Comparison of droplet digital PCR and quantitative PCR for the detection of Salmonella and its application for river sediments

Digital PCR assay for the specific detection and estimation of Salmonella contamination levels in poultry rinse

Strains of Salmonella are a frequent cause of foodborne illness and are known to contaminate poultry products. Most Salmonella testing methods can qualitatively detect Salmonella and cannot quantify or estimate the Salmonella load in samples. Therefore, the aim of this study was to standardize and validate a partitioned-based digital PCR (dPCR) assay for the detection and estimation of Salmonella contamination levels in poultry rinses. Pure culture Salmonella strains were cultured, enumerated, cold-stressed for 48 h, and used to inoculate whole carcass chicken rinse (WCCR) at 1-4 log CFU/30 mL and enriched at 37 °C for 5 h. Undiluted DNA samples with primer and probes targeting the Salmonella-specific invA gene were used for the dPCR assay. The dPCR assay was highly specific, with a limit of detection of 0.001 ng/μL and a limit of quantification of 0.01 ng/μL. The dPCR assay further showed no PCR reaction inhibition up to 5 μg of crude DNA extract. The assays accurately detected all cold-stressed Salmonella in inoculated WCCR samples following a 5-h enrichment. Most importantly, when converted to log, the dPCR copies/μL values accurately estimated the inoculated Salmonella levels. The dPCR assay standardized in this study is a robust method for the detection and estimation of Salmonella concentration in contaminated food samples. This approach can allow same-day decision-making for poultry processors attempting to maintain limits and controls on Salmonella contamination.

PathoSense: a rapid electroanalytical device platform for screening Salmonella in water samples

Salmonella contamination is a major global health challenge, causing significant foodborne illness. However, current detection methods face limitations in sensitivity and time, which mostly rely on the culture-based detection techniques. Hence, there is an immediate and critical need to enhance early detection, reduce the incidence and impact of Salmonella contamination resulting in outbreaks. In this work, we demonstrate a portable non-faradaic, electrochemical sensing platform capable of detecting Salmonella in potable water with an assay turnaround time of ~ 9 min. We evaluated the effectiveness of this sensing platform by studying two sensor configurations: one utilizing pure gold (Au) and the other incorporating a semiconductor namely a zinc oxide thin film coated on the surface of the gold (Au/ZnO). The inclusion of zinc oxide was intended to enhance the sensing capabilities of the system. Through comprehensive experimentation and analysis, the LoD (limit of detection) values for the Au sensor and Au/ZnO sensor were 0.9 and 0.6 CFU/mL, respectively. In addition to sensitivity, we examined the sensing platform's precision and reproducibility. Both the Au sensor and Au/ZnO sensor exhibited remarkable consistency, with inter-study percentage coefficient of variation (%CV) and intra-study %CV consistently below 10%. The proposed sensing platform exhibits high sensitivity in detecting low concentrations of Salmonella in potable water. Its successful development demonstrates its potential as a rapid and on-site detection tool, offering portability and ease of use. This research opens new avenues for electrochemical-based sensors in food safety and public health, mitigating Salmonella outbreaks and improving water quality monitoring.

Comparison of RT-qPCR and RT-dPCR Platforms for the Trace Detection of SARS-CoV-2 RNA in Wastewater

We compared reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and RT digital PCR (RT-dPCR) platforms for the trace detection of SARS-CoV-2 RNA in low-prevalence COVID-19 locations in Queensland, Australia, using CDC N1 and CDC N2 assays. The assay limit of detection (ALOD), PCR inhibition rates, and performance characteristics of each assay, along with the positivity rates with the RT-qPCR and RT-dPCR platforms, were evaluated by seeding known concentrations of exogenous SARS-CoV-2 in wastewater. The ALODs using RT-dPCR were approximately 2-5 times lower than those using RT-qPCR. During sample processing, the endogenous (n = 96) and exogenous (n = 24) SARS-CoV-2 wastewater samples were separated, and RNA was extracted from both wastewater eluates and pellets (solids). The RT-dPCR platform demonstrated a detection rate significantly greater than that of RT-qPCR for the CDC N1 and CDC N2 assays in the eluate (N1, p = 0.0029; N2, p = 0.0003) and pellet (N1, p = 0.0015; N2, p = 0.0067) samples. The positivity results also indicated that for the analysis of SARS-CoV-2 RNA in wastewater, including the eluate and pellet samples may further increase the detection sensitivity using RT-dPCR.

