Recipient Organization
UNIV OF MARYLAND
(N/A)
COLLEGE PARK,MD 20742
Performing Department
(N/A)
Non Technical Summary
Cattle convert crops like grass and food byproducts to high-quality protein like milk and meat. Microorganisms that live in the cow's first stomach chamber, called the rumen, initially digest these feeds, and the cow lives on the byproducts of the digestion and the microbes themselves. However, this digestion and fermentation process also releases methane gas, which represents a loss of 2% to 10% of the energy in the diet, and it is a potential greenhouse gas. The goal of the proposed research is to improve the way digestion occurs in the cow's rumen to decrease methane emissions and to thereby increase the efficiency and improve the environmental impact of food production from available feeds. The overarching hypothesis for this research is that mathematical models of fermentation based on classical laws of physics can explain and predict the profile of end products from fermentation in the cow's rumen. Specific objectives include studying the way different nutrients and probiotics in the diet cause shifts in metabolism based on laws of physics. We expect this research to show how to regulate different fermentation pathways to improve efficiencies of production and health, and ultimately to identify ways to decrease wasteful methane emissions from cattle. Results will be used to improve ration formulation for cattle, and to predict energy and protein availability for different feeds.
Animal Health Component
15%
Research Effort Categories
Basic
85%
Applied
15%
Developmental
(N/A)
Goals / Objectives
The goal of the proposed project is to develop and communicate an improved understanding of the mechanisms causing changes in ruminal fermentation that affect the profile of volatile fatty acids (VFA) and gases (carbon dioxide, methane and hydrogen).The primary objectives will be: 1) determine the effects of several enzyme inhibitors on enzyme kinetics and thermodynamics; 2) determine variation in enzyme kinetics and thermodynamics due to diurnal variation, type of diet, and transition from one diet to another; 3) correlate metagenomic and metatranscriptomic measurements with ruminal fluid microbial activity; 4) develop a dynamic mechanistic model incorporating data collected in the proposed project; and 5) this research will be available to disseminate to research, extension, and academic audiences using the developed computer models as tools.
Project Methods
Both in vitro and in vivo methods will involve measurements of VFA and gas production in small samples of ruminal fluid immediately after sampling. Ruminal fluid will be sampled directly into centrifuge tubes, which will be stoppered as they are removed to prevent changes in gas composition. Generally, 10 ml of ruminal fluid will be incubated in sealed 15-ml tubes with initial gas headspace filled with rumen gases at sampling. A hypodermic needle attached to a gas-tight syringe will be inserted through the stopper to quantify and collect produced gases. Intentionally, this method does not allow time for the ruminal fluid to change appreciably (e.g. pH become much lower), or for the activity of the microbial population to change. Thus, results will represent the instantaneous velocity of the reactions at the time the sample is taken.3.3 VFA and gas measurementsThe liquid samples will be analyzed without derivatization by a gas chromatograph (GC) with FID detector using a packed column for acetate, propionate, butyrate, isobutyrate, valerate, and isovalerate. The gases CO2, CH4, H2, and N2 will be collected in gas-tight syringes and measured directly on a GC with thermal conductivity detector. N2 gas will be an indicator of leakage.Isotope enrichment will be measured on selected samples by Dr. Nishanth Sunny. An isotope ratio mass spectrometer (IRMS) coupled to a gas chromatograph (GC) via a combustion oven (comb) will be used to measure enrichments. VFA will be introduced using a solid phase micro extraction method (Yo, 1999). CO2 and CH4 enrichment will also be determined on this machine as described by Ai et al. (2013) This device has lower limits of detection below 0.001% enrichment.3.4 Perturbation experimentsThe rates of methane and VFA production, and VFA interconversion will be measured, with addition of 5 levels of different substrates including: H2, CO2, D-glucose, sodium salts of acetate, succinate, lactate, propionate and butyrate, for a total of 40 tubes in addition to the 2 tubes with no additions. Samples with added gases will be fermented under pressure, but other samples will be fermented at atmospheric pressure by allowing attached syringes to expand.3.5 Calculation of deltaG in ruminal fluidThe deltaG for production from glucose and interconversion of each end product (CO2, H2, Acetate, Propionate, Butyrate, Lactate, and Succinate, etc.) will be calculated