Use of an electronic nose to diagnose Mycobacterium bovis infection in badgers and cattle

Metrisor: A novel diagnostic method for metritis detection in cattle based on machine learning and sensors

The Metrisor device has been developed using gas sensors for rapid, highly accurate and effective diagnosis of metritis. 513 cattle uteri were collected from abattoirs and swabs were taken for microbiological testing. The Metrisor device was used to measure intrauterine gases. The results showed a bacterial growth rate of 75.75 % in uteri with clinical metritis. In uteri positive for clinical metritis, the most commonly isolated and identified bacteria were Trueperella pyogenes, Fusobacterium necrophorum and Escherichia coli. Measurements taken with Metrisor to determine the presence of metritis in the uterus yielded the most successful results in evaluations of relevant machine learning algorithms. The ICO (Iterative Classifier Optimizer) algorithm achieved 71.22 % accuracy, 64.40 % precision and 71.20 % recall. Experiments were conducted to examine bacterial growth in the uterus and the random forest algorithm produced the most successful results with accuracy, precision and recall values of 78.16 %, 75.30 % and 78.20 % respectively. ICO also showed high performance in experiments to determine bacterial growth in metritis-positive uteri, with accuracy, precision and recall values of 78.97 %, 77.20 % and 79.00 %, respectively. In conclusion, the Metrisor device demonstrated high accuracy in detecting metritis and bacterial growth in uteri and could identify bacteria such as E. coli, S. aureus, coagulase-negative staphylococci, T. pyogenes, Bacillus spp., Clostridium spp. and F. necrophorum with rates up to 80 %. It provides a reliable, rapid and effective means of detecting metritis in animals in the field without the need for laboratory facilities.

Meeting Contemporary Challenges: Development of Nanomaterials for Veterinary Medicine

In recent decades, nanotechnology has been rapidly advancing in various fields of human activity, including veterinary medicine. The review presents up-to-date information on recent advancements in nanotechnology in the field and an overview of the types of nanoparticles used in veterinary medicine and animal husbandry, their characteristics, and their areas of application. Currently, a wide range of nanomaterials has been implemented into veterinary practice, including pharmaceuticals, diagnostic devices, feed additives, and vaccines. The application of nanoformulations gave rise to innovative strategies in the treatment of animal diseases. For example, antibiotics delivered on nanoplatforms demonstrated higher efficacy and lower toxicity and dosage requirements when compared to conventional pharmaceuticals, providing a possibility to solve antibiotic resistance issues. Nanoparticle-based drugs showed promising results in the treatment of animal parasitoses and neoplastic diseases. However, the latter area is currently more developed in human medicine. Owing to the size compatibility, nanomaterials have been applied as gene delivery vectors in veterinary gene therapy. Veterinary medicine is at the forefront of the development of innovative nanovaccines inducing both humoral and cellular immune responses. The paper provides a brief overview of current topics in nanomaterial safety, potential risks associated with the use of nanomaterials, and relevant regulatory aspects.

Detection of Mycobacterium tuberculosis complex field infections in cattle using fecal volatile organic compound analysis through gas chromatography-ion mobility spectrometry combined with chemometrics

Bovine tuberculosis is considered a re-emerging disease caused by different species from the Mycobacterium tuberculosis complex (MTC), important not only for the livestock sector but also for public health due to its zoonotic character. Despite the numerous efforts that have been carried out to improve the performance of the current antemortem diagnostic procedures, nowadays, they still pose several drawbacks, such as moderate to low sensitivity, highlighting the necessity to develop alternative and innovative tools to complement control and surveillance frameworks. Volatilome analysis is considered an innovative approach which has been widely employed in animal science, including animal health field and diagnosis, due to the useful and interesting information provided by volatile metabolites. Therefore, this study assesses the potential of gas chromatography coupled to ion mobility spectrometry (GC-IMS) to discriminate cattle naturally infected (field infections) by MTC from non-infected animals. Volatile organic compounds (VOCs) produced from feces were analyzed, employing the subsequent information through chemometrics. After the evaluation of variable importance for the projection of compounds, the final discriminant models achieved a robust performance in cross-validation, as well as high percentages of correct classification (>90%) and optimal data of sensitivity (91.66%) and specificity (99.99%) in external validation. The tentative identification of some VOCs revealed some coincidences with previous studies, although potential new compounds associated with the discrimination of infected and non-infected subjects were also addressed. These results provide strong evidence that a volatilome analysis of feces through GC-IMS coupled to chemometrics could become a valuable methodology to discriminate the infection by MTC in cattle. IMPORTANCE Bovine tuberculosis is endemic in many countries worldwide and poses important concerns for public health because of their zoonotic condition. However, current diagnostic techniques present several hurdles, such as low sensitivity and complexity, among others. In this regard, the development of new approaches to improve the diagnosis and control of this disease is considered crucial. Volatile organic compounds are small molecular mass metabolites which compose volatilome, whose analysis has been widely employed with success in different areas of animal science including animal health. The present study seeks to evaluate the combination of fecal volatilome analysis with chemometrics to detect field infections by bovine tuberculosis (Mycobacterium tuberculosis complex) in cattle. The good robust performance of discriminant models as well as the optimal data of sensitivity and specificity achieved highlight volatilome analysis as an innovative approach with huge potential.

Physiology and Biomarkers for Surveillance of Occupational Lung Disease

Respiratory surveillance is the process whereby a group of exposed workers are regularly tested (or screened) for those lung diseases which occur as a result of a specific work exposure. Surveillance is performed by assessing various measures of biological or pathological processes (or biomarkers) for change over time. These traditionally include questionnaires, lung physiological assessments (especially spirometry), and imaging. Early detection of pathological processes or disease can enable removal of a worker from a potentially harmful exposure at an early stage. In this article, we summarize the physiological biomarkers currently used for respiratory surveillance, while commenting on differences in interpretative strategies between different professional groups. We also briefly review the many new techniques which are currently being assessed for respiratory surveillance in prospective research studies and which are likely to significantly broaden and enhance this field in the near future.

Perspectives of digital agriculture in diverse types of livestock supply chain systems. Making sense of uses and benefits

Digital technology is being introduced to global agriculture in a wide variety of forms that are collectively known as digital agriculture. In this paper we provide opportunities and value propositions of how this is occurring in livestock production systems, with a consistent emphasis on technology relating to animal health, animal welfare, and product quality for value creation. This is achieved by organizing individual accounts of digital agriculture in livestock systems according to four broad types-commodity-based; value seeking; subsistence and nature-based. Each type presents contrasting modes of value creation in downstream processing; as well as from the perspective of One Health. The ideal result of digital technology adoption is an equitable and substantial diversification of supply chains, increased monetization of animal product quality, and more sensitive management to meet customer demands and environmental threats. Such changes have a significance beyond the immediate value generated because they indicate endogenous growth in livestock systems, and may concern externalities imposed by the pursuit of purely commercial ends.

