Recent sensing technologies for pathogen detection in milk: A review

Rapid Concentration and Detection of Bacteria in Milk Using a Microfluidic Surface Acoustic Wave Activated Nanosieve

Rapid detection of microbes is a key feature for monitoring food quality. Unfortunately, current detection systems rely on labor-intensive and time-consuming lab-based processes that are not suitable for point-of-interest applications and typically require several days before results are available. Here, we demonstrate a microfluidic system capable of rapidly concentrating, fluorescent staining, and detecting bacteria in unprocessed complex biological media such as milk. This concentration is done using a surface acoustic wave-driven microfluidic device which operates based on the Bjerknes force, a force generated on one particle by another in its close proximity. We exploit this effect by exciting a tightly packed bed of 50 μm polystyrene microparticles temporarily with surface acoustic waves within a microfluidic device to capture and release bacterial cells on demand. The bacterial cells are fluorescently stained during capture and then detected using fluorescence microscopy upon release. This device offers a high capturing efficiency (>80%) and a 34 Colony Forming Units (CFU)/mL limit of detection, which is 1 order of magnitude below that of plate counting at 30 CFU per standard 100 μL plate (or 300 CFU/mL). This can be attained in just 1 h of processing at 10 μL/min. With this system, we demonstrate that bacterial detection from extremely low concentration samples down to the order of ∼10 CFU/mL is possible without requiring any additional external pre- or postprocessing.

Basic concepts, recent advances, and future perspectives in the diagnosis of bovine mastitis

Mastitis is one of the most widespread infectious diseases that adversely affects the profitability of the dairy industry worldwide. Accurate diagnosis and identification of pathogens early to cull infected animals and minimize the spread of infection in herds is critical for improving treatment effects and dairy farm welfare. The major pathogens causing mastitis and pathogenesis are assessed first. The most recent and advanced strategies for detecting mastitis, including genomics and proteomics approaches, are then evaluated . Finally, the advantages and disadvantages of each technique, potential research directions, and future perspectives are reported. This review provides a theoretical basis to help veterinarians select the most sensitive, specific, and cost-effective approach for detecting bovine mastitis early.

Rapid detection of foodborne pathogens in diverse foodstuffs by universal electrochemical aptasensor based on UiO-66 and methylene blue composites

Rapid and sensitive detection of foodborne pathogens in complex environments is essential for food protection. A universal electrochemical aptasensor was fabricated for the detection of three common foodborne pathogens, including Escherichia coli (E. coli), Staphylococcus aureus (S. aureus), and Salmonella typhimurium (S. typhimurium). The aptasensor was developed based on the homogeneous and membrane filtration strategy. Zirconium-based metal-organic framework (UiO-66)/methylene blue (MB)/aptamer composite was designed as a signal amplification and recognition probe. Bacteria were quantitatively detected by the current changes of MB. By simply changing the aptamer, different bacteria could be detected. The detection limits of E. coli, S. aureus and S. typhimurium were 5, 4 and 3 CFU·mL^-1, respectively. In humidity and salt environments, the stability of the aptasensor was satisfactory. The aptasensor exhibited satisfactory detection performance in different real samples. This aptasensor has excellent potential for rapid detection of foodborne pathogens in complex environments.

Using a random laser to measure the content of protein in skim milk

The luminescence of skim milk samples with distinct protein content doped with rhodamine B was investigated. The samples were excited by a nanosecond laser tuned at 532 nm, and the emission was characterized as a random laser. Its features were analyzed as a function of the protein aggregate content. The results showed a linear correlation between the random laser peak intensity and the protein content. This paper proposes a rapid detection photonic method to evaluate the protein content in skim milk based on the intensity of the random laser emission.

