Crowd monitoring in dairy cattle-real-time VOC profiling by direct mass spectrometry

High and low pathogenicity avian influenza virus discrimination and prediction based on volatile organic compounds signature by SIFT-MS: a proof-of-concept study

High and low pathogenicity avian influenza viruses (HPAIV, LPAIV) are the primary causes of poultry diseases worldwide. HPAIV and LPAIV constitute a major threat to the global poultry industry. Therefore, early detection and well-adapted surveillance strategies are of the utmost importance to control the spread of these viruses. Volatile Organic Compounds (VOCs) released from living organisms have been investigated over the last decades as a diagnostic strategy. Mass spectrometry instruments can analyze VOCs emitted upon viral infection. Selected ion flow tube mass spectrometry (SIFT-MS) enables direct analysis of cell headspace in less than 20 min. As a proof-of-concept study, we investigated the ability of a SIFT-MS coupled sparse Partial Least Square-Discriminant Analysis analytical workflow to discriminate IAV-infected cells. Supernatants of HPAIV, LPAIV, and control cells were collected from 1 to 72 h post-infection and analyzed using our analytical workflow. At each collection point, VOCs' signatures were first identified based on four independent experiments and then used to discriminate the infectious status of external samples. Our results indicate that the identified VOCs signatures successfully discriminate, as early as 1-h post-infection, infected cells from the control cells and differentiated the HPAIV from the LPAIV infection. These results suggest a virus-dependent VOCs signature. Overall, the external samples' status was identified with 96.67% sensitivity, 100% specificity, and 97.78% general accuracy.

Carbon Dioxide, Methane, and Synthetic Cattle Breath Volatiles Attract Host-Seeking Stable Flies, Stomoxys calcitrans

Stable flies, Stomoxys calcitrans (L.), are blood-feeding ectoparasites of cattle. Host-seeking stable flies respond to various cattle host cues, but a potential role of cattle breath gases [carbon dioxide (CO2), methane (CH4)] and cattle breath volatiles (acetone, isoprene, 2-butanone, 2-propanol, propionic acid, 3-methyl butyric acid, phenol), alone or in combination, on host-seeking behavior of stable flies has not yet been comprehensively investigated. In laboratory and greenhouse experiments, we tested the hypotheses that (1) CO2 and CH4 interactively attract stable flies, (2) CO2 'gates' attraction of stable flies to CH4, and (3) breath volatiles on their own, or in combination with both CO2 and CH4, attract stable flies. In Y-tube olfactometer experiments, the blend of CH4 (0.5%) and CO2 (1%) in breathing air ('b-air') attracted significantly more female flies than CH4, or CO2, in b-air. The flies' responses to CH4 were contingent upon their prior or concurrent exposure to CO2. In two-choice experiments in a large greenhouse compartment, significantly more flies landed on the host-look-alike barrel that disseminated a blend of CO2 and CH4 in b-air (CO2/CH4/b-air) than on the barrel disseminating either b-air or CO2. Moreover, significantly more flies landed on the barrel that disseminated synthetic breath volatiles (SBVs) than on the barrel disseminating b-air. The blend of CO2/CH4/b-air and SBVs elicited more fly landings on barrels than CO2/CH4/b-air but not than SBVs. SBVs, possibly combined with both CH4 and CO2, could be developed as a lure to enhance trap captures of stable flies in livestock production facilities.

Current Limitations of Staph Infection Diagnostics, and the Role for VOCs in Achieving Culture-Independent Detection

Staphylococci are broadly adaptable and their ability to grow in unique environments has been widely established, but the most common and clinically relevant staphylococcal niche is the skin and mucous membranes of mammals and birds. S. aureus causes severe infections in mammalian tissues and organs, with high morbidities, mortalities, and treatment costs. S. epidermidis is an important human commensal but is also capable of deadly infections. Gold-standard diagnostic methods for staph infections currently rely upon retrieval and characterization of the infectious agent through various culture-based methods. Yet, obtaining a viable bacterial sample for in vitro identification of infection etiology remains a significant barrier in clinical diagnostics. The development of volatile organic compound (VOC) profiles for the detection and identification of pathogens is an area of intensive research, with significant efforts toward establishing breath tests for infections. This review describes the limitations of existing infection diagnostics, reviews the principles and advantages of VOC-based diagnostics, summarizes the analytical tools for VOC discovery and clinical detection, and highlights examples of how VOC biomarkers have been applied to diagnosing human and animal staph infections.

Estrus Detection in a Dairy Herd Using an Electronic Nose by Direct Sampling on the Perineal Region

Estrus detection is very important for the profitability of dairy herds. Different automatic systems for estrus detection have been developed over the last decades. Our study aimed to assess the ability of the electronic nose (EN) MENT-EGAS prototype to detect estrus, based on odor release from the perineal headspace in dairy cattle by direct sampling. The study was performed in an Italian dairy farm using 35 multiparous Holstein-Friesian cows. The cows were divided into three groups: group I included 10 lactating 5-month pregnant cows, group II included 19 lactating cycling cows, and group III included 6 cows that were artificially inseminated 18 days before the trial. Odors from the perineal headspace were collected using the MENT-EGAS prototype. In group I, odors were collected once a day for 5 consecutive days. In group II, odors were collected twice daily from day 18 until day 1 of the reproductive cycle. In group III, odors were also collected twice daily from the presumable day 18 of gestation until day 22. Principal component analyses (PCA) of the perineal headspace samples were performed. PCA in group I revealed no significant discrimination. PCA in group II revealed clear discrimination between proestrus and estrus, and between estrus and metestrus but no significant discrimination was obtained between proestrus and metestrus. PCA in group III revealed that in four cows the results were similar to group I and in two cows the results were similar to group II. On day 40 of the presumable pregnancy, the ultrasound examination revealed that only the four cows were pregnant and the other two cows were regularly cycling. On the basis of our findings, we conclude that it is possible to accurately detect estrus in dairy cattle from directly collected odor samples using the MENT-EGAS prototype. This represents the first study of estrus detection using an EN detection by direct sampling. EN technologies, such as MENT-EGAS, could be applied in the future in dairy cattle farms as a precise, non-invasive method for estrus detection.

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.

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.

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.

Characterization of particulate and gaseous pollutants from a French dairy and sheep farm

Agricultural activities highly contribute to atmospheric pollution, but the diversity and the magnitude of their emissions are still subject to large uncertainties. A field measurement campaign was conducted to characterize gaseous and particulate emissions from an experimental farm in France containing a sheep pen and a dairy stable. During the campaign, more than four hundred volatile organic compounds (VOCs) were characterized using an original combination of online and off-line measurements. Carbon dioxide (CO₂) and ammonia (NH₃) were the most concentrated compounds inside the buildings, followed by methanol, acetic acid and acetaldehyde. A CO₂ mass balance model was used to estimate NH₃ and VOC emission rates. To our knowledge, this study constitutes the first evaluation of emission rates for most of the identified VOCs. The measurements show that the dairy stable emitted more VOCs than the sheep pen. Despite strong VOC and NH₃ emissions, the chemical composition of particles indicates that gaseous farm emissions do not affect the loading of fine particles inside the farm and is mainly explained by the low residence time inside the buildings. The experimental dataset obtained in this work will help to improve emissions inventories for agricultural activities.