Study on the Discrimination of Possible Error Sources That Might Affect the Quality of Volatile Organic Compounds Signature in Dairy Cattle Using an Electronic Nose

Simple Summary

In recent decades, remarkable progress in the development of electronic nose (EN) technologies, particularly for disease detection, has been accomplished through the disclosure of novel methods and associated devices, mainly for the detection of volatile organic compounds (VOCs). Herein, we assessed the ability of a novel EN technology (MENT-EGAS prototype) to respond to direct sampling and to evaluate the influence of possible error sources that might affect the quality of VOC signatures. Principal Component Analyses (PCA) evidenced the presence in the analyzed samples of sufficient information to consent the discrimination of different environmental backgrounds, feed headspaces and exhalated breath between two groups of cows fed with two different types of feed. Moreover, discrimination was also observed within the same group between exhalated breaths sampled before and after feed intake. Based on these findings, we provided evidence that the MENT-EGAS prototype can identify error sources with accuracy. Livestock precision farming technologies are powerful tools for monitoring animal health and welfare parameters in a continuous and automated way.

Abstract

Electronic nose devices (EN) have been developed for detecting volatile organic compounds (VOCs). This study aimed to assess the ability of the MENT-EGAS prototype-based EN to respond to direct sampling and to evaluate the influence of possible error sources that might affect the quality of VOC signatures. This study was performed on a dairy farm using 11 (n = 11) multiparous Holstein-Friesian cows. The cows were divided into two groups housed in two different barns: group I included six lactating cows fed with a lactating diet (LD), and group II included 5 non-lactating late pregnant cows fed with a far-off diet (FD). Each group was offered 250 g of their respective diet; 10 min later, exhalated breath was collected for VOC determination. After this sampling, 4 cows from each group were offered 250 g of pellet concentrates. Ten minutes later, the exhalated breath was collected once more. VOCs were also measured directly from the feed’s headspace, as well as from the environmental backgrounds of each. Principal component analyses (PCA) were performed and revealed clear discrimination between the two different environmental backgrounds, the two different feed headspaces, the exhalated breath of groups I and II cows, and the exhalated breath within the same group of cows before and after the feed intake. Based on these findings, we concluded that the MENT-EGAS prototype can recognize several error sources with accuracy, providing a novel EN technology that could be used in the future in precision livestock farming.

In-Field Detection of American Foulbrood (AFB) by Electric Nose Using Classical Classification Techniques and Sequential Neural Networks

American foulbrood is a dangerous bee disease that attacks the sealed brood. It quickly leads to the death of bee colonies. Efficient diagnosis of this disease is essential. As specific odours are produced when larvae rot, it was investigated whether an electronic nose can distinguish between colonies affected by American foulbrood and healthy ones. The experiment was conducted in an apiary with 18 bee families, 9 of which showed symptoms of the disease confirmed by laboratory diagnostics. Three units of the Beesensor V.2 device based on an array of six semiconductor TGS gas sensors, manufactured by Figaro, were tested. Each copy of the device was tested in all bee colonies: sick and healthy. The measurement session per bee colony lasted 40 min and yielded results from four 10 min measurements. One 10-min measurement consisted of a 5 min regeneration phase and a 5 min object-measurement phase. For the experiments, we used both classical classification methods such as k-nearest neighbour, Naive Bayes, Support Vector Machine, discretized logistic regression, random forests, and committee of classifiers, that is, methods based on extracted representative data fragments. We also used methods based on the entire 600 s series, in this study of sequential neural networks. We considered, in this study, six options for data preparation as part of the transformation of data series into representative results. Among others, we used single stabilised sensor readings as well as average values from stable areas. For verifying the quality of the classical classifiers, we used the 25-fold train-and-test method. The effectiveness of the tested methods reached a threshold of 75 per cent, with results stable between 65 and 70 per cent. As an element to confirm the possibility of class separation using an artificial nose, we used applied visualisations of classes. It is clear from the experiments conducted that the artificial nose tested has practical potential. Our experiments show that the approach to the problem under study by sequential network learning on a sequence of data is comparable to the best classical methods based on discrete data samples. The results of the experiment showed that the Beesensor V.2 along with properly selected classification techniques can become a tool to facilitate rapid diagnosis of American foulbrood under field conditions.

Odors and cancer: Current status and future directions

Cancer is the second leading cause of death in the world. Because tumors detected at early stages are easier to treat, the search for biomarkers-especially non-invasive ones-that allow early detection of malignancies remains a central goal to reduce cancer mortality. Cancer, like other pathologies, often alters body odors, and much has been done by scientists over the last few decades to assess the value of volatile organic compounds (VOCs) as signatures of cancers. We present here a quantitative review of 208 studies carried out between 1984 and 2020 that explore VOCs as potential biomarkers of cancers. We analyzed the main findings of these studies, listing and classifying VOCs related to different cancer types while considering both sampling methods and analysis techniques. Considering this synthesis, we discuss several of the challenges and the most promising prospects of this research direction in the war against cancer.

A Comprehensive Overview of Technologies for Species and Habitat Monitoring and Conservation

The range of technologies currently used in biodiversity conservation is staggering, with innovative uses often adopted from other disciplines and being trialed in the field. We provide the first comprehensive overview of the current (2020) landscape of conservation technology, encompassing technologies for monitoring wildlife and habitats, as well as for on-the-ground conservation management (e.g., fighting illegal activities). We cover both established technologies (routinely deployed in conservation, backed by substantial field experience and scientific literature) and novel technologies or technology applications (typically at trial stage, only recently used in conservation), providing examples of conservation applications for both types. We describe technologies that deploy sensors that are fixed or portable, attached to vehicles (terrestrial, aquatic, or airborne) or to animals (biologging), complemented with a section on wildlife tracking. The last two sections cover actuators and computing (including web platforms, algorithms, and artificial intelligence).

Application of Volatilome Analysis to the Diagnosis of Mycobacteria Infection in Livestock

Volatile organic compounds (VOCs) are small molecular mass metabolites which compose the volatilome, whose analysis has been widely employed in different areas. This innovative approach has emerged in research as a diagnostic alternative to different diseases in human and veterinary medicine, which still present constraints regarding analytical and diagnostic sensitivity. Such is the case of the infection by mycobacteria responsible for tuberculosis and paratuberculosis in livestock. Although eradication and control programs have been partly managed with success in many countries worldwide, the often low sensitivity of the current diagnostic techniques against Mycobacterium bovis (as well as other mycobacteria from Mycobacterium tuberculosis complex) and Mycobacterium avium subsp. paratuberculosis together with other hurdles such as low mycobacteria loads in samples, a tedious process of microbiological culture, inhibition by many variables, or intermittent shedding of the mycobacteria highlight the importance of evaluating new techniques that open different options and complement the diagnostic paradigm. In this sense, volatilome analysis stands as a potential option because it fulfills part of the mycobacterial diagnosis requirements. The aim of the present review is to compile the information related to the diagnosis of tuberculosis and paratuberculosis in livestock through the analysis of VOCs by using different biological matrices. The analytical techniques used for the evaluation of VOCs are discussed focusing on the advantages and drawbacks offered compared with the routine diagnostic tools. In addition, the differences described in the literature among in vivo and in vitro assays, natural and experimental infections, and the use of specific VOCs (targeted analysis) and complete VOC pattern (non-targeted analysis) are highlighted. This review emphasizes how this methodology could be useful in the problematic diagnosis of tuberculosis and paratuberculosis in livestock and poses challenges to be addressed in future research.