A Combination of Novel Nucleic Acid Cross-Linking Dye and Recombinase-Aided Amplification for the Rapid Detection of Viable Salmonella in Milk

Salmonella, as an important foodborne pathogen, can cause various diseases, such as severe enteritis. In recent years, various types of nucleicacid-intercalating dyes have been utilized to detect viable Salmonella. However, in principle, the performance of existing nucleic acid dyes is limited because they depend on the integrity of cell membrane. Herein, based on the metabolic activity of bacteria, a novel DNA dye called thiazole orange monoazide (TOMA) was introduced to block the DNA from dead bacteria. Recombinase-aided amplification (RAA) was then performed to detect viable Salmonella in samples. In this study, the permeability of TOMA to the cell membrane of Salmonella was evaluated via confocal laser scanning microscopy and fluorescence emission spectrometry. The limit of detection (LOD) of the TOMA–RAA method was 2.0 × 10⁴ CFU/mL in pure culture. The feasibility of the TOMA–RAA method in detecting Salmonella was assessed in spiked milk. The LOD for Salmonella was 3.5 × 10² CFU/mL after 3 h of enrichment and 3.5 × 10⁰ CFU/mL after 5 h of enrichment. The proposed TOMA–RAA assay has great potential to be applied to accurately detect and monitor foodborne pathogens in milk and its byproducts.

Utilizing Electrochemical-Based Sensing Approaches for the Detection of SARS-CoV-2 in Clinical Samples: A Review

The development of precise and efficient diagnostic tools enables early treatment and proper isolation of infected individuals, hence limiting the spread of coronavirus disease 2019 (COVID-19). The standard diagnostic tests used by healthcare workers to diagnose severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection have some limitations, including longer detection time, the need for qualified individuals, and the use of sophisticated bench-top equipment, which limit their use for rapid SARS-CoV-2 assessment. Advances in sensor technology have renewed the interest in electrochemical biosensors miniaturization, which provide improved diagnostic qualities such as rapid response, simplicity of operation, portability, and readiness for on-site screening of infection. This review gives a condensed overview of the current electrochemical sensing platform strategies for SARS-CoV-2 detection in clinical samples. The fundamentals of fabricating electrochemical biosensors, such as the chosen electrode materials, electrochemical transducing techniques, and sensitive biorecognition molecules, are thoroughly discussed in this paper. Furthermore, we summarised electrochemical biosensors detection strategies and their analytical performance on diverse clinical samples, including saliva, blood, and nasopharyngeal swab. Finally, we address the employment of miniaturized electrochemical biosensors integrated with microfluidic technology in viral electrochemical biosensors, emphasizing its potential for on-site diagnostics applications.

An ultrasensitive electrochemiluminescence biosensor for the detection of total bacterial count in environmental and biological samples based on a novel sulfur quantum dot luminophore

An electrochemiluminescence sensor for total bacterial count detection based on sulfur quantum dots with β-nicotinamide adenine dinucleotide as an important parameter.

A peroxidase-like activity-based colorimetric sensor array of noble metal nanozymes to discriminate heavy metal ions

Heavy metal ions (HMIs), including Cu²⁺, Ag⁺, Cd²⁺, Hg²⁺, and Pb²⁺ from the environment pose a threat to human beings and can cause a series of life-threatening diseases. Therefore, colorimetric sensors with convenience and flexibility for HMI discrimination are still required. To provide a solution, a peroxidase-like activity-based colorimetric sensor array of citrate-capped noble metal nanozymes (osmium, platinum, and gold) has been fabricated. Some studies reported that some HMIs could interact with the noble metal nanozymes leading to a change in their peroxidase-like activity. This phenomenon was confirmed in our work. Based on this principle, different concentrations of HMIs (Cu²⁺, Ag⁺, Cd²⁺, Hg²⁺, and Pb²⁺) were discriminated. Moreover, their practical application has been tested by discriminating HMIs in tap water and SiYu lake water. What is more, as an example of the validity of our method to quantify HMIs at nanomolar concentrations, the LOD of Hg²⁺ was presented. To sum up, our study not only demonstrates the differentiation ability of this nanozyme sensor array but also gives hints for using nanozyme sensor arrays for further applications.

Green one-step synthesis of carbon quantum dots from orange peel for fluorescent detection of Escherichia coli in milk

Carbon quantum dots (CQDs) prepared by a green one-step approach was used for sensitive and selective assay of Escherichia coli O157: H7 (E. coli). CQDs was synthesized from orange peel as a carbon source via a microwave-assisted method. The CQDs displayed strong green fluorescence under excitation wavelength of 420 nm. A fluorescent probe (CQDs-MNPs) for E. coli was fabricated based on CQDs labeled with aptamer (aptamer-CQDs) and magnetic nanoparticles labeled with complementary DNA (cDNA-MNPs). Fluorescent intensity of the CQDs-MNPs was decreased with addition of E. coli. The linearity between fluorescent intensity and E. coli concentration was used for developing a fluorescent method with detecting range of 500-10⁶ CFU/mL and detection limit of 487 CFU/mL. Milk samples contaminated by E. coli were analyzed by this method, and the results agreed with that achieved by plate-counting methods. This fluorescent probe exhibits great potential in guaranteeing food quality and safety.