Application of digital PCR for public health-related water quality monitoring

Digital polymerase chain reaction (dPCR) is emerging as a reliable platform for quantifying microorganisms in the field of water microbiology. This paper reviews the fundamental principles of dPCR and its application for health-related water microbiology. The relevant literature indicates increasing adoption of dPCR for measuring fecal indicator bacteria, microbial source tracking marker genes, and pathogens in various aquatic environments. The adoption of dPCR has accelerated recently due to increasing use for wastewater surveillance of Severe Acute Respiratory Coronavirus 2 (SARS-CoV-2) - the virus that causes Coronavirus Disease 2019 (COVID-19). The collective experience in the scientific literature indicates that well-optimized dPCR assays can quantify genetic material from microorganisms without the need for a calibration curve and often with superior analytical performance (i.e., greater sensitivity, precision, and reproducibility) than quantitative polymerase chain reaction (qPCR). Nonetheless, dPCR should not be viewed as a panacea for the fundamental uncertainties and limitations associated with measuring microorganisms in water microbiology. With dPCR platforms, the sample analysis cost and processing time are typically greater than qPCR. However, if improved analytical performance (i.e., sensitivity and accuracy) is critical, dPCR can be an alternative option for quantifying microorganisms, including pathogens, in aquatic environments.

Digital Droplet-PCR for Quantification of Viable Campylobacter jejuni and Campylobacter coli in Chicken Meat Rinses

The EU commission established Regulation (2017/1495) in 2017 to reduce Campylobacter on chicken skin and to decrease the number of human cases of campylobacteriosis attributable to the consumption of poultry meat. A Process Hygiene Criterion based on colony-forming unit data was set to a maximum of 1000 CFU Campylobacter spp. per gram chicken neck skin at slaughterhouses. Confronted with stressors, including cold, oxidative stress or antibiotic treatment, live cells may enter into a viable but non-cultivable state (VBNC) and lose the ability to grow, in reference to the plate count ISO 10272-2:2017 method, but still possess the potential to recover and cause infections under favorable conditions. In this study, a droplet digital PCR combined with the intercalating dye propidium monoazide (PMA) was established for quantification of C. coli and C. jejuni in chicken meat rinses. The PMA was used to inactivate DNA from dead cells in this technique. This method was successfully validated against the reference method according to ISO 16140-2:2016 for accuracy and relative trueness. Additionally, it presented a 100% selectivity for Campylobacter jejuni and C. coli. Moreover, the technical measurement uncertainty was determined according to ISO 19036:2019, and the applicability of ddPCR for quantifying C. coli and C. jejuni in chicken meat rinses was investigated on naturally contaminated samples from slaughterhouses and supermarkets. Results obtained from this study demonstrated a strong correlation to qPCR as well as the classical microbiological reference method.

Molecular Diagnostic Tools Applied for Assessing Microbial Water Quality

Microbial water quality is of vital importance for human, animal, and environmental health. Notably, pathogenically contaminated water can result in serious health problems, such as waterborne outbreaks, which have caused huge economic and social losses. In this context, the prompt detection of microbial contamination becomes essential to enable early warning and timely reaction with proper interventions. Recently, molecular diagnostics have been increasingly employed for the rapid and robust assessment of microbial water quality implicated by various microbial pollutants, e.g., waterborne pathogens and antibiotic-resistance genes (ARGs), imposing the most critical health threats to humans and the environment. Continuous technological advances have led to constant improvements and expansions of molecular methods, such as conventional end-point PCR, DNA microarray, real-time quantitative PCR (qPCR), multiplex qPCR (mqPCR), loop-mediated isothermal amplification (LAMP), digital droplet PCR (ddPCR), and high-throughput next-generation DNA sequencing (HT-NGS). These state-of-the-art molecular approaches largely facilitate the surveillance of microbial water quality in diverse aquatic systems and wastewater. This review provides an up-to-date overview of the advancement of the key molecular tools frequently employed for microbial water quality assessment, with future perspectives on their applications.