Diagnosis of tuberculosis in wildlife: a systematic review

Animal tuberculosis (TB) is a multi-host disease caused by members of the Mycobacterium tuberculosis complex (MTC). Due to its impact on economy, sanitary standards of milk and meat industry, public health and conservation, TB control is an actively ongoing research subject. Several wildlife species are involved in the maintenance and transmission of TB, so that new approaches to wildlife TB diagnosis have gained relevance in recent years. Diagnosis is a paramount step for screening, epidemiological investigation, as well as for ensuring the success of control strategies such as vaccination trials. This is the first review that systematically addresses data available for the diagnosis of TB in wildlife following the Preferred Reporting Items of Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The article also gives an overview of the factors related to host, environment, sampling, and diagnostic techniques which can affect test performance. After three screenings, 124 articles were considered for systematic review. Literature indicates that post-mortem examination and culture are useful methods for disease surveillance, but immunological diagnostic tests based on cellular and humoral immune response detection are gaining importance in wildlife TB diagnosis. Among them, serological tests are especially useful in wildlife because they are relatively inexpensive and easy to perform, facilitate large-scale surveillance and can be used both ante- and post-mortem. Currently available studies assessed test performance mostly in cervids, European badgers, wild suids and wild bovids. Research to improve diagnostic tests for wildlife TB diagnosis is still needed in order to reach accurate, rapid and cost-effective diagnostic techniques adequate to a broad range of target species and consistent over space and time to allow proper disease monitoring.

Discrimination of Zanthoxylum bungeanum Maxim through volatile aroma compounds analysis with artificial neural network

Zanthoxylum bungeanum Maxim (ZBM), a special spice from Chinese different areas, have a widespread variation in quality and price. To avoid the commercial adulteration of ZBM, it is necessary to discriminate them from different areas. As volatile aroma compounds (VAC) have the potential to discriminate ZBM, electronic nose (E-nose) was used to preliminarily discriminate the VAC through sensor response analysis, radar chart analysis, and principal component analysis. Then, Gas chromatography-mass spectrometry (GC-MS) was utilized to identify VAC through hierarchical cluster analysis and quantitative analysis. Finally, artificial neural network (ANN) was employed to assess the accuracy of the discrimination of ZBM. As a result, we found that ZBM could be successfully discriminated between Chinese Sichuan and the other areas. Our findings would provide guidance for evaluating and predicting the variation of VAC of ZBM from different areas in further study. PRACTICAL APPLICATIONS: Zanthoxylum bungeanum Maxim (ZBM) is a traditional and important spice used in Sichuan cuisine especially hotpot, which are famous all over overseas. However, the ZBM from different producing areas bring various flavors, hampering the quality of Sichuan cuisine developing toward to standardization. Therefore, the authors in this work pursuit an effective way to distinguish the ZBM produced in Sichuan rather than in other province. According to the results of the present study, ZBM could be successfully discriminated between Chinese Sichuan and the other producing areas by using E-nose and GC-MS through artificial neural network. These findings would provide the guidance for evaluating the producing areas of ZBM to be whether or not Sichuan, which could offer the practical help in the purchase of the raw material in the supply chain. Besides, these also can be applied to predict the variation of volatile aroma compounds of the ZBM in the further study.

Immunoregulatory and Antimicrobial Activity of Bovine Neutrophil β-Defensin-5-Loaded PLGA Nanoparticles against Mycobacterium bovis

Mycobacterium bovis (M. bovis) is a member of the Mycobacterium tuberculosis complex imposing a high zoonotic threat to human health. The limited efficacy of BCG (Bacillus Calmette-Guérin) and upsurges of drug-resistant tuberculosis require new effective vaccination approaches and anti-TB drugs. Poly (lactic-co-glycolic acid) (PLGA) is a preferential drug delivery system candidate. In this study, we formulated PLGA nanoparticles (NPs) encapsulating the recombinant protein bovine neutrophil β-defensin-5 (B5), and investigated its role in immunomodulation and antimicrobial activity against M. bovis challenge. Using the classical water-oil-water solvent-evaporation method, B5-NPs were prepared, with encapsulation efficiency of 85.5% ± 2.5%. These spherical NPs were 206.6 ± 26.6 nm in diameter, with a negatively charged surface (ζ-potential -27.1 ± 1.5 mV). The encapsulated B5 protein from B5-NPs was released slowly under physiological conditions. B5 or B5-NPs efficiently enhanced the secretion of tumor necrosis factor α (TNF-α), interleukin (IL)-1β and IL-10 in J774A.1 macrophages. B5-NPs-immunized mice showed significant increases in the production of TNF-α and immunoglobulin A (IgA) in serum, and the proportion of CD4⁺ T cells in spleen compared with B5 alone. In immunoprotection studies, B5-NPs-immunized mice displayed significant reductions in pulmonary inflammatory area, bacterial burden in the lungs and spleen at 4-week after M. bovis challenge. In treatment studies, B5, but not B5-NPs, assisted rifampicin (RIF) with inhibition of bacterial replication in the lungs and spleen. Moreover, B5 alone also significantly reduced the bacterial load in the lungs and spleen. Altogether, our findings highlight the significance of the B5-PLGA NPs in terms of promoting the immune effect of BCG and the B5 in enhancing the therapeutic effect of RIF against M. bovis.

Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome

Volatilome analysis is growing in attention for the diagnosis of diseases in animals and humans. In particular, volatilome analysis in fecal samples is starting to be proposed as a fast, easy and noninvasive method for disease diagnosis. Volatilome comprises volatile organic compounds (VOCs), which are produced during both physiological and patho-physiological processes. Thus, VOCs from a pathological condition often differ from those of a healthy state and therefore the VOCs profile can be used in the detection of some diseases. Due to their strengths and advantages, feces are currently being used to obtain information related to health status in animals. However, they are complex samples, that can present problems for some analytical techniques and require special consideration in their use and preparation before analysis. This situation demands an effort to clarify which analytic options are currently being used in the research context to analyze the possibilities these offer, with the final objectives of contributing to develop a standardized methodology and to exploit feces potential as a diagnostic matrix. The current work reviews the studies focused on the diagnosis of animal diseases through fecal volatilome in order to evaluate the analytical methods used and their advantages and limitations. The alternatives found in the literature for sampling, storage, sample pretreatment, measurement and data treatment have been summarized, considering all the steps involved in the analytical process.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Evaluation of Volatile Organic Compounds Obtained from Breath and Feces to Detect Mycobacterium tuberculosis Complex in Wild Boar (Sus scrofa) in Doñana National Park, Spain