Comparison of the intensity of biofilm formation by Listeria monocytogenes using classical culture-based method and digital droplet PCR

Listeria monocytogenes is a Gram-positive bacterium, commonly found in food, water or sewage. This microorganism is capable of forming biofilm on different surfaces such as steel, glass, polypropylene etc. Recently an increase in cases of listeriosis has been noted, making L. monocytogenes the important health threat. Therefore, there is a need for rapid and sensitive detection of this pathogen. This study aimed to compare the number of L. monocytogenes cells recovered from the biofilm (prepared on steel and polypropylene) using the detection and amplification of the hlyA gene (droplet digital PCR, ddPCR) and the classical culture method. The research material consisted of 96 L. monocytogenes strains. A total of 58 isolates were obtained from clinical samples and 38 isolates derived from the municipal sewage treatment plant. Additionally, the reference strain ATCC®19111™ (WDCM00020) was used. The Pearson correlation coefficient for the results obtained by the classical culture-based method and ddPCR was 0.864 and 0.725, for biofilms produced on AISI 304 stainless steel surface and the polypropylene surface, respectively. Correlations were statistically significant (p ≤ 0.001), indicating that the ddPCR technique is an effective tool for the assessment of bacteria number in the biofilm.

Development of amperometric biosensor in modified carbon paste with enzymatic preparation based on lactase immobilized on carbon nanotubes

Abstract

The variety of products derived from milk, without or with lactose, encourages the development of more effective analytical techniques that can be applied to the quality control of both the production line and the final products. Thus, in this work an efficient and minimally invasive method for the detection of lactose was proposed, using a biosensor containing the enzyme lactase (LAC) immobilised on carbon nanotubes (CNTs) that, when reacting with lactose, emit an electrochemical signal. This biosensor was connected to a potentiostat, and its electrochemical cell was composed of the following three electrodes: reference electrode (Ag/AgCl), auxiliary electrode (platinum wire), and working electrode (biosensor) on which graphite (carbon) paste (CP), CNTs, and LAC were deposited. The transmission electron microscopy and scanning electron microscopy were used in the characterisation of the composite morphology, indicating excellent interactions between the CNTs and LAC. The sensitivity of the CP/LAC/CNT biosensor was determined as 5.67 μA cm^-2.mmol^-1 L and detection limits around 100 × 10^-6 mol L^-1 (electrode area = 0.12 cm²) and an increase in the stability of the system was observed with the introduction of CNTs because, with about 12 h of use, there was no variation in the signal (current). The results indicate that the association between the CNTs and LAC favoured the electrochemical system.

Graphic Abstract

Label-Free Detection of Bacteria in Fruit Juice by Nano-Flow Cytometry

Rapid quantification of microbial contamination in fruit juice is highly desired for food safety control. Yet, the complex sample matrix and the diversity of bacterial contaminants present a great challenge. Employing a laboratory-built nano-flow cytometer (nFCM), here we report the development of a label-free approach for the detection of bacteria population in fruit juice. The weak autofluorescence of bacterial cells was used as a hallmark for the identification of bacteria. The sample pretreatment protocol was optimized to reduce fluorescence background, lyse residual plant cells and debris, and attain a good recovery of bacteria from juice samples. It was demonstrated that the nFCM was able to enumerate individual bacteria of very weak autofluorescence, and a clear differentiation from residual juice particulates was achieved. For bacteria spiked in the orange juice, the recovery rate was around 95% and a linear correlation between nFCM analysis and plate counting was acquired in the range of 3 × 10⁴ to 3 × 10⁸ cfu/mL. The assay, including sample pretreatment and instrument analysis, can be accomplished within 1 h, which is far more efficient than plate counting. Using a 40 mL sample volume, the detection limit in apple juice was ∼10² cells/mL. The as-developed method was successfully applied to bacterial measurement of freshly made orange juice and apple juice purchased from grocery stores. We believe it could also have potential practical application in microbial control analysis of other juices and water.