Molecular Methods for Pathogenic Bacteria Detection and Recent Advances in Wastewater Analysis

With increasing concerns about public health and the development of molecular techniques, new detection tools and the combination of existing approaches have increased the abilities of pathogenic bacteria monitoring by exploring new biomarkers, increasing the sensitivity and accuracy of detection, quantification, and analyzing various genes such as functional genes and antimicrobial resistance genes (ARG). Molecular methods are gradually emerging as the most popular detection approach for pathogens, in addition to the conventional culture-based plate enumeration methods. The analysis of pathogens in wastewater and the back-estimation of infections in the community, also known as wastewater-based epidemiology (WBE), is an emerging methodology and has a great potential to supplement current surveillance systems for the monitoring of infectious diseases and the early warning of outbreaks. However, as a complex matrix, wastewater largely challenges the analytical performance of molecular methods. This review synthesized the literature of typical pathogenic bacteria in wastewater, types of biomarkers, molecular methods for bacterial analysis, and their recent advances in wastewater analysis. The advantages and limitation of these molecular methods were evaluated, and their prospects in WBE were discussed to provide insight for future development.

Enhanced Bio-Barcode Immunoassay Using Droplet Digital PCR for Multiplex Detection of Organophosphate Pesticides

A bio-barcode immunoassay based on droplet digital polymerase chain reaction (ddPCR) was developed to simultaneously quantify triazophos, parathion, and chlorpyrifos in apple, cucumber, cabbage, and pear. Three gold nanoparticle (AuNP) probes and magnetic nanoparticle (MNP) probes were prepared, binding through their antibodies with the three pesticides in the same tube. Three groups of primers, probes, templates, and three antibodies were designed to ensure the specificity of the method. Under the optimal conditions, the detection limits (expressed as IC₁₀) of triazophos, parathion, and chlorpyrifos were 0.22, 0.45, and 4.49 ng mL^-1, respectively. The linear ranges were 0.01-20, 0.1-100, and 0.1-500 ng mL^-1, and the correlation coefficients (R²) were 0.9661, 0.9834, and 0.9612, respectively. The recoveries and relative standard deviations (RSDs) were in the ranges of 75.5-98.9 and 8.3-16.7%. This study provides the first insights into the ddPCR for the determination of organophosphate pesticides. It also laid the foundation for high-throughput detection of other small molecules.

Digital PCR for accurate quantification of pathogens: Principles, applications, challenges and future prospects

Pathogens pose a severe threat to food safety and human health. The traditional methods for pathogen detection can't meet the growing diagnosis and control need. Digital PCR (dPCR) attracts a considerable attention for its ability to absolutely quantify pathogens with features of high selectivity, simplicity, accuracy and rapidity. The dPCR technique that achieves absolute quantification based on end-point measurement without standard curve offers a guideline for further genetic analysis and molecular diagnosis. It could contribute to the quantification of low level of nucleic acid, early detection and timely prevention of pathogenic diseases. In this review, 1442 publications about dPCR were selected and the detections of various pathogens by dPCR were reviewed comprehensively, including viruses, bacteria, parasites and fungi. A number of examples are cited to illustrate that dPCR is a new powerful tool with desired accuracy, sensitivity, and reproducibility for quantification of different types of pathogens. Moreover, the benefits, challenges and future prospects of the dPCR were also highlighted in this review.

Comparing Quantitative Methods for Analyzing Sediment DNA Records of Cyanobacteria in Experimental and Reference Lakes