The presence of Mycobacterium tuberculosis complex (MTBC) in wild swine, such as in wild boar (Sus scrofa) in Eurasia, is cause for serious concern. Development of accurate, efficient, and noninvasive methods to detect MTBC in wild swine would be highly beneficial to surveillance and disease management efforts in affected populations. Here, we describe the first report of identification of volatile organic compounds (VOC) obtained from the breath and feces of wild boar to distinguish between MTBC-positive and MTBC-negative boar. We analyzed breath and fecal VOC collected from 15 MTBC-positive and 18 MTBC-negative wild boar in Donaña National Park in Southeast Spain. Analyses were divided into three age classes, namely, adults (>2 years), sub-adults (12–24 months), and juveniles (<12 months). We identified significant compounds by applying the two-tailed statistical t-test for two samples assuming unequal variance, with an α value of 0.05. One statistically significant VOC was identified in breath samples from adult wild boar and 14 were identified in breath samples from juvenile wild boar. One statistically significant VOC was identified in fecal samples collected from sub-adult wild boar and three were identified in fecal samples from juvenile wild boar. In addition, discriminant function analysis (DFA) was used to build classification models for MTBC prediction in juvenile animals. Using DFA, we were able to distinguish between MTBC-positive juvenile wild boar and MTBC-negative juvenile wild boar using breath VOC or fecal VOC. Based on our results, further research is warranted and should be performed using larger sample sizes, as well as wild boar from various geographic locations, to verify these compounds as biomarkers for MTBC infection in this species. This new approach to detect MTBC infection in free-ranging wild boar potentially comprises a reliable and efficient screening tool for surveillance in animal populations.

Assessment of the Portable C-320 Electronic Nose for Discrimination of Nine Insectivorous Bat Species: Implications for Monitoring White-Nose Syndrome

The development of new C-320 electronic-nose (e-nose) methods for pre-symptomatic detection of White-Nose Syndrome (WNS) in bats has required efficacy studies of instrument capabilities to discriminate between major sources of volatile organic compounds (VOCs) derived from clinical samples. In this phase-2 study, we further tested this e-nose for capabilities to distinguish between bat species based on differences in whole-body VOC emissions. Live healthy individuals of nine bat species were temporarily captured outside of caves in Arkansas and Louisiana. VOC emissions from bats were collected using newly developed portable air collection and sampling-chamber devices in tandem. Sensor-array output responses to bat VOC emissions were compared to those of 22 pure VOC analytical standards from five chemical classes. Distinct smellprint signatures were produced from e-nose analyses of VOC metabolites derived from individual bat species. Smellprint patterns were analyzed using 2-dimensional and 3-dimensional Principal Component Analysis (PCA) to produce aroma map plots showing effective discrimination between bat species with high statistical significance. These results demonstrate potential instrument efficacy for distinguishing between species-specific, bat-derived VOC metabolite emissions as major components of clinical samples collected from bats in caves for disease detection prior to symptom development. This study provided additional information required to fully test the efficacy of a portable e-nose instrument for diagnostic applications in subsequent phase-3 testing of noninvasive, early WNS disease detection in intra-cave hibernating bats.

Kallikrein 12 Regulates Innate Resistance of Murine Macrophages against Mycobacterium bovis Infection by Modulating Autophagy and Apoptosis

Mycobacterium bovis (M. bovis) is a member of the Mycobacterium tuberculosis (Mtb) complex causing bovine tuberculosis (TB) and imposing a high zoonotic threat to human health. Kallikreins (KLKs) belong to a subgroup of secreted serine proteases. As their role is established in various physiological and pathological processes, it is likely that KLKs expression may mediate a host immune response against the M. bovis infection. In the current study, we report in vivo and in vitro upregulation of KLK12 in the M. bovis infection. To define the role of KLK12 in immune response regulation of murine macrophages, we produced KLK12 knockdown bone marrow derived macrophages (BMDMs) by using siRNA transfection. Interestingly, the knockdown of KLK12 resulted in a significant downregulation of autophagy and apoptosis in M. bovis infected BMDMs. Furthermore, we demonstrated that this KLK12 mediated regulation of autophagy and apoptosis involves mTOR/AMPK/TSC2 and BAX/Bcl-2/Cytochrome c/Caspase 3 pathways, respectively. Similarly, inflammatory cytokines IL-1β, IL-6, IL-12 and TNF-α were significantly downregulated in KLK12 knockdown macrophages but the difference in IL-10 and IFN-β expression was non-significant. Taken together, these findings suggest that upregulation of KLK12 in M. bovis infected murine macrophages plays a substantial role in the protective immune response regulation by modulating autophagy, apoptosis and pro-inflammatory pathways. To our knowledge, this is the first report on expression and the role of KLK12 in the M. bovis infection and the data may contribute to a new paradigm for diagnosis and treatment of bovine TB.

Use of faecal volatile organic compound analysis for ante-mortem discrimination between CWD-positive, -negative exposed, and -known negative white-tailed deer (Odocoileus virginianus)

Chronic wasting disease (CWD) is a naturally occurring infectious, fatal, transmissible spongiform encephalopathy of cervids. Currently, disease confirmation relies on post-mortem detection of infectious prions in the medial retropharyngeal lymph nodes or obex in the brain via immunohistochemistry (IHC). Detection of CWD in living animals using this method is impractical, and IHC and other experimental assays are not reliable in detecting low concentrations of prion present in biofluids or faeces. Here, we evaluate the capability of faecal volatile organic compound analysis to discriminate between CWD-positive and -exposed white-tailed deer located at two positive cervid farms, and two groups of CWD-negative deer from two separate disease-free farms.

Application of Electronic-Nose Technologies and VOC-Biomarkers for the Noninvasive Early Diagnosis of Gastrointestinal Diseases †

Conventional methods utilized for clinical diagnosis of gastrointestinal (GI) diseases have employed invasive medical procedures that cause stress, anxiety and pain to patients. These methods are often expensive, time-consuming, and require sophisticated chemical-analysis instruments and advanced modeling procedures to achieve diagnostic interpretations. This paper reviews recent applications of simpler, electronic-nose (e-nose) devices for the noninvasive early diagnosis of a wide range of GI diseases by collective analysis of headspace volatile organic compound (VOC)-metabolites from clinical samples to produce disease-specific aroma signatures (VOC profiles). A different "metabolomics" approach to GI disease diagnostics, involving identifications and quantifications of disease VOC-metabolites, are compared to the electronic-nose approach based on diagnostic costs, accuracy, advantages and disadvantages. The importance of changes in gut microbiome composition that result from disease are discussed relative to effects on disease detection. A new diagnostic approach, which combines the use of e-nose instruments for early rapid prophylactic disease-screenings with targeted identification of known disease biomarkers, is proposed to yield cheaper, quicker and more dependable diagnostic results. Some priority future research needs and coordination for bringing e-nose instruments into routine clinical practice are summarized.

