Microbial Source Tracking: A Tool for Identifying Sources of Microbial Contamination in the Food Chain

Interlaboratory performance and quantitative PCR data acceptance metrics for NIST SRM® 2917

Surface water quality quantitative polymerase chain reaction (qPCR) technologies are expanding from a subject of research to routine environmental and public health laboratory testing. Readily available, reliable reference material is needed to interpret qPCR measurements, particularly across laboratories. Standard Reference Material® 2917 (NIST SRM® 2917) is a DNA plasmid construct that functions with multiple water quality qPCR assays allowing for estimation of total fecal pollution and identification of key fecal sources. This study investigates SRM 2917 interlaboratory performance based on repeated measures of 12 qPCR assays by 14 laboratories (n = 1008 instrument runs). Using a Bayesian approach, single-instrument run data are combined to generate assay-specific global calibration models allowing for characterization of within- and between-lab variability. Comparable data sets generated by two additional laboratories are used to assess new SRM 2917 data acceptance metrics. SRM 2917 allows for reproducible single-instrument run calibration models across laboratories, regardless of qPCR assay. In addition, global models offer multiple data acceptance metric options that future users can employ to minimize variability, improve comparability of data across laboratories, and increase confidence in qPCR measurements.

DNA fingerprinting using BOX-A1R and (GTG)5 primers identify spatial variations of fecal contamination along Pasig River, Philippines

Pasig River is one of the most economically important rivers in Metro Manila, Philippines. It traverses some of the region's major cities, and because of its strategic location, it is utilized as a means of transportation, as a source of water for domestic and industrial uses, and for recreational purposes. However, due to population growth, industrialization, and land use, the river's water quality is deteriorating. Wastes that pollute the river pose health risks to the people that benefit from it. To prevent the river's further degradation, it is essential to identify the origin of contamination. In this study, the sources of fecal contamination in Pasig River were identified using BOX-A1R and (GTG)₅ primers in the DNA fingerprinting of Escherichia coli isolated from the river. Results showed the dominance of human contamination (percent composition = 65.55%), followed by agricultural sources (percent composition = 23.48%), and the lowest was from sewage (percent composition = 10.98%). The results of this research can help in evaluating public health risks and can be used as a scientific basis for policymaking and implementation for the rehabilitation and improvement of Pasig River.

Performance of NIST SRM® 2917 with 13 recreational water quality monitoring qPCR assays

Fecal pollution remains a significant challenge for recreational water quality management worldwide. In response, there is a growing interest in the use of real-time quantitative PCR (qPCR) methods to achieve same-day notification of recreational water quality and associated public health risk as well as to characterize fecal pollution sources for targeted mitigation. However, successful widespread implementation of these technologies requires the development of and access to a high-quality standard control material. Here, we report a single laboratory qPCR performance assessment of the National Institute of Standards and Technology Standard Reference Material 2917 (NIST SRM® 2917), a linearized plasmid DNA construct that functions with 13 recreational water quality qPCR assays. Performance experiments indicate the generation of standard curves with amplification efficiencies ranging from 0.95 ± 0.006 to 0.99 ± 0.008 and coefficient of determination values (R2) ≥ 0.980. Regardless of qPCR assay, variability in repeated measurements at each dilution level were very low (quantification threshold standard deviations ≤ 0.657) and exhibited a heteroscedastic trend characteristic of qPCR standard curves. The influence of a yeast carrier tRNA added to the standard control material buffer was also investigated. Findings demonstrated that NIST SRM® 2917 functions with all qPCR methods and suggests that the future use of this control material by scientists and water quality managers should help reduce variability in concentration estimates and make results more consistent between laboratories.

Use of metagenomic microbial source tracking to investigate the source of a foodborne outbreak of cryptosporidiosis

Cryptosporidium is a protozoan parasite of global public health importance that causes gastroenteritis in a variety of vertebrate hosts, with many human outbreaks reported yearly, often from ingestion of contaminated water or food. Despite the major public health implications, little is typically known about sources of contamination of disease outbreaks caused by Cryptosporidium. Here, we study a national foodborne outbreak resulted from infection with Cryptosporidium parvum via romaine lettuce, with the main goal to trace the source of the parasite. To do so, we combined traditional outbreak investigation methods with molecular detection and characterization methods (i.e. PCR based typing, amplicon and shotgun sequencing) of romaine lettuce samples collected at the same farm from which the contaminated food was produced. Using 18S rRNA typing, we detected C. parvum in two out of three lettuce samples, which was supported by detections in the metagenome analysis. Microbial source tracking analysis of the lettuce samples suggested sewage water as a likely source of the contamination, albeit with some uncertainty. In addition, the high degree of overlap in bacterial species content with a public human gut microbial database corroborated the source tracking results. The combination of traditional and molecular based methods applied here is a promising tool for future source tracking investigations of food- and waterborne outbreaks of Cryptosporidium spp. and can help to control and mitigate contamination risks.

