Application of quantitative real-time PCR compared to filtration methods for the enumeration of Escherichia coli in surface waters within Vietnam.

Surface water samples in Vietnam were collected from the Saigon River, rural and suburban canals, and urban runoff canals in Ho Chi Minh City, Vietnam, and were processed to enumerate Escherichia coli. Quantification was done through membrane filtration and quantitative real-time polymerase chain reaction (PCR). Mean log colony-forming unit (CFU)/100 ml E. coli counts in the dry season for river/suburban canals and urban canals were log 2.8 and 3.7, respectively, using a membrane filtration method, while using Taqman quantitative real-time PCR they were log 2.4 and 2.8 for river/suburban canals and urban canals, respectively. For the wet season, data determined by the membrane filtration method in river/suburban canals and urban canals samples had mean counts of log 3.7 and 4.1, respectively. While mean log CFU/100 ml counts in the wet season using quantitative PCR were log 3 and 2, respectively. Additionally, the urban canal samples were significantly lower than those determined by conventional culture methods for the wet season. These results show that while quantitative real-time PCR can be used to determine levels of fecal indicator bacteria in surface waters, there are some limitations to its application and it may be impacted by sources of runoff based on surveyed samples.

Fecal contamination in irrigation water and microbial quality of vegetable primary production in urban farms of Metro Manila, Philippines.

Microbial contamination of fresh produce can present a severe risk to public health. By conducting a rigorous survey of irrigation waters, the impacts of fecal contamination on the quality of produce could be assessed. In this study, surface waters were observed to be contaminated with Escherichia coli, Salmonella spp., and somatic coliphages. Culture methods show that out of 373 irrigation water, soil, and vegetable samples collected for a 1-year period, 232 (62.20%) were found positive for E. coli, 213 (57.26%) for somatic coliphages, and 2 (0.53%) for Salmonella spp. Out of 190 water samples, 167 (87.9%) were found to have E.coli, 174 (91.6%) have somatic coliphages, and 1 (0.5%) with Salmonella spp. In soil samples, 36 of 91 (39.6%) have E. coli, 31 (34.0%) have somatic coliphages, and none with Salmonella spp. Lastly, out of 92 vegetable samples, 29 (31.5%), 8 (8.7%), and 1 (1.1%) were found to have E. coli, somatic coliphages, and Salmonella spp., respectively. Molecular analysis confirmed the presence of bacterial contaminants. Seasonal weather conditions were noted to have an effect on the presence and number of these fecal indicator organisms. The observed data suggest that contaminated irrigation water may greatly affect the quality of fresh produce from these agricultural operations.

Microbiological quality of fresh produce from open air markets and supermarkets in the Philippines.

This study is the first in the Philippines to conduct a comprehensive assessment of the prevalence of bacterial pathogens and somatic phages in retailed fresh produce used in salad preparation, namely, bell pepper, cabbage, carrot, lettuce, and tomato, using culture and molecular methods. Out of 300 samples from open air and supermarkets, 16.7% tested positive for thermotolerant Escherichia coli, 24.7% for Salmonella spp., and 47% for somatic phages. Results show that counts range from 0.30 to 4.03 log10 CFU/g for E. coli, 0.66 to ≥ 2.34 log10 MPN/g for Salmonella spp., and 1.30 to ≥ 3.00 log 10 PFU/g for somatic phages. Statistical analyses show that there was no significant difference in the microbial counts between open air and supermarkets (α = 0.05). TaqMan and AccuPower Plus DualStar real-time polymerase chain reaction (RT-PCR) was used to confirm the presence of these organisms. The relatively high prevalence of microorganisms observed in produce surveyed signifies reduction in shelf-life and a potential hazard to food safety. This information may benefit farmers, consumers, merchants, and policy makers for foodborne disease detection and prevention.

Fatty acid modulation of autoinducer (AI-2) influenced growth and macrophage invasion by Salmonella Typhimurium.