MicroRNA-199a Inhibits Cellular Autophagy and Downregulates IFN-β Expression by Targeting TBK1 in Mycobacterium bovis Infected Cells

The mechanism by which microRNAs (miRNAs) modulate innate immunity and autophagy has not been fully elucidated in Mycobacterium bovis (M. bovis) infections. In this study, we identified that miR-199a inhibited key innate immune responses and autophagy in murine macrophages infected with M. bovis. Using ex vivo and in vitro approaches we show that the expression of miR-199a was significantly increased during M. bovis infection. Furthermore, miR-199a suppressed autophagy and interferon-β (IFN-β) production by directly targeting TANK-binding kinase 1 (TBK1) mRNA in both J774a.1 and BMDM cells. Upregulation of miR-199a or TBK1 silencing (siTBK1) inhibited maturation of autophagosomes and increased M. bovis survival. Our results demonstrate that, by targeting of TBK1, miR-199a modulates innate immune responses and promote the intracellular survival and growth of M. bovis.

Recent advancement in biosensors technology for animal and livestock health management

The term biosensors encompasses devices that have the potential to quantify physiological, immunological and behavioural responses of livestock and multiple animal species. Novel biosensing methodologies offer highly specialised monitoring devices for the specific measurement of individual and multiple parameters covering an animal's physiology as well as monitoring of an animal's environment. These devices are not only highly specific and sensitive for the parameters being analysed, but they are also reliable and easy to use, and can accelerate the monitoring process. Novel biosensors in livestock management provide significant benefits and applications in disease detection and isolation, health monitoring and detection of reproductive cycles, as well as monitoring physiological wellbeing of the animal via analysis of the animal's environment. With the development of integrated systems and the Internet of Things, the continuously monitoring devices are expected to become affordable. The data generated from integrated livestock monitoring is anticipated to assist farmers and the agricultural industry to improve animal productivity in the future. The data is expected to reduce the impact of the livestock industry on the environment, while at the same time driving the new wave towards the improvements of viable farming techniques. This review focusses on the emerging technological advancements in monitoring of livestock health for detailed, precise information on productivity, as well as physiology and well-being. Biosensors will contribute to the 4th revolution in agriculture by incorporating innovative technologies into cost-effective diagnostic methods that can mitigate the potentially catastrophic effects of infectious outbreaks in farmed animals.

The volatile molecule signature of four mycobacteria species

Mycobacteria are the leading cause of death from infectious disease worldwide and limitations in current diagnostics are hampering control efforts. In recent years, the use of small volatile molecules as diagnostic biomarkers for mycobacteria has shown promise for use in the rapid analysis of in vitro cultures as well as ex vivo diagnosis using breath or sputum. In this study, 18 strains from four mycobacteria species (Mycobacterium avium, M. bovis BCG, M. intracellulare and M. xenopi) were analyzed for the first time using two-dimensional gas chromatography time-of-flight mass spectrometry (GC × GC-TOFMS). This study represents the first time volatile molecules associated with M. intracellulare and M. xenopi have ever been reported. A total of 217 chromatographic features were identified and 58 features were selected that discriminate between these four species. Putative identifications are provided for 17 of the 58 discriminatory features, three of which have been reported previously in mycobacteria. The identification of mycobacteria-associated volatile biomarker suites could reduce the time-to-diagnosis for mycobacterial infections, either from in vitro cultures prior to the visualization of colonies or directly from ex vivo specimens, thereby shortening the empiric treatment window and potentially improving outcomes.

Virulent Mycobacterium bovis Beijing Strain Activates the NLRP7 Inflammasome in THP-1 Macrophages

Mycobacterium bovis is the causative agent of tuberculosis in a wide range of mammals, including humans. Macrophages are the first line of host defense. They secrete proinflammatory cytokines, such as interleukin-1 beta (IL-1β), in response to mycobacterial infection, but the underlying mechanisms by which human macrophages are activated and release IL-1β following M. bovis infection are poorly understood. Here we show that the ‘nucleotide binding and oligomerization of domain-like receptor (NLR) family pyrin domain containing 7 protein’ (NLRP7) inflammasome is involved in IL-1β secretion and caspase-1 activation induced by M. bovis infection in THP-1 macrophages. NLRP7 inflammasome activation promotes the induction of pyroptosis as well as the expression of tumor necrosis factor alpha (TNF-α), Chemokine (C-C motif) ligand 3 (CCL3) and IL-1β mRNAs. Thus, the NLRP7 inflammasome contributes to IL-1β secretion and induction of pyroptosis in response to M. bovis infection in THP-1 macrophages.

Impact of food intake on in vivo VOC concentrations in exhaled breath assessed in a caprine animal model

Physiological processes within the body may change emitted volatile organic compound (VOC) composition, and may therefore cause confounding biological background variability in breath gas analyses. To evaluate the effect of food intake on VOC concentration patterns in exhaled breath, this study assessed the variability of VOC concentrations due to food intake in a standardized caprine animal model. VOCs in (i) alveolar breath gas samples of nine clinically healthy goats and (ii) room air samples were collected and pre-concentrated before morning feeding and repeatedly after (+60 min, +150 min, +240 min) using needle trap microextraction (NTME). Analysis of VOCs was performed by gas chromatography and mass spectrometry (GC-MS). Only VOCs with significantly higher concentrations in breath gas samples compared to room air samples were taken into consideration. Six VOCs that belonged to the chemical classes of hydrocarbons and alcohols were identified presenting significantly different concentrations before and after feeding. Selected hydrocarbons showed a concentration pattern that was characterized by an initial increase 60 min after food intake, and a subsequent gradual decrease. Results emphasize consideration of physiological effects on exhaled VOC concentrations due to food intake with respect to standardized protocols of sample collection and critical evaluation of results.

Exhaled breath analysis by electronic nose in respiratory diseases

Breath analysis via electronic nose is a technique oriented around volatile organic compound (VOC) profiling in exhaled breath for diagnostic and prognostic purposes. This approach, when supported by methodologies for VOC identification, has been often referred to as metabolomics or breathomics. Although breath analysis may have a substantial impact on clinical practice, as it may allow early diagnosis and large-scale screening strategies while being noninvasive and inexpensive, some technical and methodological limitations must be solved, together with crucial interpretative issues. By integrating a review of the currently available literature with more speculative arguments about the potential interpretation and application of VOC analysis, the authors aim to provide an overview of the main relevant aspects of this promising field of research.