Microbiome Sample Comparison and Search: From Pair-Wise Calculations to Model-Based Matching

A huge quantity of microbiome samples have been accumulated, and more are yet to come from all niches around the globe. With the accumulation of data, there is an urgent need for comparisons and searches of microbiome samples among thousands of millions of samples in a fast and accurate manner. However, it is a very difficult computational challenge to identify similar samples, as well as identify their likely origins, among such a grand pool of samples from all around the world. Currently, several approaches have already been proposed for such a challenge, based on either distance calculation, unsupervised algorithms, or supervised algorithms. These methods have advantages and disadvantages for the different settings of comparisons and searches, and their results are also drastically different. In this review, we systematically compared distance-based, unsupervised, and supervised methods for microbiome sample comparison and search. Firstly, we assessed their accuracy and efficiency, both in theory and in practice. Then we described the scenarios in which one or multiple methods were applicable for sample searches. Thirdly, we provided several applications for microbiome sample comparisons and searches, and provided suggestions on the choice of methods. Finally, we provided several perspectives for the future development of microbiome sample comparison and search, including deep learning technologies for tracking the sources of microbiome samples.

Recent advances in dual recognition based surface enhanced Raman scattering for pathogenic bacteria detection: A review

Rapid and reliable detection of pathogenic bacteria at the early stage represents a highly topical research area for food safety and public health. Although culture based method is the gold standard method for bacteria detection, recent techniques have promoted the development of alternative methods, such as surface enhanced Raman scattering (SERS). SERS provides additional advantages of high speed, simultaneous detection and characterization, multiplex analysis, and comparatively low cost. However, conventional SERS methods for bacteria detection are facing limitations of low sensitivity, susceptible to matrix interference, and poor accuracy. In recent years, specific detection of pathogenic bacteria with dual recognition based SERS methods has attracted increasing attentions. These methods include two steps recognition of target bacteria, and integrate the functions of target separation and detection. Considering their merits of excellent specificity, ultrahigh sensitivity, multiplex detection capability, and potential for on-site applications, these methods are promising alternatives for rapid and reliable detection of pathogenic bacteria. Herein, this review aims to summarize the recent advances in dual recognition based SERS methods for specific detection of pathogenic bacteria. Their advantages and limitations are discussed, and further perspectives are tentatively given. This review provides new insights into the application of SERS as a reliable tool for pathogenic bacteria detection.

Molecular typing tools for identifying and characterizing lactic acid bacteria: a review

Identification and classification of beneficial microbes is of the highest significance in food science and related industries. Conventional phenotypic approaches pose many challenges, and they may misidentify a target, limiting their use. Genotyping tools show comparatively better prospects, and they are widely used for distinguishing microorganisms. The techniques already employed in genotyping of lactic acid bacteria (LAB) are slightly different from one another, and each tool has its own advantages and disadvantages. This review paper compiles the comprehensive details of several fingerprinting tools that have been used for identifying and characterizing LAB at the species, sub-species, and strain levels. Notably, most of these approaches are based on restriction digestion, amplification using polymerase chain reaction, and sequencing. Nowadays, DNA sequencing technologies have made considerable progress in terms of cost, throughput, and methodology. A research journey to develop improved versions of generally applicable and economically viable tools for fingerprinting analysis is ongoing globally.

Verification of Bacteroidales 16S rRNA markers as a complementary tool for detecting swine fecal pollution in the Yangtze Delta

To correctly assess and properly manage the public health risks associated with exposure to contaminated water, it is necessary to identify the source of fecal pollution in a watershed. In this study, we evaluated the efficacy of our two previously developed real time-quantitative PCR (qPCR) assays for the detection of swine-associated Bacteroidales genetic markers (gene 1-38, gene 3-53) in the Yangtze Delta watershed of southeastern China. The results indicated that the gene 1-38 and 3-53 markers exhibited high accuracy (92.5%, 91.7% conditional probability, respectively) in detecting Bacteroidales spp. in water samples. According to binary logistic regression (BLR), these two swine-associated markers were well correlated (P < 0.05) with fecal indicators (Escherichia coli and Enterococci spp.) and zoonotic pathogens (E. coli O157: H7, Salmonella spp. and Campylobacter spp.) in water samples. In contrast, concentrations of conventional fecal indicator bacteria (FIB) were not correlated with zoonotic pathogens, suggesting that they are noneffective at detecting fecal pollution events. Collectively, the results obtained in this study demonstrated that a swine-targeted qPCR assay based on two Bacteroidales genes markers (gene 1-38, gene 3-53) could be a useful tool in determining the swine-associated impacts of fecal contamination in a watershed.