Sediment DNA (sedDNA) analyses are rapidly emerging as powerful tools for the reconstruction of environmental and evolutionary change. While there are an increasing number of studies using molecular genetic approaches to track changes over time, few studies have compared the coherence between quantitative polymerase chain reaction (PCR) methods and metabarcoding techniques. Primer specificity, bioinformatic analyses, and PCR inhibitors in sediments could affect the quantitative data obtained from these approaches. We compared the performance of droplet digital polymerase chain reaction (ddPCR) and high-throughput sequencing (HTS) for the quantification of target genes of cyanobacteria in lake sediments and tested whether the two techniques similarly reveal expected patterns through time. Absolute concentrations of cyanobacterial 16S rRNA genes were compared between ddPCR and HTS using dated sediment cores collected from two experimental (Lake 227, fertilized since 1969 and Lake 223, acidified from 1976 to 1983) and two reference lakes (Lakes 224 and 442) in the Experimental Lakes Area (ELA), Canada. Relative abundances of Microcystis 16S rRNA (MICR) genes were also compared between the two methods. Moderate to strong positive correlations were found between the molecular approaches among all four cores but results from ddPCR were more consistent with the known history of lake manipulations. A 100-fold increase in ddPCR estimates of cyanobacterial gene abundance beginning in ~1968 occurred in Lake 227, in keeping with experimental addition of nutrients and increase in planktonic cyanobacteria. In contrast, no significant rise in cyanobacterial abundance associated with lake fertilization was observed with HTS. Relative abundances of Microcystis between the two techniques showed moderate to strong levels of coherence in top intervals of the sediment cores. Both ddPCR and HTS approaches are suitable for sedDNA analysis, but studies aiming to quantify absolute abundances from complex environments should consider using ddPCR due to its high tolerance to PCR inhibitors.

Rapid Detection of Salmonella typhimurium in Drinking Water by a White Light Reflectance Spectroscopy Immunosensor

Biosensors represent an attractive approach for fast bacteria detection. Here, we present an optical biosensor for the detection of Salmonella typhimurium lipopolysaccharide (LPS) and Salmonella bacteria in drinking water, based on white light reflectance spectroscopy. The sensor chip consisted of a Si die with a thin SiO₂ layer on top that was transformed into a biosensor through the immobilization of Salmonella LPS. The optical setup included a reflection probe with seven 200 μm fibers, a visible and near-infrared light source, and a spectrometer. The six fibers at the reflection probe circumference were coupled with the light source and illuminated the biosensor chip vertically, whereas the central fiber collected the reflected light and guided it to the spectrometer. A competitive immunoassay configuration was adopted for the analysis. Accordingly, a mixture of LPS or bacteria solution, pre-incubated for 15 min, with an anti-Salmonella LPS antibody was pumped over the chip followed by biotinylated secondary antibody and streptavidin for signal enhancement. The binding of the free anti-Salmonella antibody to chip-immobilized LPS led to a shift of the reflectance spectrum that was inversely related to the analyte concentration (LPS or bacteria) in the calibrators or samples. The total assay duration was 15 min, and the detection limits achieved were 4 ng/mL for LPS and 320 CFU/mL for bacteria. Taking into account the low detection limits, the short analysis time, and the small size of the chip and instrumentation employed, the proposed immunosensor could find wide application for bacteria detection in drinking water.

Recent Advances in the Detection of Antibiotic and Multi-Drug Resistant Salmonella: An Update

Antibiotic and multi-drug resistant (MDR) Salmonella poses a significant threat to public health due to its ability to colonize animals (cold and warm-blooded) and contaminate freshwater supplies. Monitoring antibiotic resistant Salmonella is traditionally costly, involving the application of phenotypic and genotypic tests over several days. However, with the introduction of cheaper semi-automated devices in the last decade, strain detection and identification times have significantly fallen. This, in turn, has led to efficiently regulated food production systems and further reductions in food safety hazards. This review highlights current and emerging technologies used in the detection of antibiotic resistant and MDR Salmonella.

Template length, concentration and guanidine and cytosine content influence on multiple displacement amplification efficiency

Detection of low abundance human health pathogens in environmental samples is a challenge for water monitoring. This limitation can be overcome by the introduction of multiple displacement amplification (MDA) where a minute amount of genetic material can be amplified using a phi-29 DNA polymerase. However, the genetic makeup and the concentration of the polynucleotides might influence the amplification process due to inherent assay bias. Herein, a series of experiments were designed to demonstrate the effect of genome length, guanidine and cytosine content, and template concentration on the efficiency of MDA. Quantitative polymerase chain reaction (qPCR) was performed to quantify pre- and post-MDA concentrations of selected genes. Linear regression between pre- and post-MDA log gene copies L^-1 of both environmental and lab-grown samples showed a positive correlation (F = 77.59, P < 0.001, R² = 0.7, slope = 1.01). Correlation between relative polynucleotide increase after MDA and target organism length and gene target guanidine and cytosine (G + C) content (F = 4.3, P = 0.02) shows that lower G + C and higher genome length is favored in the MDA process. The MDA process was shown to favor a longer genome over a shorter genome (1.19 and 1.04 change in log gene copy L^-1, respectively) and a lower G + C content over a higher G + C content (1.11 and 0.61 change in log gene copy L^-1, respectively). There was no MDA bias observed when polynucleotides had the same G + C and genome length but different initial concentrations. This study highlights the need for increased caution when interpreting relative abundance of organisms amplified by MDA such as in next generation sequencing.