Biosensors for On-Farm Diagnosis of Mastitis

Bovine mastitis is an inflammation of the mammary gland caused by a multitude of pathogens with devastating consequences for the dairy industry. Global annual losses are estimated to be around €30 bn and are caused by significant milk losses, poor milk quality, culling of chronically infected animals, and occasional deaths. Moreover, mastitis management routinely implies the administration of antibiotics to treat and prevent the disease which poses serious risks regarding the emergence of antibiotic resistance. Conventional diagnostic methods based on somatic cell counts (SCC) and plate-culture techniques are accurate in identifying the disease, the respective infectious agents and antibiotic resistant phenotypes. However, pressure exists to develop less lengthy approaches, capable of providing on-site information concerning the infection, and in this way, guide, and hasten the most adequate treatment. Biosensors are analytical tools that convert the presence of biological compounds into an electric signal. Benefitting from high signal-to-noise ratios and fast response times, when properly tuned, they can detect the presence of specific cells and cell markers with high sensitivity. In combination with microfluidics, they provide the means for development of automated and portable diagnostic devices. Still, while biosensors are growing at a fast pace in human diagnostics, applications for the veterinary market, and specifically, for the diagnosis of mastitis remain limited. This review highlights current approaches for mastitis diagnosis and describes the latest outcomes in biosensors and lab-on-chip devices with the potential to become real alternatives to standard practices. Focus is given to those technologies that, in a near future, will enable for an on-farm diagnosis of mastitis.

Rapid methods and sensors for milk quality monitoring and spoilage detection

Monitoring of food quality, in particular, milk quality, is critical in order to maintain food safety and human health. To guarantee quality and safety of milk products and at the same time deliver those as soon as possible, rapid analysis methods as well as sensitive, reliable, cost-effective, easy-to-use devices and systems for process control and milk spoilage detection are needed. In this paper, we review different rapid methods, sensors and commercial systems for milk spoilage and microorganism detection. The main focus lies on chemical sensors and biosensors for detection/monitoring of the well-known indicators associated with bacterial growth and milk spoilage such as changes in pH value, conductivity/impedance, adenosine triphosphate level, concentration of dissolved oxygen and produced CO₂. These sensors offer several advantages, like high sensitivity, fast response time, minimal sample preparation, miniaturization and ability for real-time monitoring of milk spoilage. In addition, electronic-nose- and electronic-tongue systems for the detection of characteristic volatile and non-volatile compounds related to microbial growth and milk spoilage are described. Finally, wireless sensors and color indicators for intelligent packaging are discussed.

Carbon Nanotube Chemical Sensors

Carbon nanotubes (CNTs) promise to advance a number of real-world technologies. Of these applications, they are particularly attractive for uses in chemical sensors for environmental and health monitoring. However, chemical sensors based on CNTs are often lacking in selectivity, and the elucidation of their sensing mechanisms remains challenging. This review is a comprehensive description of the parameters that give rise to the sensing capabilities of CNT-based sensors and the application of CNT-based devices in chemical sensing. This review begins with the discussion of the sensing mechanisms in CNT-based devices, the chemical methods of CNT functionalization, architectures of sensors, performance parameters, and theoretical models used to describe CNT sensors. It then discusses the expansive applications of CNT-based sensors to multiple areas including environmental monitoring, food and agriculture applications, biological sensors, and national security. The discussion of each analyte focuses on the strategies used to impart selectivity and the molecular interactions between the selector and the analyte. Finally, the review concludes with a brief outlook over future developments in the field of chemical sensors and their prospects for commercialization.

An automated bacterial concentration and recovery system for pre-enrichment required in rapid Escherichia coli detection

One of the biggest challenges in rapid low concentration bacterial detection is the pre-concentration or pre-enrichment, which aims to increase bacteria concentration and reduce sample volume for easy bacterial detection. In practical bacterial detection, large-volume water samples with a pathogenic bacterial concentration of less than 1 CFU/mL have to be tested rapidly. The reported biosensors either have insufficient detection limit or have limited capability of handling a sufficiently large water sample. Therefore, a high-performance automated pre-enrichment process is strongly demanded in rapid practical bacterial detection. In this paper, a practical high performance automated bacterial concentration and recovery system (ABCRS) based on the combination of a ceramic membrane and tangential flow filtration technique was presented with short processing time (less than one hour), low pre-enrichment limit (≤0.005 CFU/mL), high concentration ratio (≥ 500), high recovery efficiency (~ 90%), and small final retentate volume (≤ 5 mL).

