Previous attempts to apply statistical models, which correlate nutrient intake with methane production, have been of limited value where predictions are obtained for nutrient intakes and diet types outside those used in model construction. Dynamic mechanistic models have proved more suitable for extrapolation, but they remain computationally expensive and are not applied easily in practical situations. The first objective of this research focused on employing conventional techniques to generate statistical models of methane production appropriate to United Kingdom dairy systems. The second objective was to evaluate these models and a model published previously using both United Kingdom and North American data sets. Thirdly, nonlinear models were considered as alternatives to the conventional linear regressions. The United Kingdom calorimetry data used to construct the linear models also were used to develop the three nonlinear alternatives that were all of modified Mitscherlich (monomolecular) form. Of the linear models tested, an equation from the literature proved most reliable across the full range of evaluation data (root mean square prediction error = 21.3%). However, the Mitscherlich models demonstrated the greatest degree of adaptability across diet types and intake level. The most successful model for simulating the independent data was a modified Mitscherlich equation with the steepness parameter set to represent dietary starch-to-ADF ratio (root mean square prediction error = 20.6%). However, when such data were unavailable, simpler Mitscherlich forms relating dry matter or metabolizable energy intake to methane production remained better alternatives relative to their linear counterparts.

Dietary intervention to reduce methane emissions from lactating dairy cattle is both environmentally and nutritionally desirable due to the importance of methane as a causative agent in global warming and as a significant loss of feed energy. Reliable prediction systems for methane production over a range of dietary inputs could be used to develop novel dietary regimes for the limitation of feed energy loss to methane. This investigation builds on previous attempts at modeling methanogenesis and involves the development of a dynamic mechanistic model of wholerumen function. The model incorporates modifications to certain ruminal fermentation parameters and the addition of a postruminal digestive element. Regression analysis showed good agreement between observed and predicted results for experimental data taken from the literature (r2 = 0.76, root mean square prediction error = 15.4%). Evaluation of model predictions for experimental observations from five calorimetry studies (67 observations) with lactating dairy cows at the Centre for Dairy Research, in Reading, U.K., shows an underprediction (2.1 MJ/d) of methane production (r2 = 0.46, root mean square prediction error = 12.4%). Application of the model to develop diets for minimizing methanogenesis indicated a need to limit the ratio of lipogenic to glucogenic VFA in the rumen and hindgut. This may be achieved by replacing soluble sugars in the concentrate with starch or substituting corn silage for grass silage. On a herd basis, the model predicted that increasing dietary energy intake per cow can minimize the annual loss of feed energy through methane production. The mechanistic model is a valuable tool for predicting methane emissions from dairy cows.

Improving N utilization in dairy cows and especially reducing N output in excreta is desirable due to global concerns of agricultural contribution of N to environmental pollution, particularly as ammonia. Data from five N balance experiments were used to develop a dynamic model that was evaluated with independent data. Model predictions of feces, urine, and milk outputs were close to observed values. Statistical analysis showed that 96% of mean square prediction error for feces and urine N output predictions was due to random variation. However, the model tends to overpredict milk N output, especially at higher N intake levels. Evaluation of model predictions for independent experimental observations from Agricultural Development Advisory Service at Bridgets (U.K.) showed good agreement between predicted and observed urine N output (95% due to random variation). However, there was a slight underprediction for fecal N output (14% mean square prediction error due to bias) and overprediction of milk N output (22% of mean square prediction error due to bias). The model predictions of N outputs in excreta were sensitive to changes in energy concentration of the diet. Dietary protein degradability had only a small influence on predicted fecal N output. However, the model was sensitive in its predictions of urine N when protein degradability was varied. Application of the model to assess reduction in ammonia emissions from dairy cows showed that increasing the energy concentration could potentially reduce ammonia emissions by up to 25% per cow. Similarly, reducing CP concentration in the diet to about 16% could reduce ammonia production by 20% and lower degradability of CP to match microbial requirement by 19% per cow. The model is a first step toward a mechanistic approach of nutrient modeling, and it is a valuable method for predicting N excretions and estimating N emissions from dairy systems.

