumental settings. In addition, it becomes laborious and time-consuming process as the number of samples increases. Because of these reasons, the analysis and classification of the HRM data become challenging for species which have similar characteristics.

METHODS

To improve the classification accuracy of HRM data, we propose to use image (visual) representation of HRM data, which we call HRM images, that are generated using recurrence plots, and propose convolutional neural network (CNN) based models for classifying HRM images. In this study, two different types of recurrence plots are generated, which are black-white recurrence plots (BW-RP) and gray scale recurrence plots (GS-RP) and four different CNN models are proposed for classifying HRM data.

RESULTS

The classification performance of the proposed methods are evaluated based on average classification accuracy and F1 score, specificity, recall, and precision values for each yeast species. When BW-RP representation of HRM data is used as input to the CNN models, the best classification accuracy of 95.2% is obtained. The classification accuracies of CNN models for melting curve and GS-RP data representations of HRM data are 90.13% and 86.13%, respectively. The classification accuracy of support vector machines (SVM) model that take melting curve representation of HRM data is 86.53%. Moreover, when BW-RP representation of HRM data is used as input to the CNN models, the F1 score, specificity, recall and precision values are the highest for almost all of species.

CONCLUSIONS

Experimental results show that using BW-RP representation of HRM data improved the classification accuracy of HRM data and CNN models that take these images as input outperformed CNN models that take melting curve and GS-RP representations of HRM data as inputs and SVM model that take melting curve representation of HRM data as input.

Isolation and Identification of Escherichia albertii in Broiler Chickens From Kermanshah

Background: F Escherichia albertii is generally recognized as a human pathogen with a limited number of strains. It has also been identified as a cause of mortality among birds. The clinical significance and prevalence of E. albertii are somewhat unknown. Objectives: The aim of the present study was to isolate and identify E. albertii as a causative agent of respiratory infections in broilers. Materials and Methods: During a three-month period (Winter 2018), 200 samples of the air sacs of 100 chickens with suspected colibacillosis were collected. Routine biochemical tests were performed and suspected isolates of E. albertii were selected for polymerase chain reaction (PCR). Results: A total of 68 suspected samples of E. albertii and Escherichia coli were isolated. Further, E. coli was detected in all the suspected samples using species-specific sequences of E. coli (uidA) and E. albertii (mdh and lysP). Conclusion: Escherichia albertii was not identified as a cause of respiratory infection in broilers.

Identification and differentiation of Campylobacter isolated from chicken meat using real-time polymerase chain reaction and high resolution melting analysis of hipO and glyA genes

Background and Aim:

Campylobacter species have been recognized as the most frequently identified bacterial cause of human gastroenteritis. The aims of this study were to identify Campylobacter jejuni and Campylobacter coli species isolated from chicken meat and to analyze the differences in the melting curve patterns of both species.

Materials and Methods:

A total of 105 chicken meat samples collected from slaughterhouses and retailers in six provinces in Indonesia were examined for the isolation and identification of Campylobacter spp. A total of 56 positive isolates of Campylobacter spp. were analyzed using the quantitative real-time polymerase chain reaction and high resolution melting method.

Results:

The prevalence of Campylobacter spp. in chicken meat was found to be 61.9%. Regarding the identification, 23 isolates (41.07%) were C. jejuni, 22 (39.29%) were C. coli, six (10.71%) were a mix between C. jejuni and C. coli, and five isolates (8.93%) were Campylobacter spp. All the C. jejuni and C. coli isolates produced varied melting curve patterns.

Conclusion:

The high prevalence of C. jejuni and C. coli in chicken meat in Indonesia indicates a high risk of the incidence of campylobacteriosis in humans.

Multiplex Detection of Salmonella spp., E. coli O157 and L. monocytogenes by qPCR Melt Curve Analysis in Spiked Infant Formula

Food poisoning continue to be a threat in the food industry showing a need to improve the detection of the pathogen responsible for the hospitalization cases and death. DNA-based techniques represent a real advantage and allow the detection of several targets at the same time, reducing cost and time of analysis. The development of new methodology using SYBR Green qPCR for the detection of L. monocytogenes, Salmonella spp. and E. coli O157 simultaneously was developed and a non-competitive internal amplification control (NC-IAC) was implemented to detect reaction inhibition. The formulation and supplementation of the enrichment medium was also optimized to allow the growth of all pathogens. The limit of detection (LoD) 95% obtained was <1 CFU/25 g for E. coli O157, and 2 CFU/25 g for Salmonella spp. and L. monocytogenes and regarding the multiplex detection a LoD 95% of 1.7 CFU/25 g was observed. The specificity, relative sensitivity and accuracy of full methodology were 100% and the use of the NC-IAC allowed the reliability of the results without interfering with the sensitivity of the methodology. The described study proved to obtain results comparable to those of probe-based qPCR, and more economically than classical high resolution melting qPCR, being both important aspects for its implementation in the food industry.

