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

Non-Invasive Blood Pressure Tracking of Spontaneous Hypertension Rats Using an Electronic Nose

Traditional noninvasive blood pressure measurement methods in experimental animals are time consuming and difficult to operate, particularly for large numbers of animals. In this study, the possibility of sensing fecal odor to estimate the blood pressure status of spontaneous hypertension rats (SHRs) was explored with the aim of establishing a new method for non-invasive monitoring of blood pressure. The body weight and blood pressure of SHRs kept increasing with growth, and the odor information monitored using an E-nose varied with the blood pressure status, particularly for sensors S6 and S7. The fecal information was analyzed using principal component analysis, canonical discriminant analysis and multilayer perception neural networks (MLP) to discriminate SHRs from normal ones, with a 100% correct classification rate. For better prediction of blood pressure, the model built using multiple linear regression analysis, partial least squares regression analysis and multilayer perceptron neural network analysis were used, with coefficients of determination (R2) ranging from 0.8036 to 0.9926. Moreover, the best prediction model for blood pressure was established using MLP analysis with an R2¬ higher than 0.91. Thus, changes in blood pressure levels can be tracked non-invasively, and normotension can be distinguished from hypertension or even at different hypertension levels based on the odor information of rat feces, providing a foundation for non-invasive health monitoring. This work might provide potential instructions for functional food research aimed at lowering blood pressure.

Influence of lactic acid fermentation on the microbiological parameters, biogenic amines, and volatile compounds of bovine colostrum

In this study we hypothesized that the relations between the bovine colostrum (BC) microbiota, biogenic amine (BA) as well as volatile compound (VC) profiles can lead to new deeper insights concerning the BC changes during the biological preservation. To implement such an aim, BC samples were collected from 5 farms located in Lithuania and fermented with Lactiplantibacillus plantarum and Lacticaseibacillus paracasei strains. Nonfermented and fermented BC were subjected to microbiological [lactic acid bacteria (LAB), Escherichia coli, and total bacteria (TBC), total Enterobacteriaceae (TEC) and total mold and yeast (M-Y) viable counts] and physicochemical (pH, color coordinates, BA content and VC profile) parameters evaluation, and the relationship between the tested parameters were also further analyzed. In comparison pH and dry matter (DM) of nonfermented samples, significant differences were not found, and pH of BC was, on average, 6.30, and DM, on average, 27.5%. The pH of fermented samples decreased, on average, until 4.40 in Lp. plantarum fermented group, and, on average, until 4.37 in Lc. paracasei fermented group. Comparing color characteristics among nonfermented BC groups, significant differences between lightness (L*) and yellowness (b*) were not detected, however, the origin (i.e., agricultural company), LAB strain used for fermentation and the interaction between these factors were statistically significant on BC redness (a*) coordinate. The microbial contamination among all the tested BC groups was similar. However, different LAB strains used for BC fermentation showed different effects toward the microbial contamination reduction, and specifically Lc. paracasei was more effective than Lp. plantarum strain. Predominant BA in BC were putrescine and cadaverine. The main VC in nonfermented and fermented BC were decane, 2-ethyl-1-hexanol, dodecane, 1,3-di-tert-butylbenzene, 3,6-dimethyldecane and tetradecane. Moreover, this study showed worrying trends with respect to the frozen colostrum storage, because most of the dominant VC in BC were contaminants from the packaging material. Additionally, significant correlations between separate VC and microbial contamination were obtained. Finally, these experimental results showed that the separate VC in BC can be an important marker for biological as well as chemical contamination of BC. Also, it should be pointed out that despite the fermentation with LAB is usually described as a safe and natural process with many advantages, control of BA in the end product is necessary.

Putative volatile biomarkers of bovine tuberculosis infection in breath, skin and feces of cattle

