Lantibiotic Nisin and Its Detection Methods

The type A lantibiotic nisin produced by several Lactococcus lactis strains, and one Streptococcus uberis strainis a small antimicrobial peptide that inhibits the growth of a wide range of gram-positive bacteria, such as Bacillus, Clostridium, Listeria and Staphylococcus species. It is nontoxic to humans and used as a food preservative (E234) in more than 50 countries including the EU, the USA, and China. National legislations concerning maximum addition levels of nisin in different foods vary greatly. Therefore, there is a demand for non-laborious and sensitive methods to identify and quantify nisin reliably from different food matrices. The horizontal inhibition assay, based on the inhibitory effect of nisin to Micrococcus luteus is the base for most quantification methods developed so far. However, the sensitivity and accuracy of the agar diffusion method is affected by several parameters. Immunological tests have also been described. Taken into account the sensitivity of immunological methods to interfering substances within sample matrices, and possible cross-reactivities with lantibiotics structurally close to nisin, their usefulness for nisin detection from food samples remains limited. The proteins responsible for nisin biosynthesis, and producer self-immunity are encoded by genes arranged into two inducible operons, nisA/Z/QBTCIPRK and nisFEG, which also contain internal, constitutive promoters PnisI and PnisR. The transmembrane histidine kinase NisK and the response regulator NisR form a two-component signal transduction system, in which NisK autophosphorylates after exposure to extra cellular nisin, and subsequently transfers the phosphate to NisR. The phosphorylated NisR then relays the signal downstream by binding to two regulated promoters in the nisin gene cluster, i.e the nisA/Z/Qand the nisF promoters, thus activating transcription of the structural gene nisA/Z/Q and the downstream genes nisBTCIPRK from the nisA/Z/Q promoter, and the genes nisFEG from the nisF promoter. In this work two novel and highly sensitive nisin bioassays were developed. Both of these quantification methods were based on NisRK mediated, nisin induced Green Fluorescent Protein (GFP) fluorescence. The suitabilities of these assays for quantifica¬tion of nisin from food samples were evaluated in several food matrices. These bioassays had nisin sensitivities in the nanogram or picogram levels. In addition, shelf life of nisin in cooked sausages and retainment of the induction activity of nisin in intestinal chyme (intestinal content) was assessed.

Evolution and detection of cyanobacterial hepatotoxin synthetase genes

Mass occurrences (blooms) of cyanobacteria are common in aquatic environments worldwide. These blooms are often toxic, due to the presence of hepatotoxins or neurotoxins. The most common cyanobacterial toxins are hepatotoxins: microcystins and nodularins. In freshwaters, the main producers of microcystins are Microcystis, Anabaena, and Planktothrix. Nodularins are produced by strains of Nodularia spumigena in brackish waters. Toxic and nontoxic strains of cyanobacteria co-occur and cannot be differentiated by conventional microscopy. Molecular biological methods based on microcystin and nodularin synthetase genes enable detection of potentially hepatotoxic cyanobacteria. In the present study, molecular detection methods for hepatotoxin-producing cyanobacteria were developed, based on microcystin synthetase gene E (mcyE) and the orthologous nodularin synthetase gene F (ndaF) sequences. General primers were designed to amplify the mcyE/ndaF gene region from microcystin-producing Anabaena, Microcystis, Planktothrix, and Nostoc, and nodularin-producing Nodularia strains. The sequences were used for phylogenetic analyses to study how cyanobacterial mcy genes have evolved. The results showed that mcy genes and microcystin are very old and were already present in the ancestor of many modern cyanobacterial genera. The results also suggested that the sporadic distribution of biosynthetic genes in modern cyanobacteria is caused by repeated gene losses in the more derived lineages of cyanobacteria and not by horizontal gene transfer. Phylogenetic analysis also proposed that nda genes evolved from mcy genes. The frequency and composition of the microcystin producers in 70 lakes in Finland were studied by conventional polymerase chain reaction (PCR). Potential microcystin producers were detected in 84% of the lakes, using general mcyE primers, and in 91% of the lakes with the three genus-specific mcyE primers. Potential microcystin-producing Microcystis were detected in 70%, Planktothrix in 63%, and Anabaena in 37% of the lakes. The presence and co-occurrence of potential microcystin producers were more frequent in eutrophic lakes, where the total phosphorus concentration was high. The PCR results could also be associated with various environmental factors by correlation and regression analyses. In these analyses, the total nitrogen concentration and pH were both associated with the presence of multiple microcystin-producing genera and partly explained the probability of occurrence of mcyE genes. In general, the results showed that higher nutrient concentrations increased the occurrence of potential microcystin producers and the risk for toxic bloom formation. Genus-specific probe pairs for microcystin-producing Anabaena, Microcystis, Planktothrix, and Nostoc, and nodularin-producing Nodularia were designed to be used in a DNA-chip assay. The DNA-chip can be used to simultaneously detect all these potential microcystin/nodularin producers in environmental water samples. The probe pairs detected the mcyE/ndaF genes specifically and sensitively when tested with cyanobacterial strains. In addition, potential microcystin/nodularin producers were identified in lake and Baltic Sea samples by the DNA-chip almost as sensitively as by quantitative real-time PCR (qPCR), which was used to validate the DNA-chip results. Further improvement of the DNA-chip assay was achieved by optimization of the PCR, the first step in the assay. Analysis of the mcy and nda gene clusters from various hepatotoxin-producing cyanobacteria was rewarding; it revealed that the genes were ancient. In addition, new methods detecting all the main producers of hepatotoxins could be developed. Interestingly, potential microcystin-producing cyanobacterial strains of Microcystis, Planktothrix, and Anabaena, co-occurred especially in eutrophic and hypertrophic lakes. Protecting waters from eutrophication and restoration of lakes may thus decrease the prevalence of toxic cyanobacteria and the frequency of toxic blooms.