Differentiation of stx1A gene for detection of Escherichia coli serotype O157: H7 and Shigella dysenteriae type 1 in food samples using high resolution melting curve analysis

Escherichia coli serotype O157: H7 and Shigella dysenteriae type 1 as the Shiga toxin-producing bacteria cause some acute gastrointestinal and extraintestinal diseases such as hemorrhagic uremic syndrome and bloody diarrhea in human. Stx genes are the key virulence factors in these pathogens. The aim of this study was to develop HRMA assay to differentiate stx1A gene for detection of E. coli serotype O157: H7 and Sh. dysenteriae type 1 and determine the prevalence of these pathogens in food samples using this method. PCR-HRMA assay and gold standard methods have been carried out for identification of pathogens among 135 different food samples. We found HRMA method a sensitive and specific assay (100 and 100%, respectively) for differentiation of stx1A gene, consequently, detection of these pathogens in food samples. Also, the highest prevalence of E. coli serotype O157: H7 and Sh. dysenteriae type 1 harboring stx1A gene was observed in raw milk and vegetable salad samples, respectively. HRMA as a rapid, inexpensive, sensitive and specific method is suggested to be used for differentiation of stx1A gene to detect E. coli serotype O157: H7 and Sh. dysenteriae type 1 as the key pathogens for safety evaluation of food samples.

Fecal Colonization of Extended-Spectrum Beta Lactamase-Producing Salmonella spp. in Broilers in Lorestan Province of Iran

Background: Poultry is considered as a major source of human contamination with nontyphoidal Salmonella species. Global concern regarding the emergence and dispersion of extended-spectrum beta-lactamase (ESBLs)-producing isolates in broilers has increased during recent years. Objective: This study was proposed to evaluate the prevalence of Salmonella and the associated ESBLs in broilers in Lorestan province of Iran. Materials and Methods: Five hundred fresh fecal samples of broilers were phenotypically screened for Salmonella. The isolates were confirmed molecularly using an invA-based polymerase chain reaction (PCR). Confirmatory combination disk method was applied for phenotypic detection of ESBLs among the isolates, followed by molecular identification of blaCTX-M, blaTEM, and blaSHV genes in 3 single PCR assays among positive isolates. Chi-square test in SPSS software was used for the assessment of statistical relationships. Results: Of the 95 Salmonella isolates detected using routine bacteriological methods, all were confirmed molecularly. They generated the expected 254-bp amplicon. Moreover, 13 isolates were phenotypically recognized as ESBL determinants, among which 9 and 4 harbored blaCTX-M and blaTEM, respectively. No blaSHV and co-existence of the genes were determined. Conclusion: The threat imposed by dissemination of ESBL-producing non-typhoidal Salmonella spp. isolated from broilers was confirmed in the studied region. Continuous monitoring programs, application of biosecurity measures, and prudent prescription of antibiotics are warranted in order to prevent the introduction or dispersion of the ESBL-producing Salmonella.

Microsatellite High-Resolution Melting (SSR-HRM) to Track Olive Genotypes: From Field to Olive Oil