Bovine tuberculosis (bTB) is an infectious disease with significant impact on animal health, public health and international trade. Standard bTB screening in live cattle consists in injecting tuberculin and measuring the swelling at the place of injection few days later. This procedure is expensive, time-consuming, logistically challenging, and is not conclusive before performing confirmatory tests and additional analysis. The analysis of the volatile organic compounds (VOCs) emitted by non-invasive biological samples can provide an alternative diagnostic approach suitable for bTB screening. In the present study, we analyzed VOC samples emitted through the breath, feces and skin of 18 cows diagnosed with bTB from three farms from Romania, as well as of 27 negative cows for bTB from the same farms. Analytical studies employing gas chromatography coupled to mass spectrometry revealed 80 VOCs emitted through the breath, 200 VOCs released by feces, and 80 VOCs emitted through the skin. Statistical analysis of these compounds allowed the identification of 3 tentative breath VOC biomarkers (acetone; 4-methyldecane; D-limonene), 9 tentative feces VOC biomarkers (toluene; [(1,1-dimethylethyl)thio]acetic acid; alpha-thujene; camphene; phenol; o-cymene; 3-(1,1-dimethylethyl)-2,2,4,4-tetramethyl-3-pentanol; 2,5-dimethylhexane-2,5-dihydroperoxide; 2,4-di-tert-butylphenol), and 3 tentative skin VOC biomarkers (ammonia; 1-methoxy-2-propanol; toluene). The possible pathway of these volatile biomarkers is discussed.

Exhaled volatile fatty acids, ruminal methane emission, and their diurnal patterns in lactating dairy cows

To date, the commonly used methods to assess rumen fermentation are invasive. Exhaled breath contains hundreds of volatile organic compounds (VOC) that can reflect animal physiological processes. In the present study, for the first time, we aimed to use a noninvasive metabolomics approach based on high-resolution mass spectrometry to identify rumen fermentation parameters in dairy cows. Enteric methane (CH4) production from 7 lactating cows was measured 8 times over 3 consecutive days using the GreenFeed system (C-Lock Technology Inc.). Simultaneously, exhalome samples were collected in Tedlar gas sampling bags and analyzed offline using a secondary electrospray ionization high-resolution mass spectrometry system. In total, 1,298 features were detected, among them targeted exhaled volatile fatty acids (eVFA; i.e., acetate, propionate, butyrate), which were putatively annotated using their exact mass-to-charge ratio. The intensity of eVFA, in particular acetate, increased immediately after feeding and followed a similar pattern to that observed for ruminal CH4 production. The average total eVFA concentration was 35.5 count per second (CPS), and among the individual eVFA, acetate had the greatest concentration, averaging 21.3 CPS, followed by propionate at 11.5 CPS, and butyrate at 2.67 CPS. Further, exhaled acetate was on average the most abundant of the individual eVFA at around 59.3%, followed by 32.5 and 7.9% of the total eVFA for propionate and butyrate, respectively. This corresponds well with the previously reported proportions of these VFA in the rumen. The diurnal patterns of ruminal CH4 emission and individual eVFA were characterized using a linear mixed model with cosine function fit. The model characterized similar diurnal patterns for eVFA and ruminal CH4 and H2 production. Regarding the diurnal patterns of eVFA, the phase (time of peak) of butyrate occurred first, followed by that of acetate and propionate. Importantly, the phase of total eVFA occurred around 1 h before that of ruminal CH4. This corresponds well with existing data on the relationship between rumen VFA production and CH4 formation. Results from the present study revealed a great potential to assess the rumen fermentation of dairy cows using exhaled metabolites as a noninvasive proxy for rumen VFA. Further validation, with comparisons to rumen fluid, and establishment of the proposed method are required.

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.

Biodiversity indices and Random Forests reveal the potential for striped skunk (Mephitis mephitis) fecal microbial communities to function as a biomarker for oral rabies vaccination

Wildlife disease surveillance and monitoring poses unique challenges when assessing rates of population vaccination, immunity, or infection prevalence. Non-invasively detected biomarkers can help reduce risk to both animal and field personnel during wildlife disease management activities. In this study, we investigated the utility of fecal microbiome data collected from captive striped skunks (Mephitis mephitis) in predicting rabies virus vaccination and infection status. We sequenced the hypervariable region 4 (V4) of the bacterial 16S gene and estimated alpha and beta diversity across timepoints in three groups of skunks: vaccination then rabies virus infection, sham vaccination then rabies virus infection, and rabies virus infected without vaccination. Alpha diversity did not differ among treatment groups but beta diversity between treatments was statistically significant. The phyla Firmicutes and Proteobacteria were dominant among all samples. Using Random Forests, we identified operational taxonomic units (OTUs) that greatly influenced classification of fecal samples into treatment groups. Each of these OTUs was correlated with fecal volatile organic compounds detected from the samples for companion treatment groups in another study. This research is the first to highlight striped skunk microbiome biodiversity as a vaccination biomarker which pushes the frontier on alternative methods for surveillance and monitoring of vaccination and disease in wildlife populations.