Autoinducer-2 (AI-2) is a small molecule that is involved in bacterial cell-to-cell signaling whose precursor formation is mediated by luxS. A luxS mutant of Salmonella Typhimurium PJ002 (ΔluxS) was grown in glucose-containing M-9 minimal medium supplemented with varying concentrations (1×, 10×, and 100×) of long-chain fatty acids (linoleic acid, oleic acid, palmitic acid, and stearic acid) to study the influence of fatty acids on growth rate and macrophage invasion. Additionally, in vitro synthesized AI-2 was added to this medium to identify the influence of AI-2 on S. Typhimurium PJ002 (ΔluxS) growth rate and macrophage invasion. The growth rate constant (k) for each experimental treatment was determined based on OD600 values recorded during 12 h of incubation. There was a significant (p=0.01) increase in the growth rate of S. Typhimurium PJ002 (ΔluxS) in the presence of AI-2 when compared to the phosphate-buffered saline (PBS) control. However, fatty acids either singly or in a mixture were unable to influence AI-2's effect on growth rate. The presence of AI-2 significantly (p=0.02) decreased the invasiveness of S. Typhimurium PJ002 (ΔluxS) towards the murine macrophage cell line, RAW 264.7. However, the fatty acid mixture was able to reverse this reduction and restore invasiveness to background levels. These results suggest that, while AI-2 may enhance the growth rate and reduce macrophage invasion by the luxS mutant S. Typhimurium PJ002 (ΔluxS), fatty acids may influence the virulence in S. Typhimurium (PJ002) by modulating AI-2 activity.

Antimicrobial Susceptibility and Frequency of bla and qnr Genes in Salmonella enterica Isolated from Slaughtered Pigs.

Salmonella enterica is known as one of the most common foodborne pathogens worldwide. While salmonellosis is usually self-limiting, severe infections may require antimicrobial therapy. However, increasing resistance of Salmonella to antimicrobials, particularly fluoroquinolones and cephalosporins, is of utmost concern. The present study aimed to investigate the antimicrobial susceptibility of S. enterica isolated from pork, the major product in Philippine livestock production. Our results show that both the qnrS and the blaTEM antimicrobial resistance genes were present in 61.2% of the isolates. While qnrA (12.9%) and qnrB (39.3%) were found less frequently, co-carriage of blaTEM and one to three qnr subtypes was observed in 45.5% of the isolates. Co-carriage of blaTEM and blaCTX-M was also observed in 3.9% of the isolates. Antimicrobial susceptibility testing revealed that the majority of isolates were non-susceptible to ampicillin and trimethoprim/sulfamethoxazole, and 13.5% of the isolates were multidrug-resistant (MDR). MDR isolates belonged to either O:3,10, O:4, or an unidentified serogroup. High numbers of S. enterica carrying antimicrobial resistance genes (ARG), specifically the presence of isolates co-carrying resistance to both ß-lactams and fluoroquinolones, raise a concern on antimicrobial use in the Philippine hog industry and on possible transmission of ARG to other bacteria.

PCR-based detection and serovar identification of Salmonella in retail meat collected from wet markets in Metro Manila, Philippines.

This study aimed to detect Salmonella from retail meat collected from nine wet markets in Metro Manila, and identify the subtypes of Salmonella isolates using molecular serotyping assays from previously developed primers. Of the 720 collected meat samples, 57.64% were found to be Salmonella-contaminated. The most predominant serogroup was Salmonella O:3, and Salmonella serogroups O:4, O:6,7, O:8, O:9, and undetermined serogroups were also found. Most frequently detected isolates in bovine meat were S. 3:e,h:1,6 (putative identity: S. Anatum) and S: 4:e,h:1,2 (putative identity: S. Saintpaul), in porcine meat was S. 3:e,h:1,6 (putative identity: S. Anatum), and S. 8:i:z6 (putative identity: S. Kentucky) was common in poultry products. This study also demonstrated retail meat samples were contaminated with multiple Salmonella serogroups and serovars. This is the first Philippine study that utilized PCR-based assays to characterize Salmonella isolates down to a serovar level and provides baseline information regarding Salmonella prevalence and serovar distribution in retail meat. Molecular serotyping performed in this study can be used as an alternative approach to traditional serotyping in surveillance of Salmonella in the Philippines since the latter is expensive, time-consuming, and requires skilled technicians.

Quantitative microbial risk assessment of Cryptosporidium in bivalve samples from Manila Bay, Philippines

In the Philippines, consumption of bivalves is very common due to its year-round availability and cheap price. However, many consume bivalves as lightly-cooked or raw. This might pose health hazards because bivalves are filter-feeders which act as vehicles for transmission of several pathogens such as the protozoan parasite Cryptosporidium, the causative agent of cryptosporidiosis. Cryptosporidiosis in humans is manifested by profuse diarrhea and abdominal pain. To determine the risk of acquiring cryptosporidiosis from consumption of bivalves, quantitative microbial risk assessment (QMRA) should be done. This study aimed to determine the risk associated with the consumption of bivalves which are contaminated with Cryptosporidium oocysts. The results indicate that consumption of at least 21 grams of cooked bivalves contaminated with at least 0.1% viable oocysts might pose a risk to consumers, especially to immunocompromised individuals. This estimated risk of infection exceeded the United States Environmental Protection Agency (US EPA) standards (1.0×10-4). Results call for drive of decision-makers to establish an educational or treatment program to reduce the incidence of gastrointestinal infections of the consumers. Improvement of sanitation techniques and hygienic practices will contribute to the decrease of occurrence of the disease.