Diagnosis of bovine tuberculosis using a metal oxide-based electronic nose

Electronic noses (e-noses) have been used for environmental monitoring, standardization of medicinal flavourings, food safety tests and diagnosis of infectious diseases based on the statistical analysis of volatile organic compounds (VOCs). Bovine tuberculosis (bTB) is officially diagnosed using the intradermal skin test (IST), which is time-consuming and labour-intensive. Therefore, a more convenient and rapid test with greater sensitivity would be advantageous as prescreening test. In this study, we used a metal oxide sensor (MOS) type e-nose to analyse VOCs in a bTB-infected (n = 11) and bTB-free (n = 10) sera, from cattle whose health status was confirmed using the IST, and pathological and bacteriological examinations. The differences in VOCs from bTB-infected and bTB-free sera detected by the e-nose were statistically analysed using principal components and discriminant factor analyses. bTB-infected and bTB-free sera could be discriminated by MOS type e-nose, and analysing time per sample was only 20 min. VOC analysis using a MOS e-nose was a rapid and automated prescreening method to diagnose bTB, and can be used to select bTB-suspect cattle for IST confirmation. Further studies are required to estimate test sensitivity and specificity. Significance and impact of the study: Bovine tuberculosis (bTB) in cattle is diagnosed using the intradermal skin test (IST); however, this method is very time-consuming and labour-intensive. We analysed volatile organic compounds that are obtained from serum using a metal oxide sensor type of electronic nose to discriminate between TB-infected and TB-free sera. This simple and automated technique will be useful to prescreen bTB-suspects and reduce the time and labour required to perform the IST.

Recurrent bovine tuberculosis in New Zealand cattle and deer herds, 2006–2010

A retrospective cohort study was conducted to identify risk factors for bovine tuberculosis (bTB) recurrence in New Zealand cattle and deer herds identified as bTB-infected from 1 June 2006 to 1 November 2010. A Cox proportional hazards model identified a positive relationship between the daily hazard of bTB recurrence and: (1) the number of prior bTB episodes for two episodes [hazard ratio (HR) 3·22, 95% confidence interval (CI) 1·21–8·60], and for five episodes (HR 89·5, 95% CI 13·8–580), (2) more than one positive bTB case animal at the index episode (HR 2·25, 95% CI 1·19–4·25) and (3) the presence of cleared test-positives at the final test of the index episode. The proportional hazards assumption was violated for the latter variable so a time-dependent covariate was introduced. Up to 2 years post-clearance, the daily hazard of bTB recurrence was greater in herds with test-positives at the final test (HR 2·59, 95% CI 1·30–5·13), but this effect was not observed more than 2 years' post-clearance (HR 1·05, 95% CI 0·28–3·91). We conclude that unresolved infection contributes to further bTB episodes in the first 2 years after herd clearance.

A pilot study exploring the use of breath analysis to differentiate healthy cattle from cattle experimentally infected with Mycobacterium bovis

Bovine tuberculosis, caused by Mycobacterium bovis, is a zoonotic disease of international public health importance. Ante-mortem surveillance is essential for control; however, current surveillance tests are hampered by limitations affecting ease of use or quality of results. There is an emerging interest in human and veterinary medicine in diagnosing disease via identification of volatile organic compounds produced by pathogens and host-pathogen interactions. The objective of this pilot study was to explore application of existing human breath collection and analysis methodologies to cattle as a means to identify M. bovis infection through detection of unique volatile organic compounds or changes in the volatile organic compound profiles present in breath. Breath samples from 23 male Holstein calves (7 non-infected and 16 M. bovis-infected) were collected onto commercially available sorbent cartridges using a mask system at 90 days post-inoculation with M. bovis. Samples were analyzed using gas chromatography-mass spectrometry, and chromatographic data were analyzed using standard analytical chemical and metabolomic analyses, principle components analysis, and a linear discriminant algorithm. The findings provide proof of concept that breath-derived volatile organic compound analysis can be used to differentiate between healthy and M. bovis-infected cattle.

Clinical application of volatile organic compound analysis for detecting infectious diseases

This review article introduces the significance of testing of volatile organic compounds (VOCs) in clinical samples and summarizes important features of some of the technologies. Compared to other human diseases such as cancer, studies on VOC analysis in cases of infectious diseases are limited. Here, we have described results of studies which have used some of the appropriate technologies to evaluate VOC biomarkers and biomarker profiles associated with infections. The publications reviewed include important infections of the respiratory tract, gastrointestinal tract, urinary tract, and nasal cavity. The results highlight the use of VOC biomarker profiles resulting from certain infectious diseases in discriminating between infected and healthy subjects. Infection-related VOC profiles measured in exhaled breath as well as from headspaces of feces or urine samples are a source of information with respect to disease detection. The volatiles emitted in clinical matrices may on the one hand represent metabolites of the infecting pathogen or on the other hand reflect pathogen-induced host responses or, indeed, a combination of both. Because exhaled-breath samples are easy to collect and online instruments are commercially available, VOC analysis in exhaled breath appears to be a promising tool for noninvasive detection and monitoring of infectious diseases.

Diagnostic potential of the pulsed discharged helium ionization detector (PDHID) for pathogenic Mycobacterial volatile biomarkers

Pathogenic Mycobacteria cause diseases in animals and humans with significant economic and societal consequences. Current methods for Mycobacterial detection relies upon time- and labor-intensive techniques such as culturing or DNA analysis. Using gas chromatography and mass spectrometry, four volatile compounds (methyl phenylacetate, methyl p-anisate, methyl nicotinate and o-phenyl anisole) were recently proposed as potential biomarkers for Mycobacteria. We demonstrate for the first time the capabilities of a field-deployable, pulsed discharge helium ionization detector (PDHID) for sensing these volatiles. We determined the analytical performance of the PDHID toward these Mycobacterial volatiles. Detector performance was moderately affected over the temperature range of 150 to 350 °C. The linear dynamic range for all four analytes exceeded three orders of magnitude. The limits of detection (LOD) and quantitation (LOQ) were calculated as 150 and 450 pg respectively, for all compounds, except methyl phenylacetate (LOD and LOQ, 90 and 270 pg, respectively). Control charts revealed that the PDHID detection system was generally stable, and deviations could be traced to common causes and excluded special causes. Grob tests and ionization potential data suggest that the PDHID is capable of detecting Mycobacterial volatiles in a complex milieu such as culture headspace or breath samples from tuberculosis patients. The diagnostic potential of the PDHID is critical to our goal of a handheld, field-deployable 'sniffer' system for biological pathogens and chemical warfare agents.

Facts and dilemmas in diagnosis of tuberculosis in wildlife

Mycobacterium bovis, causing bovine tuberculosis (BTB), has been recognized as a global threat at the wildlife-livestock-human interface, a clear "One Health" issue. Several wildlife species have been identified as maintenance hosts. Spillover of infection from these species to livestock or other wildlife species may have economic and conservation implications and infection of humans causes public health concerns, especially in developing countries. Most BTB management strategies rely on BTB testing, which can be performed for a range of purposes, from disease surveillance to diagnosing individual infected animals. New diagnostic assays are being developed for selected wildlife species. This review investigates the most frequent objectives and associated requirements for testing wildlife for tuberculosis at the level of individual animals as well as small and large populations. By aligning those with the available (immunological) ante mortem diagnostic assays, the practical challenges and limitations wildlife managers and researchers are currently faced with are highlighted.