Detection of a putative hemolysin operon, hhdBA, of Haemophilus parasuis from pigs with Glasser disease

The aim of the current study was to investigate whether polymerase chain reaction amplification of 16S ribosomal (r)RNA and a putative hemolysin gene operon, hhdBA, can be used to monitor live pigs for the presence of Haemophilus parasuis and predict the virulence of the strains present. Nasal cavity swabs were taken from 30 live, healthy, 1- to 8-week-old pigs on a weekly cycle from a commercial Thai nursery pig herd. A total of 27 of these pigs (90%) tested positive for H. parasuis as early as week 1 of age. None of the H. parasuis-positive samples from healthy pigs was positive for the hhdBA genes. At the same pig nursery, swab samples from nasal cavity, tonsil, trachea, and lung, and exudate samples from pleural/peritoneal cavity were taken from 30 dead pigs displaying typical pathological lesions consistent with Glasser disease. Twenty-two of 140 samples (15.7%) taken from 30 diseased pigs yielded a positive result for H. parasuis. Samples from the exudate (27%) yielded the most positive results, followed by lung, tracheal swab, tonsil, and nasal swab, respectively. Out of 22 positive samples, 12 samples (54.5%) harbored hhdA and/or hhdB genes. Detection rates of hhdA were higher than hhdB. None of the H. parasuis-positive samples taken from nasal cavity of diseased pigs tested positive for hhdBA genes. More work is required to determine if the detection of hhdBA genes is useful for identifying the virulence potential of H. parasuis field isolates.

Autonomous UAVs wildlife detection using thermal imaging, predictive navigation and computer vision

There is an increased interest on the use of Unmanned Aerial Vehicles (UAVs) for wildlife and feral animal monitoring around the world. This paper describes a novel system which uses a predictive dynamic application that places the UAV ahead of a user, with a low cost thermal camera, a small onboard computer that identifies heat signatures of a target animal from a predetermined altitude and transmits that target’s GPS coordinates. A map is generated and various data sets and graphs are displayed using a GUI designed for easy use. The paper describes the hardware and software architecture and the probabilistic model for downward facing camera for the detection of an animal. Behavioral dynamics of target movement for the design of a Kalman filter and Markov model based prediction algorithm are used to place the UAV ahead of the user. Geometrical concepts and Haversine formula are applied to the maximum likelihood case in order to make a prediction regarding a future state of the user, thus delivering a new way point for autonomous navigation. Results show that the system is capable of autonomously locating animals from a predetermined height and generate a map showing the location of the animals ahead of the user.

Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

MPC controlled multirotor with suspended slung load: System architecture and visual load detection

There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

Modern techniques in detection, identification and quantification of bacteria and peptides from foods