QCM-based immunosensor for rapid detection of Salmonella Typhimurium in food

Salmonella Typhimurium is one of the main causes of outbreaks and sporadic cases of human gastroenteritis. At present, the rapid detection of this pathogen is a major goal of biosensing technology applied to food safety. In fact, ISO standardized culture method takes up to ten days to provide a reliable response. In this paper, we describe a relatively simple protocol for detecting Salmonella Typhimurium in chicken meat based on a Quartz-Crystal Microbalance (QCM), which leads to a limit of detection (LOD) less than of 10° CFU/mL and requires a pre-enrichment step lasting only 2 h at 37 °C. The reliability of the proposed immunosensor has been demonstrated through the validation of the experimental results with ISO standardized culture method. The cost-effectiveness of the procedure and the rapidity of the QCM-based biosensor in providing the qualitative response make the analytical method described here suitable for applications in food inspection laboratory and throughout the chain production of food industry.

Novel surfactant peptide for removal of biofilms

Conventional chemical surfactants attach on blots randomly, accompanied with health and environmental issues. To address this, a surfactant peptide was designed to mimic chemical surfactants with an affinity binding peptide as a hydrophobic tail for the cleanup of biofilm contaminations. The micelle forming and structural changes of the peptide in aqueous solution were systematically investigated. More importantly, the biofilm removal efficiency toward Escherichia coli O157:H7 biofilm reached 75% in neutral aqueous solutions at the concentration of 125 mg/L (critical micelle concentration 91 mg/L), a significant improvement in comparison to conventional surfactants and random surfactant peptide. The dynamic removal process reported by confocal laser scanning microscope (CLSM) also displayed the different constituents of biofilm blots, which associated with surfactant peptide binding efficiency. Hopefully, this surfactant strategy will eventually provide new scopes in the design of surface active biological agents.

Microfluidic curved-channel centrifuge for solution exchange of target microparticles and their simultaneous separation from bacteria

One of the common operations in sample preparation is to separate specific particles (e.g. target cells, embryos or microparticles) from non-target substances (e.g. bacteria) in a fluid and to wash them into clean buffers for further processing like detection (called solution exchange in this paper). For instance, solution exchange is widely needed in preparing fluidic samples for biosensing at the point-of-care and point-of-use, but still conducted via the use of cumbersome and time-consuming off-chip analyte washing and purification techniques. Existing small-scale and handheld active and passive devices for washing particles are often limited to very low throughputs or require external sources of energy. Here, we integrated Dean flow recirculation of two fluids in curved microchannels with selective inertial focusing of target particles to develop a microfluidic centrifuge device that can isolate specific particles (as surrogates for target analytes) from bacteria and wash them into a clean buffer at high throughput and efficiency. We could process micron-size particles at a flow rate of 1 mL min-1 and achieve throughputs higher than 104 particles per second. Our results reveal that the device is capable of singleplex solution exchange of 11 μm and 19 μm particles with efficiencies of 86 ± 2% and 93 ± 0.7%, respectively. A purity of 96 ± 2% was achieved in the duplex experiments where 11 μm particles were isolated from 4 μm particles. Application of our device in biological assays was shown by performing duplex experiments where 11 μm or 19 μm particles were isolated from an Escherichia coli bacterial suspension with purities of 91-98%. We envision that our technique will have applications in point-of-care devices for simultaneous purification and solution exchange of cells and embryos from smaller substances in high-volume suspensions at high throughput and efficiency.