This study was conducted to document the development of populations of lactic acid bacteria (LAB) and Lactobacillus buchneri in alfalfa silage treated with various inoculants. Wilted and chopped alfalfa (45% dry matter) was treated with 1) distilled water (untreated, U), 2) Lactobacillus buchneri 40788 (4 x 10(5) cfu/g; LB), or 3) L. buchneri 40788 (4 x 10(5) cfu/g) and Pediococcus pentosaceus (1 x 10(5) cfu/g; LBPP). Forages were packed into triplicate vacuum-sealed, nylon-polyethylene bags per treatment, and ensiled for 2, 5, 45, 90, and 180 d. Viable (cfu) LAB in forage and silage were quantified by traditional plating on selective agar, and numbers of L. buchneri (cfu-equivalent, cfu-E) were quantified by real-time quantitative PCR. Fresh, untreated forage had 5.52 log cfu of LAB/g and 3.79 log cfu-E of L. buchneri/g. After 2 d of ensiling, numbers of LAB increased to >8 log cfu/g in all silages. In contrast, numbers of L. buchneri in U remained below 4 log cfu-E/g but reached approximately 7 log cfu-E/g in LB and LBPP. From d 5 onward, numbers of L. buchneri in U remained below 6 log cfu-E/g but approached 9 log cfu-E/g in LB and LBPP. The pH was lower in LBPP compared with U and LB after 2 and 5 d of ensiling, but pH was lower for U compared with LB and LBPP thereafter. Treatments LB and LBPP had more acetic acid than U at 45 d of ensiling, which coincided with detectable amounts of 1,2 propanediol. Inoculation with LBPP resulted in silage with the highest concentration of 1,2 propanediol after 180 d of ensiling. From d 45 onward, LB and LBPP silages had lower concentrations of residual water-soluble carbohydrates but had higher concentrations of ammonia-N than U. In conclusion, epiphytic L. buchneri can be detected in alfalfa but this population is unable to lead the silage fermentation. In contrast, when L. buchneri was added to silage as an inoculant, the numbers of L. buchneri (cfu-E) increased markedly but did not dictate fermentation until 45 d of ensiling. These findings help to explain why the response (in increased acetic acid) from the addition of L. buchneri in silages is not immediate.

Phosphorus (P) is a key mineral in energy metabolism and is essential in nearly every biochemical aspect of dairy cow metabolism. Therefore, P needs to be supplied in sufficient quantity to optimize animal performance. However, dairy cows only use 30 – 45% of their dietary P intake and the rest is excreted mainly in faeces. Excess faecal excretion can lead to P accumulation and saturation in the soil and filter into groundwater or remain in surface water (Tamminga, 1996), which is known to cause eutrophication. It is therefore desirable to formulate P rations according to the requirement of the animals and thereby reduce P pollution. The objective of the present study was to develop a dynamic model of P metabolism in dairy cows and use that to identify and quantify trends of P excretion as a function of P intake and investigate effects of energy supplementation on P utilisation.

Chopped barley forage was ensiled untreated or treated with several doses (1 x 10(5) to 1 x 10(6) cfu/g of fresh forage) of Lactobacillus buchneri 40788 in laboratory silos and untreated or treated (4 x 10(5) cfu/g) in a farm silo. Silage from the farm silos was fed to lactating cows. In the laboratory silo, the effects of inoculation on fermentation and aerobic stability were also compared to silage treated with a commercial inoculant and a buffered propionic acid additive. Inoculation with L. buchneri 40788 decreased the final concentrations of lactic acid but increased concentrations of acetic acid and ethanol in silage from laboratory and farm silos. Silages stored in laboratory silos did not heat after exposure to air for 7 d and were then mixed with alfalfa silage and a concentrate to form total mixed rations (TMR) that were further exposed to air. The TMR containing silages treated with L. buchneri 40788 or a buffered propionic-acid-based additive took longer to heat and spoil than the TMR containing untreated silage or silagetreated with the commercial inoculant. Silage stored in a farm silo and treated with L. buchneri 40788 had fewer yeasts and molds than did untreated silage. Aerobic stability was greater in treated silage alone and in a TMR containing treated silage. Dry matter intake (18.6 kg/d), milk production (25.7 kg/d), and milk composition did not differ between cows fed a TMR containinguntreated or treated silage. These findings show that L. buchneri can improve the aerobic stability of barley silage in laboratory and farm silos and that feeding treated silage had no negative effect on intake or performance.