Molecular genotyping and epidemiology of Mycobacterium bovis strains obtained from cattle in Iran

Restriction fragment length polymorphism (RFLP) genotyping was employed to analyze the population genetics of Mycobacterium bovis in Iran. One hundred and twenty-three isolates collected from slaughtered tuberculosis-suspect cattle and one clinically asymptomatic buffalo were subjected to RFLP analysis with probes of the polymorphic GC-rich sequence (PGRS) and the direct repeat sequence (DR) using DNA digested with PvuII and AluI. All these methods detected a large homogeneous population in which only a few isolates had variant genotypes. Only AluI-based RFLPs of both the PGRS and DR sequences were able to clearly differentiate between BCG and field strains of M. bovis. As in previous reports, these findings seem to reflect a recent dispersal of one or a few strains in Iran following the substantial expansion of Holstein-Friesian cattle over the last few decades.

Mycobacterium bovis infection in the Eurasian badger (Meles meles): the disease, pathogenesis, epidemiology and control

Eurasian badgers (Meles meles) are an important wildlife reservoir of tuberculosis (Mycobacterium bovis) infection in Ireland and the United Kingdom. As part of national programmes to control tuberculosis in livestock, considerable effort has been devoted to studying the disease in badgers and this has lead to a rapid increase in our knowledge of tuberculosis in this host. Tuberculosis in badgers is a chronic infection and in a naturally-infected population the severity of disease can vary widely, from latent infection (infection without clinical signs and no visible lesions) to severe disease with generalized pathology. The high prevalence of pulmonary infection strongly supports the lungs as the principal site of primary infection and that inhalation of infectious aerosol particles is the principal mode of transmission. However, other routes, including transmission via infected bite wounds, are known to occur. The ante-mortem diagnosis of infection is difficult to achieve, as clinical examination and immunological and bacteriological examination of clinical samples are insensitive diagnostic procedures. Because infection in the majority of badgers is latent, the gross post-mortem diagnosis is also insensitive. A definitive diagnosis can only be made by the isolation of M. bovis. However, to gain a high level of sensitivity in the bacteriological examination, a large number of tissues from each badger must be cultured and sensitive culture methods employed. The transmission and maintenance of M. bovis in badger populations are complex processes where many factors influence within-population prevalence and rates of transmission. Badger social structures and the longevity of infected animals make them an ideal maintenance host for M. bovis infection. Badgers are directly implicated in the transmission of infection to cattle and the inability to eradicate the disease from cattle is, in part, a consequence of the interactions between the two species. A detailed understanding and knowledge of the epidemiology and pathogenesis of the disease are recognized as fundamental for devising new strategies to control infection with a view to limiting interspecies transmission. Vaccination, in spite of formidable challenges, is seen as the best long-term strategy option and studies with captive badgers have shown that vaccination with M. bovis bacillus Calmette-Guérin (BCG) induces protection when delivered by a variety of routes. Continued research is required to develop effective technologies to control the disease both in badgers and cattle. A combination of strategies, which employ the optimal use and targeting of resources, is likely to make a significant contribution towards eradication of the disease.

Invited review: The role of contagious disease in udder health

Contagious diseases are a threat to animal health and productivity, both nationally and at the farm level. This makes implementation of biosecurity measures to prevent their introduction and spread within countries and farms a necessity. Mastitis is the most common and costly contagious disease affecting dairy farms in the western world. The major mastitis pathogens are endemic in most countries, and biosecurity measures to prevent introduction and transmission must therefore be implemented at farm level. The 40-yr-old mastitis control plan remains a solid foundation to prevent the spread of contagious intramammary infections. Contagious diseases that do not affect the mammary gland directly may have an indirect effect on mastitis. This is true for list A diseases such as foot and mouth disease, for which biosecurity measures may need to be taken at national level, and for other infections with nonmastitis pathogens such as bovine viral diarrhea virus and Mycobacterium avium ssp. paratuberculosis. Maintaining a closed herd decreases the risk of introduction of pathogens that affect udder health directly or indirectly. If animals are purchased, their udder health history should be evaluated and they should be examined and tested for contagious diseases. Transmission of infections by and to humans and nonbovine animals may occur. Contact with visitors and nonbovine animals should therefore be minimized. Because of globalization and heightened consumer awareness, the importance of biosecurity now supersedes individual farms, and increased pressure to control transmission of contagious diseases can be expected at industry or government levels in western countries and elsewhere.

Detection of cutaneous myiasis in sheep using an 'electronic nose'

Cutaneous myiasis (flystrike), in Australia caused primarily by Lucilia cuprina [Diptera: Calliphoridae], is a debilitating, painful and potentially lethal disease of sheep. Early detection of flystrike is difficult and continual flock surveillance is required to enable timely treatment of struck sheep. Electronic nose technology offers the potential for early and automated detection of flystrike. An electronic nose consisting of six metal oxide semiconductor sensors and temperature and humidity sensors was used to measure odours collected by dynamic headspace sampling during flystrike development in four experiments and from urine- and faeces-stained fleece in one experiment. Non-linear signal measurement techniques and linear discriminant analysis (LDA) were used to extract signal features and process those features for analysis of categorical separation of odour groups. The results from LDA indicated that the electronic nose accurately distinguished flystrike odour on days 1, 2 and 3 of development from that of dry wool in all experiments (P<0.05). The electronic nose was also able to discriminate flystrike odour on the day of larval implantation (day 0) in three of the four studies. In the experiment with urine- and faeces-stained wool, these odours were accurately distinguished from both dry wool and flystrike (P<0.05). This study provides proof-of-concept for the detection of flystrike using electronic nose technology. Practical methods for collection of odour in the field and suitable detection algorithms will be required for development to commercial application.

Evaluation of a combination of SIFT-MS and multivariate data analysis for the diagnosis of Mycobacterium bovis in wild badgers

The currently accepted 'gold standard' tuberculosis (TB) detection method for veterinary applications is that of culturing from a tissue sample post mortem. The test is accurate, but growing Mycobacterium bovis is difficult and the process can take up to 12 weeks to return a diagnosis. In this paper we evaluate a much faster screening approach based on serum headspace analysis using selected ion flow tube mass spectrometry (SIFT-MS). SIFT-MS is a rapid, quantitative gas analysis technique, with sample analysis times of as little as a few seconds. Headspace from above serum samples from wild badgers, captured as part of a randomised trial, was analysed. Multivariate classification algorithms were then employed to extract a simple TB diagnosis from the complex multivariate response provided by the SIFT-MS instrument. This is the first time that such multivariate analysis has been applied to SIFT-MS data. An accuracy of TB discrimination of approximately 88% true positive was achieved which shows promise, but the corresponding false positive rate of 38% indicates that there is more work to do before this approach could replace the culture test. Recommendations for future work that could increase the performance are therefore proposed.