Pathogen-Specific Impacts of the 2011-2012 La Niña-Associated Floods on Enteric Infections in the MAL-ED Peru Cohort: A Comparative Interrupted Time Series Analysis

Extreme floods pose multiple direct and indirect health risks. These risks include contamination of water, food, and the environment, often causing outbreaks of diarrheal disease. Evidence regarding the effects of flooding on individual diarrhea-causing pathogens is limited, but is urgently needed in order to plan and implement interventions and prioritize resources before climate-related disasters strike. This study applied a causal inference approach to data from a multisite study that deployed broadly inclusive diagnostics for numerous high-burden common enteropathogens. Relative risks (RRs) of infection with each pathogen during a flooding disaster that occurred at one of the sites-Loreto, Peru-were calculated from generalized linear models using a comparative interrupted time series framework with the other sites as a comparison group and adjusting for background seasonality. During the early period of the flood, increased risk of heat-stable enterotoxigenic E. coli (ST-ETEC) was identified (RR = 1.73 [1.10, 2.71]) along with a decreased risk of enteric adenovirus (RR = 0.36 [0.23, 0.58]). During the later period of the flood, sharp increases in the risk of rotavirus (RR = 5.30 [2.70, 10.40]) and sapovirus (RR = 2.47 [1.79, 3.41]) were observed, in addition to increases in transmission of Shigella spp. (RR = 2.86 [1.81, 4.52]) and Campylobacter spp. (RR = 1.41 (1.01, 1.07). Genotype-specific exploratory analysis reveals that the rise in rotavirus transmission during the flood was likely due to the introduction of a locally atypical, non-vaccine (G2P[4]) strain of the virus. Policy-makers should target interventions towards these pathogens-including vaccines as they become available-in settings where vulnerability to flooding is high as part of disaster preparedness strategies, while investments in radical, transformative, community-wide, and locally-tailored water and sanitation interventions are also needed.

Microbial indicators and molecular markers used to differentiate the source of faecal pollution in the Bogotá River (Colombia)

Intestinal pathogenic microorganisms are introduced into the water by means of faecal contamination, thus creating a threat to public health and to the environment. Detecting these contaminants has been difficult due to such an analysis being costly and time-intensive; as an alternative, microbiological indicators have been used for this purpose, although they cannot differentiate between human or animal sources of contamination because these indicators are part of the digestive tracts of both. To identify the sources of faecal pollution, the use of chemical, microbiological and molecular markers has been proposed. Currently available markers present some geographical specificity. The aim of this study was to select microbial and molecular markers that could be used to differentiate the sources of faecal pollution in the Bogotá River and to use them as tools for the evaluation and identification of the origin of discharges and for quality control of the water. In addition to existing microbial source markers, a phage host strain (PZ8) that differentiates porcine contamination was isolated from porcine intestinal content. The strain was identified biochemically and genotypically as Bacteroides. The use of this strain as a microbial source tracking indicator was evaluated in bovine and porcine slaughterhouse wastewaters, raw municipal wastewaters and the Bogotá River. The results obtained indicate that the selected microbial and molecular markers enable the determination of the source of faecal contamination in the Bogotá River by using different algorithms to develop prediction models.

Tracking of Intentionally Inoculated Lactic Acid Bacteria Strains in Yogurt and Probiotic Powder