Biomarker Metabolites Discriminate between Physiological States of Field, Cave and White-nose Syndrome Diseased Bats

Analysis of volatile organic compound (VOC) emissions using electronic-nose (e-nose) devices has shown promise for early detection of white-nose syndrome (WNS) in bats. Tricolored bats, Perimyotis subflavus, from three separate sampling groups defined by environmental conditions, levels of physical activity, and WNS-disease status were captured temporarily for collection of VOC emissions to determine relationships between these combinations of factors and physiological states, Pseudogymnoascus destructans (Pd)-infection status, and metabolic conditions. Physiologically active (non-torpid) healthy individuals were captured outside of caves in Arkansas and Louisiana. In addition, healthy and WNS-diseased torpid bats were sampled within caves in Arkansas. Whole-body VOC emissions from bats were collected using portable air-collection and sampling-chamber devices in tandem. Electronic aroma-detection data using three-dimensional Principal Component Analysis provided strong evidence that the three groups of bats had significantly different e-nose aroma signatures, indicative of different VOC profiles. This was confirmed by differences in peak numbers, peak areas, and tentative chemical identities indicated by chromatograms from dual-column GC-analyses. The numbers and quantities of VOCs present in whole-body emissions from physiologically active healthy field bats were significantly greater than those of torpid healthy and diseased cave bats. Specific VOCs were identified as chemical biomarkers of healthy and diseased states, environmental conditions (outside and inside of caves), and levels of physiological activity. These results suggest that GC/E-nose dual-technologies based on VOC-detection and analyses of physiological states, provide noninvasive alternative means for early assessments of Pd-infection, WNS-disease status, and other physiological states.

Passive breath monitoring of livestock: Using factor analysis to deconvolve the cattle shed

Respiratory and metabolic diseases in livestock cost the agriculture sector billions each year, with delayed diagnosis a key exacerbating factor. Previous studies have shown the potential for breath analysis to successfully identify incidence of disease in a range of livestock. However, these techniques typically involve animal handling, the use of nasal swabs or fixing a mask to individual animals to obtain a sample of breath. Using a cohort of 26 cattle as an example, we show how the breath of individual animals within a herd can be monitored using a passive sampling system, where no such handling is required. These benefits come at the cost of the desired breath samples unavoidably mixed with the complex cocktail of odours that are present within the cattle shed. Data were analysed using positive matrix factorisation (PMF) to identify and remove non-breath related sources of VOC. In total three breath factors were identified (endogenous-, non-endogenous breath and rumen) and seven factors related to other sources within and around the cattle shed (e.g. foodcattle feed, traffic, urine and faeces). Simulation of a respiratory disease within the herd showed that the abnormal change in breath composition were captured in the residuals of the 10 factor PMF solution, highlighting the importance of their inclusion as part of the breath fraction. Increasing the number of PMF factors to 17 saw the identification of a "diseased" factor, which coincided with the visits of the three "diseased" cattle to the breath monitor platform. This work highlights the important role that factor analysis techniques can play in analysing passive breath monitoring data.

Preservation of vapor samples on adsorbent alumina capillaries and implications for field sampling

Dynamic vapor microextraction (DVME) is a vapor preconcentration method that employs a capillary trap coated with an adsorbent, followed by solvent elution to recover the sample. DVME has been developed for applications in the laboratory, including highly precise vapor pressure measurements, and in the field. When vapor collection is conducted outside the laboratory, samples must almost always undergo some interval of storage representing the time between collection and analysis. This interval may be hours, days, or longer, depending on the situation. Regardless, in all situations there must be confidence that the integrity of the samples is maintained until processing and analysis. In this paper, we present results of two studies that tested the stability of a 50% weathered gasoline headspace sample on alumina PLOT (porous layer open tubular) capillaries stored at room temperature for periods from 24 h up to 20 wk. We used principal component analysis (PCA) to reduce the dimensionality of the chromatographic and mass spectral data and elucidate trends in stability with respect to the complex sample's range of hydrocarbon classes and molecular weights. Both analyses identified changes over storage periods of six weeks or more. The hydrocarbon class analysis, which used selected ion monitoring (SIM) data as input, proved more sensitive to changes over shorter storage periods. Sample integrity was preserved for at least 24 h, but losses, especially of high-volatility compounds, occurred by 168 h (7 d). Near total loss of sample occurred by 20 wk. These findings, which are specific to the sample, adsorbent, and storage conditions, will guide choices in experimental and instrumental design to ensure that data from future field studies is reliable.