Standards have been placed to regulate the microbial and preservative contents to assure that foods are safe to the consumer. In a case of a food-related disease outbreak, it is crucial to be able to detect and identify quickly and accurately the cause of the disease. In addition, for every day control of food microbial and preservative contents, the detection methods must be easily performed for numerous food samples. In this present study, quicker alternative methods were studied for identification of bacteria by DNA fingerprinting. A flow cytometry method was developed as an alternative to pulsed-field gel electrophoresis, the golden method . DNA fragment sizing by an ultrasensitive flow cytometer was able to discriminate species and strains in a reproducible and comparable manner to pulsed-field gel electrophoresis. This new method was hundreds times faster and 200,000 times more sensitive. Additionally, another DNA fingerprinting identification method was developed based on single-enzyme amplified fragment length polymorphism (SE-AFLP). This method allowed the differentiation of genera, species, and strains of pathogenic bacteria of Bacilli, Staphylococci, Yersinia, and Escherichia coli. These fingerprinting patterns obtained by SE-AFLP were simpler and easier to analyze than those by the traditional amplified fragment length polymorphism by double enzyme digestion. Nisin (E234) is added as a preservative to different types of foods, especially dairy products, around the world. Various detection methods exist for nisin, but they lack in sensitivity, speed or specificity. In this present study, a sensitive nisin-induced green fluorescent protein (GFPuv) bioassay was developed using the Lactococcus lactis two-component signal system NisRK and the nisin-inducible nisA promoter. The bioassay was extremely sensitive with detection limit of 10 pg/ml in culture supernatant. In addition, it was compatible for quantification from various food matrices, such as milk, salad dressings, processed cheese, liquid eggs, and canned tomatoes. Wine has good antimicrobial properties due to its alcohol concentration, low pH, and organic content and therefore often assumed to be microbially safe to consume. Another aim of this thesis was to study the microbiota of wines returned by customers complaining of food-poisoning symptoms. By partial 16S rRNA gene sequence analysis, ribotyping, and boar spermatozoa motility assay, it was identified that one of the wines contained a Bacillus simplex BAC91, which produced a heat-stable substance toxic to the mitochondria of sperm cells. The antibacterial activity of wine was tested on the vegetative cells and spores of B. simplex BAC91, B. cereus type strain ATCC 14579 and cereulide-producing B. cereus F4810/72. Although the vegetative cells and spores of B. simplex BAC91 were sensitive to the antimicrobial effects of wine, the spores of B. cereus strains ATCC 14579 and F4810/72 stayed viable for at least 4 months. According to these results, Bacillus spp., more specifically spores, can be a possible risk to the wine consumer.

DNA-based detection and characterisation of strictly anaerobic beer-spoilage bacteria

Megasphaera cerevisiae, Pectinatus cerevisiiphilus, Pectinatus frisingensis, Selenomonas lacticifex, Zymophilus paucivorans and Zymophilus raffinosivorans are strictly anaerobic Gram-stain-negative bacteria that are able to spoil beer by producing off-flavours and turbidity. They have only been isolated from the beer production chain. The species are phylogenetically affiliated to the Sporomusa sub-branch in the class "Clostridia". Routine cultivation methods for detection of strictly anaerobic bacteria in breweries are time-consuming and do not allow species identification. The main aim of this study was to utilise DNA-based techniques in order to improve detection and identification of the Sporomusa sub-branch beer-spoilage bacteria and to increase understanding of their biodiversity, evolution and natural sources. Practical PCR-based assays were developed for monitoring of M. cerevisiae, Pectinatus species and the group of Sporomusa sub-branch beer spoilers throughout the beer production process. The developed assays reliably differentiated the target bacteria from other brewery-related microbes. The contaminant detection in process samples (10 1,000 cfu/ml) could be accomplished in 2 8 h. Low levels of viable cells in finished beer (≤10 cfu/100 ml) were usually detected after 1 3 d culture enrichment. Time saving compared to cultivation methods was up to 6 d. Based on a polyphasic approach, this study revealed the existence of three new anaerobic spoilage species in the beer production chain, i.e. Megasphaera paucivorans, Megasphaera sueciensis and Pectinatus haikarae. The description of these species enabled establishment of phenotypic and DNA-based methods for their detection and identification. The 16S rRNA gene based phylogenetic analysis of the Sporomusa sub-branch showed that the genus Selenomonas originates from several ancestors and will require reclassification. Moreover, Z. paucivorans and Z. raffinosivorans were found to be in fact members of the genus Propionispira. This relationship implies that they were carried to breweries along with plant material. The brewery-related Megasphaera species formed a distinct sub-group that did not include any sequences from other sources, suggesting that M. cerevisiae, M. paucivorans and M. sueciensis may be uniquely adapted to the brewery ecosystem. M. cerevisiae was also shown to exhibit remarkable resistance against many brewery-related stress conditions. This may partly explain why it is a brewery contaminant. This study showed that DNA-based techniques provide useful tools for obtaining more rapid and specific information about the presence and identity of the strictly anaerobic spoilage bacteria in the beer production chain than is possible using cultivation methods. This should ensure financial benefits to the industry and better product quality to customers. In addition, DNA-based analyses provided new insight into the biodiversity as well as natural sources and relations of the Sporomusa sub-branch bacteria. The data can be exploited for taxonomic classification of these bacteria and for surveillance and control of contaminations.