for both in vitro and in vivo experiments according to established equations (e.g. Ungerfeld and Kohn, 2006)3.6 Calculation of Vmax and Km Data collected from the perturbation experiment in Section 3.4 will be used to calculate apparent Vmax and Km for all production and interconversion pathways between substrates and products. The Vmax and Km will be determined by regression of the inverse of initial substrate by the response plotted as the inverse of the initial velocity; slope = Vmax/Km and X intercept = -Km-1 in accordance with Lineweaver-Burk plots.3.7 In vitro experiments with inhibitorsThe deltaG, Vmax and Km will be determined as described above for ruminal fluid taken 4 hours after feeding and used to determine kinetic and thermodynamic parameters with or without addition of one of two-levels of the following inhibitors: ionophore, pH, NO3, and SO3.3.8 In vivo experiment The proposed experiment will be conducted with 4 rumen-cannulated late-lactation or non-lactating Holstein cows in a double switchback design. Treatments will be two different forage:concentrate ratios (100% forage and 70:30) by substituting corn grain for timothy hay. Samples will be taken on days 2, 9, and 21 at 4-hours after feeding for each of the 4 periods. The earlier samples will show changes during transition from one diet to the other. On the 21st day of each treatment, samples will also be taken at 1, 8, and 16 hours after morning feeding, as well as 4 hours after feeding as indicated. Thus, treatments will represent different forage to concentrate ratios, transitions from one diet to the other, and diurnal variation.Stable isotopes will be used for additional measurements. Stable 15N-NH4+ will be added to two duplicate samples without any other additions to measure microbial growth on each treatment. Stable 13C-label will be used to show the specific conversion from added substrate to major end products. Thus, these results will show Vmax for specific conversions of each added substrate to the possible end products. The specific Vmax will show which pathway steps are affected by treatments.3.9 Metagenomics and metatranscriptomicsThe samples taken on day 21 will be composited over the 4 time points for each cow and period and analyzed for metagenomic and metatranscriptomic differences between the 8 observations of animals on high-concentrate diets and the 8 observations on high-forage diets. In addition to descriptive analysis of the populations and transcriptome, 16S r-RNA analysis will be used to quantify shifts in populations involved in alternative pathways for propionate synthesis (e.g. lactic acid bacteria vs. succinic acid bacteria), and changes in gene expression for production and utilization of lactic acid and succinate will be determined. Changes in quantity of methanogens, and reductive acetogens, and the transcripts for the processes they carry out will also be determined.3.10 Development of a mechanistic modelThe in vitro and vivo experiments will be used to develop a mathematical model incorporating the kinetic and thermodynamic parameters. Data will be collected for rates and ?G for production and interconversion of each major VFA (acetate, propionate, butyrate, succinate, and lactate). VFA production from glucose or CO2 and H2 will be quantified. All kinetic and thermodynamic parameters will be calculated for pathways to and from pyruvate, the central intermediate for most VFA production by solving simultaneously using the data representing overlapping pathways. A compartmental model will be fit using the variables of deltaG, Km, and Vmax for each set of conditions (e.g. high forage or high concentrate, tested inhibitors), and then the variables will be adjusted for different types of diets. This adjustment can also be predicted mechanistically from the energy obtained by organisms that carry out certain reactions. For example, as more substrate is metabolized in a specific pathway, organisms that carry out the pathway would grow and their activity would increase. If deltaG becomes very negative because of low product concentration, higher growth rates may be predicted. For example, methanogen growth rate increases as deltaG becomes more negative. Since changes in Vmax and Km that are predicted mechanistically are likely to be less accurate than empirically predicted parameters, an alternative model will use force functions for setting these parameters for different types of diets. Both models will later be tested for prediction accuracy compared with published studies. Generally, more empirical models are more accurate, but provide less information to test potential mechanisms of metabolism control. However, the more empirical model is likely to be more readily applicable in the field for desired predictions. The dynamic models will be developed using the software ScientistTM from Micromath Corp and demonstrated for teaching using StellaTM.