Breath analysis for detection and trajectory monitoring of acute respiratory distress syndrome in swine

Despite the enormous impact on human health, acute respiratory distress syndrome (ARDS) is poorly defined, and its timely diagnosis is difficult, as is tracking the course of the syndrome. The objective of this pilot study was to explore the utility of breath collection and analysis methodologies to detect ARDS through changes in the volatile organic compound (VOC) profiles present in breath. Five male Yorkshire mix swine were studied and ARDS was induced using both direct and indirect lung injury. An automated portable gas chromatography device developed in-house was used for point of care breath analysis and to monitor swine breath hourly, starting from initiation of the experiment until the development of ARDS, which was adjudicated based on the Berlin criteria at the breath sampling points and confirmed by lung biopsy at the end of the experiment. A total of 67 breath samples (chromatograms) were collected and analysed. Through machine learning, principal component analysis and linear discrimination analysis, seven VOC biomarkers were identified that distinguished ARDS. These represent seven of the nine biomarkers found in our breath analysis study of human ARDS, corroborating our findings. We also demonstrated that breath analysis detects changes 1–6 h earlier than the clinical adjudication based on the Berlin criteria. The findings provide proof of concept that breath analysis can be used to identify early changes associated with ARDS pathogenesis in swine. Its clinical application could provide intensive care clinicians with a noninvasive diagnostic tool for early detection and continuous monitoring of ARDS.

ARDS, confirmed by lung biopsy, was induced in swine, with breath monitored hourly. Seven VOC markers distinguish ARDS, which are the same as those in human ARDS and can predict ARDS onset ∼3 h earlier than clinical adjudication.https://bit.ly/3zIIIMQ

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.

Detection of Paratuberculosis in Dairy Herds by Analyzing the Scent of Feces, Alveolar Gas, and Stable Air

Paratuberculosis is an important disease of ruminants caused by Mycobacterium avium ssp. paratuberculosis (MAP). Early detection is crucial for successful infection control, but available diagnostic tests are still dissatisfying. Methods allowing a rapid, economic, and reliable identification of animals or herds affected by MAP are urgently required. This explorative study evaluated the potential of volatile organic compounds (VOCs) to discriminate between cattle with and without MAP infections. Headspaces above fecal samples and alveolar fractions of exhaled breath of 77 cows from eight farms with defined MAP status were analyzed in addition to stable air samples. VOCs were identified by GC-MS and quantified against reference substances. To discriminate MAP-positive from MAP-negative samples, VOC feature selection and random forest classification were performed. Classification models, generated for each biological specimen, were evaluated using repeated cross-validation. The robustness of the results was tested by predicting samples of two different sampling days. For MAP classification, the different biological matrices emitted diagnostically relevant VOCs of a unique but partly overlapping pattern (fecal headspace: 19, alveolar gas: 11, stable air: 4-5). Chemically, relevant compounds belonged to hydrocarbons, ketones, alcohols, furans, and aldehydes. Comparing the different biological specimens, VOC analysis in fecal headspace proved to be most reproducible, discriminatory, and highly predictive.

Review on Volatolomic Studies as a Frontier Approach in Animal Research

This paper presents a comprehensive review of the research studies in volatolomics performed on animals so far. At first, the procedures proposed for the collection, preconcentration, and storing of the volatile organic compounds emitted by various biological samples of different animals are presented and discussed. Next, the results obtained in the analysis of the collected volatile samples with analytical equipment are shown. The possible volatile biomarkers identified for various diseases are highlighted for different types of diseases, animal species, and biological samples analyzed. The chemical classes of these compounds, as well as the biomarkers found in a higher number of animal diseases, are indicated, and their possible origin is analyzed. The studies that dealt with the diagnosis of various diseases from sample measurement with electronic nose systems are also presented and discussed. The paper ends with a final remark regarding the necessity of optimization and standardization of sample collection and analysis procedures for obtaining meaningful results.

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.