Mycobacterium bovis infection in Holstein Friesian cattle, Iran

To identify strains of Mycobacterium bovis circulating in Iran, we used region of difference, spoligotypes, and variable number tandem repeats to genotype 132 M. bovis isolates from Holstein Friesian cattle. Despite wide geographic origins, the strains were genetically homogeneous. Increased distribution of cattle herds and inadequate control measures may have contributed to strain dispersion.

Discrimination of plant volatile signatures by an electronic nose: aA potential technology for plant pest and disease monitoring

The volatile organic compounds (VOCs) profile emitted from plants often changes in response to environmental factors, and monitoring the change of such profiles could provide a nondestructive means of plant health measurement An electronic nose (e-nose) was used to discriminate among VOC bouquets emitted by cucumber, pepper, and tomato leaves subjected to mechanical damage or pest and disease attacks compared with undamaged control leaves. Principle component analysis, discriminant function analysis, and cluster analysis were applied to evaluate the data. The results indicate that the e-nose can discriminate among VOCs from undamaged leaves of the three tested species. It can also discriminate undamaged and artificially damaged leaves of the same plant species. In cucumber, the e-nose can discriminate among VOCs emitted from control, artificially damaged, and spider-mite-infested leaves. It could also discriminate among VOCs emitted from control, artificially damaged, hornworm-damaged, and powdery-mildew-infected tomato leaves. The relationships between the changes in volatile signatures detected by the e-nose to changes in the underlying chemistry of plant VOC signatures in response to applied stresses were quantified by gas chromatography mass spectrometry. We conclude that the e-nose had genuine responses to changes in plant VOC signatures and can successfully discriminate them. These studies demonstrate the potential use of such e-nose technology as a real time pest and disease monitoring system in agricultural and horticultural settings.

An investigation into the suitability of using three electronic nose instruments for the detection and discrimination of bacteria types

The use of electronic nose (e-nose) technology for detection of food-borne bacteria has several practical advantages over current laboratory procedures, such as lower cost and reduced testing time. In this work, we are interested in using electronic nose systems to detect E. coli and Listeria in a nutrient broth, and discriminate between these bacteria types at various concentrations. To do this, we use instruments based on three different technologies - fingerprint mass spectrometry, metal oxide sensors, and conductive polymer sensors. Our results indicate that separation between groups can be achieved. We describe the relative merits and drawbacks of each technology and discuss how this rich multimodal dataset can be used to build a classification system.

Facing the crisis: improving the diagnosis of tuberculosis in the HIV era

Although the human immunodeficiency virus (HIV) infection pandemic has had a catastrophic impact on tuberculosis (TB) control efforts, especially in sub-Saharan Africa, most of the fundamental concepts reflected in the directly observed treatment, short course (DOTS) strategy still hold true in the HIV era. What has changed, and dramatically, is the importance of speedy and accurate TB diagnosis and the difficulty of achieving this. The disproportionate amount of smear-negative disease in sub-Saharan Africa, which shoulders two-thirds of the global burden of HIV infection and acquired immunodeficiency syndrome, has greatly complicated TB case detection and disease control. Now, 15 years after TB rates began to soar in countries where HIV infection is prevalent, we have learned that the conventional approach -- passively waiting for patients with advanced symptomatic disease to make their way to microscopy centers for diagnosis -- has disastrous consequences. Without better diagnostic tools for TB and effective strategies for their implementation, transmission will not be interrupted, mortality will not be checked, and TB will not be controlled in areas where HIV infection is prevalent. Fortunately, a number of technical opportunities exist for the creation of improved diagnostic tests. Developing and exploiting such tests to support TB control in HIV-infected populations is an urgent priority. A substantial public sector effort is under way to work in partnership with the biotechnology industry to accelerate progress toward that goal. In this article, we will define the need for better TB tests and describe technologies being developed to meet that need.

Diagnóstico imunológico da tuberculose: problemas e estratégias para o sucesso

A tuberculose continua sendo um grave problema social e de saúde, afetando milhões de pessoas anualmente. A vacina Bacille Calmette-Guerin (BCG), usada no controle profilático, é incapaz de conter a progressão da doença, que usualmente se manifesta através da queda da imunidade celular do indivíduo. O diagnóstico da tuberculose em seus estágios iniciais, aliado à poliquimioterapia, pode contribuir para o controle da disseminação da infecção. Os atuais métodos de diagnóstico apresentam problemas, como: baixa sensibilidade da baciloscopia; longo tempo de realização das culturas microbiológicas; e baixa especificidade do teste cutâneo com o derivado protéico purificado do M. tuberculosis. Novos métodos de diagnóstico que utilizam antígenos específicos (por exemplo, os conhecidos em inglês como o early secreted antigenic target 6-kDa e o culture filtrate protein 10-kDa), estão sendo testados. Os genes que codificam esses antígenos estão localizados na região de diferença 1 do M. tuberculosis, M. africanum e M. bovis, mas estão ausentes no M. bovis (BCG) e na maioria das micobactérias do meio ambiente. Métodos de diagnóstico baseados na produção de interferon-gama por linfócitos T, em resposta a esses antígenos, como o QuantiFERON-TB® e o T SPOT.TB®, estão sendo testados, e superam o teste cutâneo com o derivado protéico purificado nas seguintes características: maior sensibilidade; menor reatividade cruzada devido à vacinação com o BCG ou infecção por micobactérias do meio ambiente; e tempo de execução. A introdução de métodos de diagnóstico mais específicos e sensíveis, assim como um maior entendimento dos mecanismos moleculares e celulares que regulam a interação parasito-hospedeiro, pode contribuir para um eficiente combate à tuberculose.

Prospects for clinical application of electronic-nose technology to early detection of Mycobacterium tuberculosis in culture and sputum

Ziehl-Neelsen (ZN) staining for the diagnosis of tuberculosis (TB) is time-consuming and operator dependent and lacks sensitivity. A new method is urgently needed. We investigated the potential of an electronic nose (EN) (gas sensor array) comprising 14 conducting polymers to detect different Mycobacterium spp. and Pseudomonas aeruginosa in the headspaces of cultures, spiked sputa, and sputum samples from 330 culture-proven and human immunodeficiency virus-tested TB and non-TB patients. The data were analyzed using principal-component analysis, discriminant function analysis, and artificial neural networks. The EN differentiated between different Mycobacterium spp. and between mycobacteria and other lung pathogens both in culture and in spiked sputum samples. The detection limit in culture and spiked sputa was found to be 1 x 10(4) mycobacteria ml(-1). After training of the neural network with 196 sputum samples, 134 samples (55 M. tuberculosis culture-positive samples and 79 culture-negative samples) were used to challenge the model. The EN correctly predicted 89% of culture-positive patients; the six false negatives were the four ZN-negative and two ZN-positive patients. The specificity and sensitivity of the described method were 91% and 89%, respectively, compared to culture. At present, the reasons for the false negatives and false positives are unknown, but they could well be due to the nonoptimized system used here. This study has shown the ability of an electronic nose to detect M. tuberculosis in clinical specimens and opens the way to making this method a rapid and automated system for the early diagnosis of respiratory infections.