The need to support food labelling has driven to the development of PCR-based techniques suitable for food analysis. DNA-based markers have been successfully employed for varietal tracing in Protected Designation of Origin (PDO) olive oils. In this study, we report a fast, sensitive, and easy-to-use strategy for PDO olive varietal identification. To achieve this aim four different DNA extraction methods were tested and compared, based on initial volume, extraction time, the gDNA concentration, and quality ratios. The optimized DNA extraction protocol from extra virgin olive oils, based on CTAB-hexane-chloroform extraction, proved to be the most effective. High-resolution melting (HRM) DNA assay was developed based on nuclear microsatellites (gSSR) and plastid DNA (cpDNA) aiming an accurate identification of the olive varieties present in the olive oil samples. After PCR reproducibility evaluation, six molecular markers: three SSRs and three cpDNA loci were chosen based on their discrimination power. The SSR-HRM strategy assays were designed to target UDO99-011, UDO99-039, UDO99-024, and ssrOeUA-DCA16 loci. All SSR-PCR products generated from these primers were analyzed by capillary electrophoresis (CE) for HRM data validation. The SSR coupled with HRM melting curve analysis generated 14 HRM profiles sufficient to genotype all varieties, highlighting their potential use for varietal discrimination. The locus ssrOeUA-DCA16 generated a specific melting curve that allow a high-throughput discrimination of the Picual and Cobrançosa varieties in olive oil samples. Further, the UDO99-024 was also tested by SSR-HRM assay in commercial olive oil samples with promising results. Considering time, cost, and performance SSR-HRM proved to be a reliable method suitable for varietal tracing of olive oils. PRACTICAL APPLICATION: Olive oil authenticity is a form of protecting producers and consumers against fraudulent practices. Herein, we present a DNA barcode suitable for the identification of olive varieties, allowing an accurate identification of the olive varieties in olive oil samples using SSR-HRM assay. Its applicability in commercial olive oil samples is viable. This methodology can be used as a tool for Extra Virgin Olive Oil (EVOO) adulterations detection.

A Novel Natural Antimicrobial Can Reduce the in vitro and in vivo Pathogenicity of T6SS Positive Campylobacter jejuni and Campylobacter coli Chicken Isolates

Human campylobacteriosis is considered one of the most common foodborne diseases worldwide with poultry identified as the main source of infection accounting for 50-80% of human cases. Highly virulent Campylobacter spp., positive for the Type VI secretion system (T6SS), which have an increased ability to adhere to and invade the host gastrointestinal epithelium are highly prevalent in poultry. Multidrug resistant strains of bacteria are rapidly evolving and therefore, new antimicrobials to supplement animal feed that are able to control Campylobacter species, are in great need. The work presented herein indicates that a novel phenolic antimicrobial, Auranta 3001, is able to reduce the adhesion and invasion of human intestinal epithelial cells (HCT-8) by two T6SS positive chicken isolates, C. jejuni RC039 (p < 0.05) and C. coli RC013 (p < 0.001). Exposure of C. jejuni RC039 and C. coli RC013 to Auranta 3001 downregulated the expression of hcp and cetB genes, known to be important in the functionality of T6SS. Furthermore, the reduced adhesion and invasion is associated with a significant decrease in bacterial motility of both isolates (p < 0.05-p < 0.001) in vitro. Most importantly our in vivo results show that Auranta 3001 is able to reduce cecum colonization levels from log 8 CFU/ml to log 2 CFU/ml for C. jejuni RC039 and from log 7 CFU/ml to log 2 CFU/ml for C. coli RC013. In conclusion, this novel antimicrobial is able to reduce the pathogenic properties of T6SS campylobacters in vitro and also to decrease colonization in vivo.

A Novel Natural Antimicrobial Can Reduce the in vitro and in vivo Pathogenicity of T6SS Positive Campylobacter jejuni and Campylobacter coli Chicken Isolates

Human campylobacteriosis is considered one of the most common foodborne diseases worldwide with poultry identified as the main source of infection accounting for 50-80% of human cases. Highly virulent Campylobacter spp., positive for the Type VI secretion system (T6SS), which have an increased ability to adhere to and invade the host gastrointestinal epithelium are highly prevalent in poultry. Multidrug resistant strains of bacteria are rapidly evolving and therefore, new antimicrobials to supplement animal feed that are able to control Campylobacter species, are in great need. The work presented herein indicates that a novel phenolic antimicrobial, Auranta 3001, is able to reduce the adhesion and invasion of human intestinal epithelial cells (HCT-8) by two T6SS positive chicken isolates, C. jejuni RC039 (p < 0.05) and C. coli RC013 (p < 0.001). Exposure of C. jejuni RC039 and C. coli RC013 to Auranta 3001 downregulated the expression of hcp and cetB genes, known to be important in the functionality of T6SS. Furthermore, the reduced adhesion and invasion is associated with a significant decrease in bacterial motility of both isolates (p < 0.05-p < 0.001) in vitro. Most importantly our in vivo results show that Auranta 3001 is able to reduce cecum colonization levels from log 8 CFU/ml to log 2 CFU/ml for C. jejuni RC039 and from log 7 CFU/ml to log 2 CFU/ml for C. coli RC013. In conclusion, this novel antimicrobial is able to reduce the pathogenic properties of T6SS campylobacters in vitro and also to decrease colonization in vivo.