Volatile Cues Influence Host-Choice in Arthropod Pests

Many arthropod pests of humans and other animals select their preferred hosts by recognising volatile odour compounds contained in the hosts' 'volatilome'. Although there is prolific literature on chemical emissions from humans, published data on volatiles and vector attraction in other species are more sporadic. Despite several decades since the identification of a small number of critical volatiles underpinning specific host-vector relationships, synthetic chemicals or mixtures still largely fail to reproduce the attractiveness of natural hosts to their disease vectors. This review documents allelochemicals from non-human terrestrial animals and considers where challenges in collection and analysis have left shortfalls in animal volatilome research. A total of 1287 volatile organic compounds were identified from 141 species. Despite comparable diversity of entities in each compound class, no specific chemical is ubiquitous in all species reviewed, and over half are reported as unique to a single species. This review provides a rationale for future enquiries by highlighting research gaps, such as disregard for the contribution of breath volatiles to the whole animal volatilome and evaluating the role of allomones as vector deterrents. New opportunities to improve vector surveillance and disrupt disease transmission may be unveiled by understanding the host-associated stimuli that drive vector-host interactions.

Bovine Respiratory Disease: Looking Back and Looking Forward, What Do We See?

Changes in cattle feeding in the twentieth century led to the "Golden Age of Cattle Feeding" on the US High Plains; this was accompanied by recognition that bovine respiratory disease (BRD) is the leading cause of feedlot morbidity and mortality. Decades of research have illuminated the multiple viruses and bacteria that contribute to BRD, which led to vaccines and antimicrobials to prevent, treat, and control BRD. Despite these discoveries, feedlot BRD morbidities do not appear to have changed substantially over this time. New technologies are being developed that have the potential to improve accuracy of BRD detection.

A Data-Driven Prediction Method for an Early Warning of Coccidiosis in Intensive Livestock Systems: A Preliminary Study

Coccidiosis is still one of the major parasitic infections in poultry. It is caused by protozoa of the genus Eimeria, which cause concrete economic losses due to malabsorption, bad feed conversion rate, reduced weight gain, and increased mortality. The greatest damage is registered in commercial poultry farms because birds are reared together in large numbers and high densities. Unfortunately, these enteric pathologies are not preventable, and their diagnosis is only available when the disease is full-blown. For these reasons, the preventive use of anticoccidials-some of these with antimicrobial action-is a common practice in intensive farming, and this type of management leads to the release of drugs in the environment which contributes to the phenomenon of antibiotic resistance. Due to the high relevance of this issue, the early detection of any health problem is of great importance to improve animal welfare in intensive farming. Three prototypes, previously calibrated and adjusted, were developed and tested in three different experimental poultry farms in order to evaluate whether the system was able to identify the coccidia infection in intensive poultry farms early. For this purpose, a data-driven machine learning algorithm was built, and specific critical values of volatile organic compounds (VOCs) were found to be associated with abnormal levels of oocystis count at an early stage of the disease. This result supports the feasibility of building an automatic data-driven machine learning algorithm for an early warning of coccidiosis.

Volatile metabolomic signatures of rabies immunization in two mesocarnivore species

Rabies is a zoonotic disease caused by infection with rabies virus, which circulates naturally in several wild carnivore and bat reservoirs in the United States (US). The most important reservoir in the US from an animal and public health perspective is the raccoon (Procyon lotor). To prevent the westward expansion of a significant raccoon rabies epizootic along the eastern seaboard, an operational control program implementing oral rabies vaccination (ORV) has existed in the US since the 1990s. Recently, two vaccine efficacy studies conducted with raccoons and striped skunks (Mephitis mephitis) provided the opportunity to determine if volatile fecal metabolites might be used to non-invasively monitor ORV programs and/or predict virus protection for these species. The volatile metabolome is a rich source of information that may significantly contribute to our understanding of disease and infection. Fecal samples were collected at multiple time points from raccoons and striped skunks subjected to oral treatment with rabies vaccine (or sham). Intramuscular challenge with a lethal dose of rabies virus was used to determine protection status at six (raccoons) and 11 (skunks) months post-vaccination. In addition to fecal samples, blood was collected at various time points to permit quantitative assessment of rabies antibody responses arising from immunization. Feces were analyzed by headspace gas chromatography with mass spectrometric detection and the chromatographic responses were grouped according to cluster analysis. Cluster scores were subjected to multivariate analyses of variance (MANOVA) to determine if fecal volatiles may hold a signal of immunization status. Multiple regression was then used to build models of the measured immune responses based on the metabolomic data. MANOVA results identified one cluster associated with protective status of skunks and one cluster associated with protective status of raccoons. Regression models demonstrated considerably greater success in predicting rabies antibody responses in both species. This is the first study to link volatile compounds with measures of adaptive immunity and provides further evidence that the volatile metabolome holds great promise for contributing to our understanding of disease and infections. The volatile metabolome may be an important resource for monitoring rabies immunization in raccoons and striped skunks.