As the global threat of drug- and antibiotic-resistant bacteria continues to rise, new strategies are required to advance the drug discovery process. This work describes the construction of an array of Escherichia coli strains for use in whole-cell screens to identify new antimicrobial compounds. We used the recombination systems from bacteriophages lambda and P1 to engineer each strain in the array for low-level expression of a single, essential gene product, thus making each strain hypersusceptible to specific inhibitors of that gene target. Screening of nine strains from the array in parallel against a large chemical library permitted identification of new inhibitors of bacterial growth. As an example of the target specificity of the approach, compounds identified in the whole-cell screen for MurA inhibitors were also found to block the biochemical function of the target when tested in vitro.

The acid-fastness of all mycobacteria is based upon a shared universal cell wall core structure. The mycobacterial cell wall consists of an outer lipid layer and an inner peptidoglycan layer. The outer layer is highly impermeable and is composed of unique 70 -90 carbon-containing lipids, known as mycolic acids. The mycolic acids are esterified to the non-reducing terminal arabinosyl residues of the polysaccharide arabinogalactan (1-5). The reducing end of arabinogalactan is connected to the peptidoglycan via the disaccharide linker, ␣-L-Rha-(133)␣-DGlcNAc-(13phosphate). Structural analyses showed that the integrity of the whole two-layer mycolic acid peptidoglycan assembly hinges on the presence of the rhamnosyl moiety as depicted in Fig. 1A. The complete structure of the linker is illustrated in Fig. 1B, and the reaction catalyzed by the enzyme, dTDP-Rha:␣-D-GlcNAc-pyrophosphate polyprenol, ␣-3-Lrhamnosyltransferase (referred to as rhamnosyltransferase in this study) is shown in Fig. 1C. The rhamnosyl residue and much if not all of the arabinogalactan polysaccharide are synthesized on GlcNAc-P-P-decaprenyl carrier lipid (6). The eventual transfer of the arabinogalactan-Rha-GlcNAc-phosphate unit to the O-6 of a muramic acid places the polysaccharide in mass onto the peptidoglycan. Finally, at some still to be defined point, the mycolic acids are attached to arabinofuranosyl residues at the non-reducing end of arabinogalactan.To further define and characterize the essential steps involved in the synthesis of the mycobacterial cell wall core, the classic microbial approach of isolating conditional lethal mutants was undertaken. Our strategy was to isolate temperature-sensitive (TS) 1 mutants in the genetically amenable and relatively fast growing Mycobacterium smegmatis mc 2 155 (7). A preferred large temperature range that would support growth precluded Mycobacterium tuberculosis from serving as the host for the generation of TS mutants. TS mutants would be genetically complemented with M. tuberculosis genomic DNA in hopes of identifying essential genes encoding cell wall biosynthetic enzymes. Herein, we describe the isolation of a TS cell wall mutant and the independent genetic complementation of that mutant with a M. tuberculosis gene and an E. coli gene. We report biochemical characterization of the TS mutant, the deduced amino acid change due to the mutation, the genetic complementation of an E. coli mutant to confirm the function of a M. tuberculosis gene, and the effect of the mutation on mycobacterial viability after exposure to non-permissive temperatures. EXPERIMENTAL PROCEDURESIsolation of TS Mutants-The strategy for the isolation and enrichment of bacterial TS mutants in a culture as outlined by A. Morris Hooke (8) was adapted for use in this study. M. smegmatis mc 2 155 (7) was inoculated into Middlebrook 7H9 with ADC supplement (Difco) (7H9) and grown at 37°C to ϳ10 8 colony-forming units/ml. Nitrosoguanidine (Sigma) was added to a final concentration of 0.1 mg/ml, and cultures were incubated at 37°C...