Semi-quantitative method for Staphylococci magnetic detection in raw milk

Bovine mastitis is the most costly disease for dairy farmers, hence, control measures to prevent it are crucial for dairy farm sustainability. Staphylococcus aureus is considered a major mastitis pathogen because of its impact on milk quality and low cure rates. Prevention of S. aureus mastitis includes segregation of infected animals, whilst treatment of such animals should be performed for a longer time to improve cure rates. This makes identification of S. aureus infected quarters and animals of significant importance. The experiments reported in this research paper aimed to develop and validate a sensitive method for magnetic detection of S. aureus and of the Staphylococcus genus in raw milk samples. Mastitic milk samples were collected aseptically from 47 cows with subclinical mastitis, from 12 Portuguese dairy farms. Forty nine quarter milk samples were selected based on bacteriological results. All samples were submitted to PCR analysis. In parallel, these milk samples were mixed with a solution combining specific antibodies and magnetic nanoparticles, to be analysed using a lab-on-a-chip magnetoresistive cytometer, with microfluidic sample handling. The antibodies used in this work were a rabbit polyclonal IgG anti-S. aureus ScpA protein and a mouse monoclonal IgM anti-S. aureus ATCC 29740. This paper describes the methodology used for magnetic detection of bacteria, including analysis of false positive/negative results. This immunological recognition was able to detect bacterial presence above 100 cfu/ml, independently of antibody and targeted bacteria used in this work. Comparison with PCR results showed sensitivities of 57·1 and 79·3%, specificity values of 75 and 50%, and PPV values of 40 and 95·8% for magnetic identification of Staphylococci species with an anti-S. aureus antibody and an anti-Staphylococcus spp. antibody, respectively. Some constraints are described as well as the method's limitations in bacterial quantification. Sensitivities and specificities require to be improved, nevertheless, the methodology described may form the basis for a means of identifying S. aureus infected cows at the point of care.

Development of a Droplet Digital Polymerase Chain Reaction for Rapid and Simultaneous Identification of Common Foodborne Pathogens in Soft Cheese

Dairy products can harbor various microorganisms (e.g., Campylobacter spp., Salmonella spp., Listeria monocytogenes, verocytotoxin-producing Escherichia coli) arising from animal reservoirs, and which can become important sources of foodborne illness. Therefore, early detection of food pathogens is crucial to prevent diseases. We wished to develop an accurate quantitative protocol based on a droplet digital polymerase chain reaction (ddPCR) involving eight individual TaqMan™ reactions to detect simultaneously, without selective enrichment, Listeria spp., L. monocytogenes, Salmonella spp., verocytotoxin-producing E. coli and Campylobacter spp. in cheese. ddPCR (a "third-generation PCR") provides absolute quantification of target DNAs without requirement of a standard curve, which simplifies experimentation and data comparability. The accuracy, specificity and sensitivity of the developed ddPCR system were assessed using purified DNA from 50 reference pathogenic and non-pathogenic strains from international or Italian collections and analyzing soft cheese samples artificially contaminated with serial dilutions (from 4 × 106 to 4 × 101 CFU/g) of pure cultures from the American Type Culture Collection. Finally, the performance of our ddPCR system was compared by parallel testing with quantitative PCR: it gave higher sensitivity (102 CFU/g for the Listeria spp. assay) without the necessity of a standard curve. In conclusion, this is the first ddPCR system developed for simultaneous detection of common foodborne pathogens in cheese using a single set of amplification conditions. As such, it could become a useful strategy for high-throughput screening of microorganisms to evaluate the quality and safety of food products.

Fundamentals, achievements and challenges in the electrochemical sensing of pathogens

Electrochemical sensors are powerful tools widely used in industrial, environmental and medical applications. The versatility of electrochemical methods allows for the investigation of chemical composition in real time and in situ. Electrochemical detection of specific biological molecules is a powerful means for detecting disease-related markers. In the last 10 years, highly-sensitive and specific methods have been developed to detect waterborne and foodborne pathogens. In this review, we classify the different electrochemical techniques used for the qualitative and quantitative detection of pathogens. The robustness of electrochemical methods allows for accurate detection even in heterogeneous and impure samples. We present a fundamental description of the three major electrochemical sensing methods used in the detection of pathogens and the advantages and disadvantages of each of these methods. In each section, we highlight recent breakthroughs, including the utilisation of microfluidics, immunomagnetic separation and multiplexing for the detection of multiple pathogens in a single device. We also include recent studies describing new strategies for the design of future immunosensing systems and protocols. The high sensitivity and selectivity, together with the portability and the cost-effectiveness of the instrumentation, enhances the demand for further development in the electrochemical detection of microbes.