Screening of Microbial Volatile Organic Compounds for Detection of Disease in Cattle: Development of Lab-scale Method

The primary hurdle for diagnosis of some diseases is the long incubation required to culture and confirm the presence of bacteria. The concept of using microbial VOCs as "signature markers" could provide a faster and noninvasive diagnosis. Finding biomarkers is challenging due to the specificity required in complex matrices. The objectives of this study were to (1) build/test a lab-scale platform for screening of microbial VOCs and (2) apply it to Mycobacterium avium paratuberculosis; the vaccine strain of M. bovis Bacillus Calmette-Guérin; and M. kansasii to demonstrate detection times greater those typically required for culture. SPME-GC-MS was used for sampling, sample preparation, and analyses. For objective (1), a testing platform was built for headspace sampling of bacterial cultures grown in standard culture flasks via a biosecure closed-loop circulating airflow system. For (2), results show that the suites of VOCs produced by Mycobacteria ssp. change over time and that individual strains produce different VOCs. The developed method was successful in discriminating between strains using a pooled multi-group analysis, and in timepoint-specific multi- and pair-wise comparisons. The developed testing platform can be useful for minimally invasive and biosecure collection of biomarkers associated with human, wildlife and livestock diseases for development of diagnostic point-of-care and field surveillance.

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.

Persistent Spillback of Bovine Tuberculosis From White-Tailed Deer to Cattle in Michigan, USA: Status, Strategies, and Needs

Free-ranging white-tailed deer (Odocoileus virginianus) are believed to be a self-sustaining reservoir for bovine tuberculosis (bTB) in northeastern Lower Michigan, USA. Although a comprehensive control program is in place and on-farm mitigation strategies to curtail bTB transmission between cattle and deer have been implemented for over a decade, cattle and deer continue to become infected with the disease. Thus, renewed motivation to eradicate bTB is needed if that is truly the goal. Recurrent detection of bTB in cattle in the region is of mounting concern for state and federal agricultural agencies, producers, and wildlife managers. Current on-farm mitigation efforts include fencing and refined cattle feeding and watering practices. Liberal removal of antlerless deer through hunter harvest and disease control permits (DCPs) issued to cattle producers and agency sharp shooters have also been ongoing. Although these strategies have merit and efforts to reduce prevalence in deer and occurrence of positive farms are elevated, additional actions are needed. Heightened management actions to combat bTB in deer could include deer vaccination programs, strategic habitat manipulations to redistribute deer from farms, and precision removal of deer in proximity to high-risk farms. Foundational research to address development and delivery of vaccine to free-ranging deer is complete. Strategic management and habitat manipulation could reduce and disperse local concentrations of deer while better meeting wildlife, forestry, and agricultural goals. The responses of local deer populations to targeted removal of individuals are generally understood and there is potential to reduce deer activity around agricultural operations while allowing them to persist nearby on natural foods. We summarize the history and progress to date, discuss the realized merit of novel management strategies, and suggest options to rid deer and cattle in Michigan of bTB.

Smart Animal Agriculture: Application of Real-Time Sensors to Improve Animal Well-Being and Production

Consumption of animal products such as meat, milk, and eggs in first-world countries has leveled off, but it is rising precipitously in developing countries. Agriculture will have to increase its output to meet demand, opening the door to increased automation and technological innovation; intensified, sustainable farming; and precision livestock farming (PLF) applications. Early indicators of medical problems, which use sensors to alert cattle farmers early concerning individual animals that need special care, are proliferating. Wearable technologies dominate the market. In less-value-per-animal systems like sheep, goat, pig, poultry, and fish, one sensor, like a camera or robot per herd/flock/school, rather than one sensor per animal, will become common. PLF sensors generate huge amounts of data, and many actors benefit from PLF data. No standards currently exist for sharing sensor-generated data, limiting the use of commercial sensors. Technologies providing accurate data can enhance a well-managed farm. Development of methods to turn the data into actionable solutions is critical.