Droplet digital PCR for the detection and monitoring of Legionella pneumophila

Legionella pneumophila(L. pneumophila is a harmful pathogen often found in water systems. In hospitals, the absence of L. pneumophila in water systems is mandatory by law, therefore, frequent and effective monitoring of water is of fundamental importance. Molecular methods based on reverse transcription-quantitative polymerase chain reaction (RT-qPCR) have been proposed for the detection of L. pneumophila, however, the sensitivity and accuracy of these methods have not been validated yet. Therefore, it is important to evaluate other strategies able to overcome the limits of culture-based and RT-qPCR methods. On these bases, we compared the sensitivity and accuracy of droplet digital PC (ddPCR) and RT-qPCR in water samples with known concentrations of L. pneumophila and in an in vitro model of water heat treatments. ddPCR showed a higher sensitivity rate and accuracy compared to RT-qPCR in detecting low bacterial load. In addition, ddPCR is not affected by the presence of fragmented DNA and showed higher accuracy than RT-qPC in monitoring the efficacy of heat shock treatments. In conclusion, ddPCR represents an innovative strategy to effectively detect L. pneumophila in water samples. Thanks to its high robustness, ddPCR could be applied also for the detection of L. pneumophila in patients with suspected legionellosis.

Fast, sensitive, and reliable detection of waterborne pathogens by digital PCR after coagulation and foam concentration

The quantification of pathogens is important for assessing water safety and preventing disease outbreaks. Culture-independent approaches, such as quantitative PCR (qPCR) and digital PCR (dPCR), are useful techniques for quantifying pathogens in water samples. However, since pathogens are usually present at low concentrations in water, it is necessary to concentrate microbial cells before extracting their DNA. Many existing microbial concentration methods are inefficient or take a long time to perform. In this study, we applied a coagulation and foam separation method to concentrate environmental water samples of between 1000 and 5000 mL to 100 μL of DNA (i.e., a 1-5 × 10⁴-fold concentration). The concentration process took <1 h. The DNA samples were then used to quantify various target pathogens using dPCR. One gene, the Shiga toxin gene (stx₂) of Shiga toxin-producing Escherichia coli, was detected at 32 copies/100 mL in a river water sample. The coagulation and foam concentration method followed by dPCR reported herein is a fast, sensitive, and reliable method to quantify pathogen genes in environmental water samples.

Comparing the performance of conventional PCR, RTQ-PCR, and droplet digital PCR assays in detection of Shigella

The incidence of foodborne infections caused by Shigella spp. is still very high in every year, which poses a great potential threat to public health. Conventional quantification methods based on culture techniques, biochemical, and serological identification are time-consuming and labor-intensive. To develop a more rapid and efficient detection method of Shigella spp., we compared the sensitivity and specificity of three different polymerase chain reaction (PCR) methods, including conventional PCR, quantitative real-time PCR (RTQ-PCR), and droplet digital PCR (ddPCR). Our results indicated that ddPCR method exhibited higher sensitivity, and the limit of detection was 10^-5 ng/μl for genomic DNA templates, 10^-1 cfu/ml for Shigella bacteria culture. In addition, we found that ddPCR was a time-saving method, which required a shorter pre-culturing time. Collectively, ddPCR assay was a reliable method for rapid and effective detection of Shigella spp.