The present work aimed at tracking intentionally inoculated lactic acid bacteria (LAB) strains in yogurt and probiotic powder. Leuconostoc (Leu.) mesenteroides (11251), Lactobacillus (L.) brevis (B151), and Lactobacillus plantarum (LB41^K) strains were tracked in yogurt, and L. plantarum (LB41^P) was tracked in a commercial probiotic powder. The yogurt was intentionally inoculated with the selected bacterial strains. Two types of yogurt with known and unknown bacterial pools were utilized. The standard 16S rRNA gene sequencing was used to evaluate the initial screening. The molecular typing tools, random amplified polymorphic DNA (RAPD), repetitive element palindromic PCR (rep-PCR), and comparative gene sequence analysis of selected housekeeping loci were used to track the inoculated dubious strains. Out of 30 random selections for each inoculation, the developed method identified seven (11251), nine (B151), and five (LB41^K) colonies in the yogurt. The validation was performed by identifying 7 colonies (LB41^P) out of 30 in the probiotic powder. The DNA banding profiles and the gene sequence alignments led to the identification of the correct inoculated strains. Overall, the study summarizes the use of molecular tools to identify the deliberately inoculated LAB strains. In conclusion, the proposed polyphasic approach effectively tracked the intentionally inoculated strains: Leu. mesenteroides, L. brevis, and L. plantarum (LB41^K) in yogurt and L. plantarum (LB41^P) in probiotic powder. The study demonstrates how to track industrially relevant misused LAB strains in marketable food products.

The Importance of Bacterial Culture to Food Microbiology in the Age of Genomics

Culture-based and genomics methods provide different insights into the nature and behavior of bacteria. Maximizing the usefulness of both approaches requires recognizing their limitations and employing them appropriately. Genomic analysis excels at identifying bacteria and establishing the relatedness of isolates. Culture-based methods remain necessary for detection and enumeration, to determine viability, and to validate phenotype predictions made on the bias of genomic analysis. The purpose of this short paper is to discuss the application of culture-based analysis and genomics to the questions food microbiologists routinely need to ask regarding bacteria to ensure the safety of food and its economic production and distribution. To address these issues appropriate tools are required for the detection and enumeration of specific bacterial populations and the characterization of isolates for, identification, phylogenetics, and phenotype prediction.

Combining phagomagnetic separation with immunoassay for specific, fast and sensitive detection of Staphylococcus aureus

A Staphylococcus aureus (S. aureus)-specific lytic bacteriophage P-S. aureus-9, isolated from an environmental water sample, was assembled on magnetic beads for capturing S. aureus from samples through magnetic separation. Horseradish Peroxidase (HRP) labeled immunoglobulin (IgG) antibodies were used to detect the captured S. aureus by reacting with protein A on S. aureus followed by colorimetric signals, which were generated from the catalytic reaction between HRP and the substrate 3,3',5,5'-Tetramethylbenzidine (TMB). Under optimal conditions, the calibration curve was linear from 1.0×10⁴ to 1.0×10⁶CFUmL^-1. The limit of detection (LOD) for the assay was 2.47×10³CFUmL^-1 and 8.86×10³CFUmL^-1 of S. aureus in PBS and apple juice, respectively. Moreover, the whole assay revealed outstanding specificity towards S. aureus, without any interference of common pathogenic bacteria, and can be completed within 90min without any pre-enrichment. As far as known, it was the first time to detect S. aureus based on the double site recognition of bacteriophage and mammal IgG. The novel approach has shown good potentials for a rapid, specific, cheap and simple detection of S. aureus in food samples.

Dual Recognition Strategy for Specific and Sensitive Detection of Bacteria Using Aptamer-Coated Magnetic Beads and Antibiotic-Capped Gold Nanoclusters

Food poisoning and infectious diseases caused by pathogenic bacteria such as Staphylococcus aureus (SA) are serious public health concerns. A method of specific, sensitive, and rapid detection of such bacteria is essential and important. This study presents a strategy that combines aptamer and antibiotic-based dual recognition units with magnetic enrichment and fluorescent detection to achieve specific and sensitive quantification of SA in authentic specimens and in the presence of much higher concentrations of other bacteria. Aptamer-coated magnetic beads (Apt-MB) were employed for specific capture of SA. Vancomycin-stabilized fluorescent gold nanoclusters (AuNCs@Van) were prepared by a simple one-step process and used for sensitive quantification of SA in the range of 32-10(8) cfu/mL with the detection limit of 16 cfu/mL via a fluorescence intensity measurement. And using this strategy, about 70 cfu/mL of SA in complex samples (containing 3 × 10(8) cfu/mL of other different contaminated bacteria) could be successfully detected. In comparison to prior studies, the developed strategy here not only simplifies the preparation procedure of the fluorescent probes (AuNCs@Van) to a great extent but also could sensitively quantify SA in the presence of much higher concentrations of other bacteria directly with good accuracy. Moreover, the aptamer and antibiotic used in this strategy are much less expensive and widely available compared to common-used antibodies, making it cost-effective. This general aptamer- and antibiotic-based dual recognition strategy, combined with magnetic enrichment and fluorescent detection of trace bacteria, shows great potential application in monitoring bacterial food contamination and infectious diseases.