Continuous real-time breath analysis in ruminants: effect of eructation on exhaled VOC profiles

BACKGROUND

The analysis of volatile organic compounds (VOCs) in breath allows non-invasive investigations of diseases. Animal studies are conducted as a model to perform research of VOCs and their relation to diseases. In large animal models ruminants were often used as experimental targets. The effect of their physiological eructation on VOC exhalation has not been examined yet and is the objective of this study.

METHODS

Continuous breath profiles of two young cattle, four adult goats and four adult sheep were measured through a mask, covering mouth and nose, in real-time (200 ms) by means of proton transfer reaction time of flight mass spectrometry. Each animal was analysed twelve times for 3 consecutive minutes.

RESULTS

Real-time monitoring yielded a distinction of different episodes in the breath profiles of ruminants. An algorithm to separate eructation episodes and alveolar breath was established. In the first exhalation after eructation at least 19 VOC concentrations increased (up to 36-fold) and went back to initial levels in subsequent exhalations in all investigated ruminants. Decay of concentrations was substance specific. In goats, less VOCs were affected by the eructation compared to cattle and sheep. Breath profiles without exclusion of eructation episodes showed higher variations and median values than profiles where eructation episodes were excluded.

CONCLUSION

Real-time breath analysis of ruminants enables the discrimination and characterisation of alveolar breath and eructation episodes. This leads to a better understanding of variation in breath data and possible origins of VOCs: breath or digestion related. To avoid impairment of breath gas results and to gain further information on bacterial products from the rumen, eructation and alveolar breath data should be analysed separately.

Towards the use of breath for detecting mycobacterial infection: a case study in a murine model

In the present research, the potential of breath analysis by comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS) was investigated for the discrimination between healthy and infected mice. A pilot study employing a total of 16 animals was used to develop a method for breath analysis in a murine model for studying Mycobacterium tuberculosis complex (MTBC) using the M. bovis bacillus Calmette-Guérin. Breath was collected in Tedlar bags and concentrated onto thermal desorption tubes for subsequent analysis by GC×GC-MS. Immunological test and bacterial cell count in bronchoalveolar lavage fluid and mice lung homogenate confirmed the presence of bacteria in the infected group. From the GC×GC-MS analysis, 23 molecules were found to mainly drive the separation between control and infected mice and their tentative identification is provided.This study shows that the overall used methodology is able to differentiate breath between healthy and infected animals, and the information herein can be used to further develop the mouse breath model to study MTBC pathogenesis, evaluate pre-clinical drug regimen efficacy, and to further develop the concept of breath-based diagnostics.

Use of fecal volatile organic compound analysis to discriminate between non-vaccinated and BCG-Vaccinated cattle prior to and after Mycobacterium bovis challenge

Bovine tuberculosis is a zoonotic disease of global public health concern. Development of diagnostic tools to improve test accuracy and efficiency in domestic livestock and enable surveillance of wildlife reservoirs would improve disease management and eradication efforts. Use of volatile organic compound analysis in breath and fecal samples is being developed and optimized as a means to detect disease in humans and animals. In this study we demonstrate that VOCs present in fecal samples can be used to discriminate between non-vaccinated and BCG-vaccinated cattle prior to and after Mycobacterium bovis challenge.

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.

Comparison of volatile organic compounds from lung cancer patients and healthy controls-challenges and limitations of an observational study

This paper outlines the design and performance of an observational study on the profiles of volatile organic compounds (VOCs) in the breath of 37 lung cancer patients and 23 healthy controls of similar age. The need to quantify each VOC considered as a potential disease marker on the basis of individual calibration is elaborated, and the quality control measures required to maintain reproducibility in breath sampling and subsequent instrumental trace VOC analysis using solid phase microextraction-gas chromatography-mass spectrometry over a study period of 14 months are described. Twenty-four VOCs were quantified on the basis of their previously suggested potential as cancer markers. The concentration of aromatic compounds in the breath was increased, as expected, in smokers, while lung cancer patients displayed significantly increased levels of oxygenated VOCs such as aldehydes, 2-butanone and 1-butanol. Although sets of selected oxygenated VOCs displayed sensitivities and specificities between 80% and 90% using linear discriminant analysis (LDA) with leave-one-out cross validation, the effective selectivity of the breath VOC approach with regard to cancer detection is clearly limited. Results are discussed against the background of the literature on volatile cancer marker investigations and the prospects of linking increased VOC levels in patients' breath with approaches that employ sniffer dogs. Experience from this study and the literature suggests that the currently available methodology is not able to use breath VOCs to reliably discriminate between cancer patients and healthy controls. Observational studies often tend to note significant differences in levels of certain oxygenated VOCs, but without the resolution required for practical application. Any step towards the exploitation of differences in VOC profiles for illness detection would have to solve current restrictions set by the low and variable VOC concentrations. Further challenges are the technical complexity of studies involving breath sampling and possibly the limited capability of current analytical procedures to detect unstable marker candidates.