New strategies for the enumeration of enteric pathogens in water

Water quality standards for drinking water and recreational waters have long been based on the enumeration of faecal coliforms in the various water supplies, with 0 CFU Escherichia coli/100 ml for drinking water and <126 CFU generic E. coli/100 ml for recreational waters. Irrigation water will soon undergo the same scrutiny in the United States. For over 50 years the most probable number method has been used by laboratories to estimate the level of viable bacteria in a sample, but this method is labour intensive and slow, especially if large numbers of samples need to be tested. In this review, we describe some recent innovations in methods to enumerate enteric pathogens in water. These methods are based on different reasoning schemes that can be categorized as biosensors and nucleic acid-based methods. All the methods described here used natural water sources. Several were also used to survey the bacterial levels in naturally contaminated samples. The different methods vary in their limits of detection, ease of use, and potential portability. Some combine very good limits of detection with the ability to overcome technical challenges; however, there is considerable room for improvement, as none of the methods are without shortcomings.

Methods for the detection of Cryptosporidium and Giardia: From microscopy to nucleic acid based tools in clinical and environmental regimes

The detection and characterization of genotypes and sub genotypes of Cryptosporidium and Giardia is essential for their enumeration, surveillance, prevention, and control. Different diagnostic methods are available for the analysis of Cryptosporidium and Giardia including conventional phenotypic tools that face major limitations in the specific diagnosis of these protozoan parasites. The substantial advancement in the development of genetic signature based molecular tools for the quantification, diagnosis and genetic variation analysis has increased the understanding of the epidemiology and preventive measures of related infections. The conventional methods such as microscopy, antibody and enzyme based approaches, offer better detection results when combined with advanced molecular methods. Gene based approaches increase the precision of identification, for example, many signatures detected in environmental matrices represent species/genotype that are not infectious to humans. This review summarizes the available methods and the advantages and limitations of advance detection techniques like nucleic acid-based approaches for the detection of viable oocysts and cysts of Cryptosporidium and Giardia along with the conventional and widely accepted detection techniques like microscopy, antibody and enzyme based ones. This technical article also encourages the wide application of molecular methods in genetic characterization of distinct species of Cryptosporidium and Giardia, to adopt necessary preventive measures with reliable identification and mapping the source of contamination.

Fusobacterium nucleatum and colorectal cancer: A review

Fusobacterium nucleatum (F. nucleatum) is a Gram-negative obligate anaerobe bacterium in the oral cavity and plays a role in several oral diseases, including periodontitis and gingivitis. Recently, several studies have reported that the level of F. nucleatum is significantly elevated in human colorectal adenomas and carcinomas compared to that in adjacent normal tissue. Several researchers have also demonstrated that F. nucleatum is obviously associated with colorectal cancer and promotes the development of colorectal neoplasms. In this review, we have summarized the recent reports on F. nucleatum and its role in colorectal cancer and have highlighted the methods of detecting F. nucleatum in colorectal cancer, the underlying mechanisms of pathogenesis, immunity status, and colorectal cancer prevention strategies that target F. nucleatum.

Optimized Co-extraction and Quantification of DNA From Enteric Pathogens in Surface Water Samples Near Produce Fields in California

Pathogen contamination of surface water is a health hazard in agricultural environments primarily due to the potential for contamination of crops. Furthermore, pathogen levels in surface water are often unreported or under reported due to difficulty with culture of the bacteria. The pathogens are often present, but require resuscitation, making quantification difficult. Frequently, this leads to the use of quantitative PCR targeted to genes unique to the pathogens. However, multiple pathogen types are commonly in the same water sample, both gram + and gram -, leading to problems with DNA extraction. With Shiga toxin-producing Escherichia coli (STEC), Salmonella enterica and Listeria monocytogenes as target, a method was optimized to co-extract all three and quantify the level of each using droplet digital PCR (ddPCR). Multiplexed target genes in STEC were virulence genes, shiga toxin 2 (stx2) and hemolysin (ehx). Likewise, multiplexed targets in Listeria and Salmonella were the virulence genes listeriolysin (hly) and invasion protein A (invA). Water samples were processed using microbiological techniques for each of the pathogens and duplicate water samples were quantified by ddPCR. A significant correlation was found between culture and ddPCR results indicating detection primarily of culturable cells by ddPCR. Average virulence gene levels were 923, 23 k, 69 and 152 copies per sample for stx2, ehx, hly and invA, respectively. Additionally, stx2, ehx and inv levels were significantly correlated (P < 0.05, R = 0.34) with generic E. coli MPN levels in the duplicate samples. Indirect quantification with ddPCR will improve understanding of prevalence of the pathogens and may reduce risks associated with contaminated surface water.