Semi-Quantitative Method for Streptococci Magnetic Detection in Raw Milk

Bovine mastitis is the most costly disease for dairy farmers and the most frequent reason for the use of antibiotics in dairy cattle; thus, control measures to detect and prevent mastitis are crucial for dairy farm sustainability. The aim of this study was to develop and validate a sensitive method to magnetically detect Streptococcus agalactiae (a Group B streptococci) and Streptococcus uberis in raw milk samples. Mastitic milk samples were collected aseptically from 44 cows with subclinical mastitis, from 11 Portuguese dairy farms. Forty-six quarter milk samples were selected based on bacterial identification by conventional microbiology. All samples were submitted to PCR analysis. In parallel, these milk samples were mixed with a solution combining specific antibodies and magnetic nanoparticles, to be analyzed using a lab-on-a-chip magnetoresistive cytometer, with microfluidic sample handling. This paper describes a point of care methodology used for detection of bacteria, including analysis of false positive/negative results. This immunological recognition was able to detect bacterial presence in samples spiked above 100 cfu/mL, independently of antibody and targeted bacteria used in this work. Using PCR as a reference, this method correctly identified 73% of positive samples for streptococci species with an anti-S. agalactiae antibody, and 41% of positive samples for an anti-GB streptococci antibody.

Rapid detection of Cronobacter sakazakii by real-time PCR based on the cgcA gene and TaqMan probe with internal amplification control

Cronobacter sakazakii is a severe virulent strain that is frequently detected in powdered infant formula (PIF). Therefore, it is necessary to develop a fast and specific detection method. The specificity of our newly developed quantitative real-time PCR (qRT–PCR) was validated with DNA from 46 strains. Among them, 12 C. sakazakii strains were correctly amplified, whereas no positive florescent signal was observed from 34 nontarget controls. The detection limit of C. sakazakii was about 110 CFU/mL in broth and 1100 CFU/g in PIF. After enrichment in buffered peptone water for 6 h, our developed qRT–PCR assay could reliably detect C. sakazakii when the inoculation level was as low as 2 CFU/25 g (0.08 CFU/g) in PIF. The growth of C. sakazakii could be inhibited by the presence of Lactobacillus pentosus and Bacillus cereus, which used a longer enrichment period before the isolation was accomplished. However, at 5 and 50 CFU/25 g inoculation levels of C. sakazakii in the presence of 4 × 106 CFU L. pentosus/25 g or of 2 × 104 CFU B. cereus/25 g, the qRT–PCR assay could detect the presence of Cronobacter even though these artificially spiked samples were negative in culture. Therefore, our results indicated that the qRT–PCR assay could detect samples containing inhibitors and could avoid false negatives by using an internal amplification control.

Spatial and temporal epidemiological analysis in the Big Data era

Concurrent with global economic development in the last 50 years, the opportunities for the spread of existing diseases and emergence of new infectious pathogens, have increased substantially. The activities associated with the enormously intensified global connectivity have resulted in large amounts of data being generated, which in turn provides opportunities for generating knowledge that will allow more effective management of animal and human health risks. This so-called Big Data has, more recently, been accompanied by the Internet of Things which highlights the increasing presence of a wide range of sensors, interconnected via the Internet. Analysis of this data needs to exploit its complexity, accommodate variation in data quality and should take advantage of its spatial and temporal dimensions, where available. Apart from the development of hardware technologies and networking/communication infrastructure, it is necessary to develop appropriate data management tools that make this data accessible for analysis. This includes relational databases, geographical information systems and most recently, cloud-based data storage such as Hadoop distributed file systems. While the development in analytical methodologies has not quite caught up with the data deluge, important advances have been made in a number of areas, including spatial and temporal data analysis where the spectrum of analytical methods ranges from visualisation and exploratory analysis, to modelling. While there used to be a primary focus on statistical science in terms of methodological development for data analysis, the newly emerged discipline of data science is a reflection of the challenges presented by the need to integrate diverse data sources and exploit them using novel data- and knowledge-driven modelling methods while simultaneously recognising the value of quantitative as well as qualitative analytical approaches. Machine learning regression methods, which are more robust and can handle large datasets faster than classical regression approaches, are now also used to analyse spatial and spatio-temporal data. Multi-criteria decision analysis methods have gained greater acceptance, due in part, to the need to increasingly combine data from diverse sources including published scientific information and expert opinion in an attempt to fill important knowledge gaps. The opportunities for more effective prevention, detection and control of animal health threats arising from these developments are immense, but not without risks given the different types, and much higher frequency, of biases associated with these data.