Differential expression of virulence-related genes in A Salmonella enterica serotype typhimurium luxS mutant in response to autoinducer AI-2 and poultry meat-derived AI-2 inhibitor.

Bacterial cells communicate with each other and respond to external stimuli using signal molecules called autoinducers (AIs). Poultry meat contains inhibitors that apparently interfere with AI-2 signaling. Our objective was to understand the expression of Salmonella Typhimurium genes (using spotted microarrays) in response to AI-2 in the presence, and absence, of poultry meat (PM) derived AI-2 inhibitors. Expression of 1136 virulence-related genes in Salmonella Typhimurium wildtype and its isogenic luxS mutant strain (unable to produce AI-2) was monitored when the cells were exposed for 3 hours to different treatments containing in vitro synthesized AI-2 and a PM inhibitor (AI-2, AI-2 + PM, or PM alone). The responses of the genes were unique in the presence of in vitro synthesized AI-2. Of 1136 genes on the array, 23 genes were differentially expressed (either upregulated or downregulated) at least 1.5-fold (P < 0.05) in the presence of AI-2. Exposure to the PM inhibitor resulted in 36 genes being differentially expressed, while the combined AI-2 + PM treatment resulted in 22 genes being differentially expressed, of which only 7 genes showed overlap with the PM treatment, suggesting a unique response when AI-2 interacts with the inhibitor molecules. The results suggest that Salmonella gene expression can vary depending on the presence or absence of the poultry meat matrix and/or AI-2 molecules. Understanding the interaction of AI-2 and inhibitors of AI-2 activity found in poultry meat can help explain Salmonella survival and virulence on poultry products.

Use of artificial neural networks to accurately identify Cryptosporidium oocyst and Giardia cyst images.

Cryptosporidium parvum and Giardia lamblia are protozoa capable of causing gastrointestinal diseases. Currently, these organisms are identified using immunofluorescent antibody (IFA)-based microscopy, and identification requires trained individuals for final confirmation. Since artificial neural networks (ANN) can provide an automated means of identification, thereby reducing human errors related to misidentification, ANN were developed to identify Cryptosporidium oocyst and Giardia cyst images. Digitized images of C. parvum oocysts and G. lamblia cysts stained with various commercial IFA reagents were used as positive controls. The images were captured using a color digital camera at 400 x (total magnification), processed, and converted into a binary numerical array. A variety of "negative" images were also captured and processed. The ANN were developed using these images and a rigorous training and testing protocol. The Cryptosporidium oocyst ANN were trained with 1,586 images, while Giardia cyst ANN were trained with 2,431 images. After training, the best-performing ANN were selected based on an initial testing performance against 100 images (50 positive and 50 negative images). The networks were validated against previously "unseen" images of 500 Cryptosporidium oocysts (250 positive, 250 negative) and 282 Giardia cysts (232 positive, 50 negative). The selected ANNs correctly identified 91.8 and 99.6% of the Cryptosporidium oocyst and Giardia cyst images, respectively. These results indicate that ANN technology can be an alternate to having trained personnel for detecting these pathogens and can be a boon to underdeveloped regions of the world where there is a chronic shortage of adequately skilled individuals to detect these pathogens.

Identification of Cryptosporidium parvum oocysts by an artificial neural network approach.

Microscopic detection of Cryptosporidium parvum oocysts is time-consuming, requires trained analysts, and is frequently subject to significant human errors. Artificial neural networks (ANN) were developed to help identify immunofluorescently labeled C. parvum oocysts. A total of 525 digitized images of immunofluorescently labeled oocysts, fluorescent microspheres, and other miscellaneous nonoocyst images were employed in the training of the ANN. The images were cropped to a 36- by 36-pixel image, and the cropped images were placed into two categories, oocyst and nonoocyst images. The images were converted to grayscale and processed into a histogram of gray color pixel intensity. Commercially available software was used to develop and train the ANN. The networks were optimized by varying the number of training images, number of hidden neurons, and a combination of these two parameters. The network performance was then evaluated using a set of 362 unique testing images which the network had never "seen" before. Under optimized conditions, the correct identification of authentic oocyst images ranged from 81 to 97%, and the correct identification of nonoocyst images ranged from 78 to 82%, depending on the type of fluorescent antibody that was employed. The results indicate that the ANN developed were able to generalize the training images and subsequently discern previously unseen oocyst images efficiently and reproducibly. Thus, ANN can be used to reduce human errors associated with the microscopic detection of Cryptosporidium oocysts.