Lactic acid bacteria and their antimicrobial peptides : Induction,detection,partial characterization, and potential applications

Bacteriocin-producing lactic acid bacteria and their isolated peptide bacteriocins are of value to control pathogens and spoiling microorganisms in foods and feed. Nisin is the only bacteriocin that is commonly accepted as a food preservative and has a broad spectrum of activity against Gram-positive organisms including spore forming bacteria. In this study nisin induction was studied from two perspectives, induction from inside of the cell and selection of nisin inducible strains with increased nisin induction sensitivity. The results showed that a mutation in the nisin precursor transporter NisT rendered L. lactis incapable of nisin secretion and lead to nisin accumulation inside the cells. Intracellular proteolytic activity could cleave the N-terminal leader peptide of nisin precursor, resulting in active nisin in the cells. Using a nisin sensitive GFP bioassay it could be shown, that the active intracellular nisin could function as an inducer without any detectable release from the cells. The results suggested that nisin can be inserted into the cytoplasmic membrane from inside the cell and activate NisK. This model of two-component regulation may be a general mechanism of how amphiphilic signals activate the histidine kinase sensor and would represent a novel way for a signal transduction pathway to recognize its signal. In addition, nisin induction was studied through the isolation of natural mutants of the GFPuv nisin bioassay strain L. lactis LAC275 using fl uorescence-activated cell sorting (FACS). The isolated mutant strains represent second generation of GFPuv bioassay strains which can allow the detection of nisin at lower levels. The applied aspect of this thesis was focused on the potential of bacteriocins in chicken farming. One aim was to study nisin as a potential growth promoter in chicken feed. Therefore, the lactic acid bacteria of chicken crop and the nisin sensitivity of the isolated strains were tested. It was found that in the crop Lactobacillus reuteri, L. salivarius and L. crispatus were the dominating bacteria and variation in nisin resistance level of these strains was found. This suggested that nisin may be used as growth promoter without wiping out the dominating bacterial species in the crop. As the isolated lactobacilli may serve as bacteria promoting chicken health or reducing zoonoosis and bacteriocin production is one property associated with probiotics, the isolated strains were screened for bacteriocin activity against the pathogen Campylobacter jejuni. The results showed that many of the isolated L. salivarius strains could inhibit the growth of C. jejuni. The bacteriocin of the L. salivarius LAB47 strain, with the strongest activity, was further characterized. Salivaricin 47 is heat-stable and active in pH range 3 to 8, and the molecular mass was estimated to be approximately 3.2 kDa based on tricine SDS-PAGE analysis.

Decision trees for detection of activity intensity in youth with cerebral palsy

PURPOSE To develop and test decision tree (DT) models to classify physical activity (PA) intensity from accelerometer output and Gross Motor Function Classification System (GMFCS) classification level in ambulatory youth with cerebral palsy (CP); and 2) compare the classification accuracy of the new DT models to that achieved by previously published cut-points for youth with CP. METHODS Youth with CP (GMFCS Levels I - III) (N=51) completed seven activity trials with increasing PA intensity while wearing a portable metabolic system and ActiGraph GT3X accelerometers. DT models were used to identify vertical axis (VA) and vector magnitude (VM) count thresholds corresponding to sedentary (SED) (<1.5 METs), light PA (LPA) (>/=1.5 and <3 METs) and moderate-to-vigorous PA (MVPA) (>/=3 METs). Models were trained and cross-validated using the 'rpart' and 'caret' packages within R. RESULTS For the VA (VA_DT) and VM decision trees (VM_DT), a single threshold differentiated LPA from SED, while the threshold for differentiating MVPA from LPA decreased as the level of impairment increased. The average cross-validation accuracy for the VC_DT was 81.1%, 76.7%, and 82.9% for GMFCS levels I, II, and III, respectively. The corresponding cross-validation accuracy for the VM_DT was 80.5%, 75.6%, and 84.2%, respectively. Within each GMFCS level, the decision tree models achieved better PA intensity recognition than previously published cut-points. The accuracy differential was greatest among GMFCS level III participants, in whom the previously published cut-points misclassified 40% of the MVPA activity trials. CONCLUSION GMFCS-specific cut-points provide more accurate assessments of MVPA levels in youth with CP across the full spectrum of ambulatory ability.