E-nose identification of Salmonella enterica in poultry manure

A DiagNose II electronic nose (e-nose) system was tested to evaluate the performance of such systems in the detection of the Salmonella enterica pathogen in poultry manure. To build a database, poultry manure samples were collected from 7 broiler houses, samples were homogenised, and subdivided into 4 portions. One portion was left as is; the other three portions were artificially infected with S. enterica. An artificial neural network (ANN) model was developed and validated using the developed database. In order to test the performance of DiagNose II and the ANN model, 16 manure samples were collected from 6 different broiler houses and tested using these two systems. The results showed that DiagNose II was able to classify manure samples correctly as infected or non-infected based on the ANN model developed with a 94% level of accuracy.

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.

Fecal Volatile Organic Ccompound Profiles from White-Tailed Deer (Odocoileus virginianus) as Indicators of Mycobacterium bovis Exposure or Mycobacterium bovis Bacille Calmette-Guerin (BCG) Vaccination

White-tailed deer (Odocoileus virginianus) serve as a reservoir for bovine tuberculosis, caused by Mycobacterium bovis, and can be a source of infection in cattle. Vaccination with M. bovis Bacille Calmette Guerin (BCG) is being considered for management of bovine tuberculosis in deer. Presently, no method exists to non-invasively monitor the presence of bovine tuberculosis in deer. In this study, volatile organic compound profiles of BCG-vaccinated and non-vaccinated deer, before and after experimental challenge with M. bovis strain 95–1315, were generated using solid phase microextraction fiber head-space sampling over suspended fecal pellets with analysis by gas chromatography/mass spectrometry. Chromatograms were processed using XCMS Online to characterize ion variation among treatment groups. The principal component scores resulting from significant (α = 0.05) ion responses were used to build linear discriminant analysis models. The sensitivity and specificity of these models were used to evaluate the feasibility of using this analytical approach to distinguish within group comparisons between pre- and post-M. bovis challenge: non-vaccinated male or female deer, BCG-vaccinated male deer, and the mixed gender non-vaccinated deer data. Seventeen compounds were identified in this analysis. The peak areas for these compounds were used to build a linear discriminant classification model based on principal component analysis scores to evaluate the feasibility of discriminating between fecal samples from M. bovis challenged deer, irrespective of vaccination status. The model best representing the data had a sensitivity of 78.6% and a specificity of 91.4%. The fecal head-space sampling approach presented in this pilot study provides a non-invasive method to discriminate between M. bovis challenged deer and BCG-vaccinated deer. Additionally, the technique may prove invaluable for BCG efficacy studies with free-ranging deer as well as for use as a non-invasive monitoring system for the detection of tuberculosis in captive deer and other livestock.

Physiological variability in volatile organic compounds (VOCs) in exhaled breath and released from faeces due to nutrition and somatic growth in a standardized caprine animal model

Physiological effects may change volatile organic compound (VOC) concentrations and may therefore act as confounding factors in the definition of VOCs as disease biomarkers. To evaluate the extent of physiological background variability, this study assessed the effects of feed composition and somatic growth on VOC patterns in a standardized large animal model. Fifteen clinically healthy goats were followed during their first year of life. VOCs present in the headspace over faeces, exhaled breath and ambient air inside the stable were repeatedly assessed in parallel with the concentrations of glucose, protein, and albumin in venous blood. VOCs were collected and analysed using solid-phase or needle-trap microextraction and gas chromatograpy together with mass spectroscopy. The concentrations of VOCs in exhaled breath and above faeces varied significantly with increasing age of the animals. The largest variations in volatiles detected in the headspace over faeces occurred with the change from milk feeding to plant-based diet. VOCs above faeces and in exhaled breath correlated significantly with blood components. Among VOCs exhaled, the strongest correlations were found between exhaled nonanal concentrations and blood concentrations of glucose and albumin. Results stress the importance of a profound knowledge of the physiological backgrounds of VOC composition before defining reliable and accurate marker sets for diagnostic purposes.