Exhalomics as a noninvasive method for assessing rumen fermentation in dairy cows: Can exhaled-breath metabolomics replace rumen sampling?

Previously, we used secondary electrospray ionization-mass spectrometry (SESI-MS) to investigate the diurnal patterns and signal intensities of exhaled (EX) volatile fatty acids (VFA) of dairy cows. The current study aimed to validate the potential of an exhalomics approach for evaluating rumen fermentation. The experiment was conducted in a switchback design, with 3 periods of 9 d each, including 7 d for adaptation and 2 d for sampling. Four rumen-cannulated original Swiss Brown (Braunvieh) cows were randomly assigned to 1 of 2 diet sequences (ABA or BAB): (A) low starch (LS; 6.31% starch on a dry matter basis) and (B) high starch (HS; 16.2% starch on a dry matter basis). Feeding was once per day at 0830 h. Exhalome (with the GreenFeed System), and rumen samples were collected 8 times to represent every 3 h of a day, and EX-VFA and ruminal (RM)-VFA were analyzed using SESI-MS and HPLC, respectively. Furthermore, the VFA concentration in the gas phase (HR-VFA) was predicted based on RM-VFA and Henry's Law (HR) constants. No interactions were identified between the types of diets (HS vs. LS) and the measurement methods on daily average VFA profiles (RM vs. EX or HR vs. EX), suggesting a consistent performance among the methods. Additionally, when the 3-h interval VFA data from HS and LS diets were analyzed separately, no interactions were observed between methods and time of day, indicating that the relative daily pattern of VFA molar proportions was similar regardless of the VFA measurement method used. The results revealed that the levels of acetate sharply increased immediately after feeding, trailed by an increase in the acetate:propionate ratio and a steady increase for propionate (2 h after feeding the HS diet, 4 h for LS), and butyrate. This change was more pronounced for the HS diet than the LS diet. However, there was no overall diet effect on the VFA molar proportions, although the measurement methods affected the molar proportions. Furthermore, we observed a strong positive correlation between the levels of RM and EX acetate for both diets (HS: r = 0.84; LS: r = 0.85), RM and EX propionate (r = 0.74), and RM and EX acetate:propionate ratio (r = 0.80). Both EX-VFA and RM-VFA exhibited similar responses to feeding and dietary treatments, suggesting that EX-VFA could serve as a useful proxy for characterizing RM-VFA molar proportions to evaluate rumen fermentation. Similar relationships were observed between RM-VFA and HR-VFA. In conclusion, this study underscores the potential of exhalomics as a reliable approach for assessing rumen fermentation. Moving forward, research should further explore the depth of exhalomics in ruminant studies to provide a comprehensive insight into rumen fermentation metabolites, especially across diverse dietary conditions.

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.

Volatolomics: A broad area of experimentation

Chemical analysis (detection and monitoring) of compounds associated with the metabolic activities of an organism is at the cutting edge of science. Volatile metabolomics (volatolomics) are applied in a broad range of applications including: biomedical research (e.g. disease diagnostic tools, personalized healthcare and nutrition, etc.), toxicological analysis (e.g. exposure tool to environmental pollutants, toxic and hazardous chemical environments, industrial accidents, etc.), molecular communications, forensics, safety and security (e.g. search and rescue operations). In the present review paper, an overview of recent advances and applications of volatolomics will be given. The main focus will be on volatile organic compounds (VOCs) originating from biological secretions of various organisms (e.g. microorganisms, insects, plants, humans) and resulting fusion of chemical information. Bench-top and portable or field-deployable technologies-systems will also be presented and discussed.