A simple, one-tube assay for the simultaneous detection and diagnosis of ten Australian poultry Eimeria

Coccidiosis is a costly worldwide enteric disease of chickens caused by parasites of the genus Eimeria. At present, there are seven described species that occur globally and a further three undescribed, operational taxonomic units (OTUs X, Y, and Z) that are known to infect chickens from Australia. Species of Eimeria have both overlapping morphology and pathology and frequently occur as mixed-species infections. This makes definitive diagnosis with currently available tests difficult and, to date, there is no test for the detection of the three OTUs. This paper describes the development of a PCR-based assay that is capable of detecting all ten species of Eimeria, including OTUs X, Y, and Z in field samples. The assay is based on a single set of generic primers that amplifies a single diagnostic fragment from the mitochondrial genome of each species. This one-tube assay is simple, low-cost, and has the capacity to be high throughput. It will therefore be of great benefit to the poultry industry for Eimeria detection and control, and the confirmation of identity and purity of vaccine strains.

An improved real-time PCR assay for the detection of Old World screwworm flies

The Old World screwworm (OWS) fly, Chrysomya bezziana, is a serious pest of livestock, wildlife and humans in tropical Africa, parts of the Middle East, the Indian subcontinent, south-east Asia and Papua New Guinea. Although to date Australia remains free of OWS flies, an incursion would have serious economic and animal welfare implications. For these reasons Australia has an OWS fly preparedness plan including OWS fly surveillance with fly traps. The recent development of an improved OWS fly trap and synthetic attractant and a specific and sensitive real-time PCR molecular assay for the detection of OWS flies in trap catches has improved Australia's OWS fly surveillance capabilities. Because all Australian trap samples gave negative results in the PCR assay, it was deemed necessary to include a positive control mechanism to ensure that fly DNA was being successfully extracted and amplified and to guard against false negative results. A new non-competitive internal amplification control (IAC) has been developed that can be used in conjunction with the OWS fly PCR assay in a multiplexed single-tube reaction. The multiplexed assay provides an indicator of the performance of DNA extraction and amplification without greatly increasing labour or reagent costs. The fly IAC targets a region of the ribosomal 16S mitochondrial DNA which is conserved across at least six genera of commonly trapped flies. Compared to the OWS fly assay alone, the multiplexed OWS fly and fly IAC assay displayed no loss in sensitivity or specificity for OWS fly detection. The multiplexed OWS fly and fly IAC assay provides greater confidence for trap catch samples returning negative OWS fly results. © 2014 International Atomic Energy Agency.

Cattle herd inspections and fly trapping for the detection of the Old World screw-worm fly (Chrysomya bezziana)

ObjectivesTo compare the sensitivity of inspections of cattle herds and adult fly trapping for detection of the Old World screw-worm fly (OWS). ProceduresThe incidence of myiases on animals and the number of OWS trapped with LuciTrap (R)/Bezzilure were measured concurrently on cattle farms on Sumba Island (Indonesia) and in peninsular Malaysia (two separate periods for the latter). The numbers of animal inspections and traps required to achieve OWS detection at the prevalent fly densities were calculated. ResultsOn Sumba Island, with low-density OWS populations, the sensitivity of herd inspections and of trapping for OWS detection was 0.30 and 0.85, respectively. For 95% confidence of detecting OWS, either 45 inspections of 74 animals or trapping with 5 sets of 4 LuciTraps for 14 days are required. In Malaysia, at higher OWS density, herd inspections of 600 animals (twice weekly, period 1) or 1600 animals (weekly, period 2) always detected myiases (sensitivity = 1), while trapping had sensitivities of 0.89 and 0.64 during periods 1 and 2, respectively. For OWS detection with 95% confidence, fewer than 600 and 1600 animals or 2 and 6 LuciTraps are required in periods 1 and 2, respectively. ConclusionsInspections of cattle herds and trapping with LuciTrap and Bezzilure can detect OWS populations. As a preliminary guide for OWS detection in Australia, the numbers of animals and traps derived from the Sumba Island trial should be used because the prevailing conditions better match those of northern Australia.

Quick abnormal-bid-detection method for construction contract auctions

Non-competitive bids have recently become a major concern in both Public and Private sector construction contract auctions. Consequently, several models have been developed to help identify bidders potentially involved in collusive practices. However, most of these models require complex calculations and extensive information that is difficult to obtain. The aim of this paper is to utilize recent developments for detecting abnormal bids in capped auctions (auctions with an upper bid limit set by the auctioner) and extend them to the more conventional uncapped auctions (where no such limits are set). To accomplish this, a new method is developed for estimating the values of bid distribution supports by using the solution to what has become known as the German tank problem. The model is then demonstrated and tested on a sample of real construction bid data and shown to detect cover bids with high accuracy. This work contributes to an improved understanding of abnormal bid behavior as an aid to detecting and monitoring potential collusive bid practices.