Peter J. Moate

MINMOD Millennium: A Computer Program to Calculate Glucose Effectiveness and Insulin Sensitivity from the Frequently Sampled Intravenous Glucose Tolerance Test

The Bergman Minimal Model enables estimation of two key indices of glucose/insulin dynamics: glucose effectiveness and insulin sensitivity. In this paper we describe MINMOD Millennium, the latest Windows-based version of minimal model software. Extensive beta testing of MINMOD Millennium has shown that it is user-friendly, fully automatic, fast, accurate, reproducible, repeatable, and highly concordant with past versions of MINMOD. It has a simple interface, a comprehensive help system, an input file editor, a file converter, an intelligent processing kernel, and a file exporter. It provides publication-quality charts of glucose and insulin and a table of all minimal model parameters and their error estimates. In contrast to earlier versions of MINMOD and some other minimal model programs, Millennium provides identified estimates of insulin sensitivity and glucose effectiveness for almost every subject.

WinSAAM: a windows-based compartmental modeling system

Over the last 50 years, complex, dynamic, compartmental models have been used to describe and to make predictions on a host of pharmacokinetic, metabolic, and biological systems. Sophisticated modeling software is required to fit data to such models and to make predictions using these compartmental models. WinSAAM is one such modeling program. The purpose the current report is to describe the features of WinSAAM that make this program suited for modeling all manner of biological systems. We highlight new features, especially those that are unique to WinSAAM, and illustrate with examples how WinSAAM is used to construct models of metabolic systems, to simulate the effects of experiments on systems, and to fit models to data.

An inhibitor persistently decreased enteric methane emission from dairy cows with no negative effect on milk production

Significance Methane from enteric fermentation in the ruminant digestive system is a major contributor to anthropogenic greenhouse gas emissions in the United States and worldwide. Methane is also a net loss of feed energy to the animal. This study was undertaken to investigate the effect of a methane inhibitor on enteric methane emissions from lactating dairy cows. The experiment demonstrated that, under industry-relevant conditions, the inhibitor persistently decreased by 30% enteric methane emissions, without negatively affecting animal productivity. The spared methane energy was partially used for tissue synthesis, which led to a greater body weight gain by the inhibitor-treated cows. If adopted, this mitigation practice could lead to a substantial reduction of greenhouse gas emissions from the ruminant livestock sector. A quarter of all anthropogenic methane emissions in the United States are from enteric fermentation, primarily from ruminant livestock. This study was undertaken to test the effect of a methane inhibitor, 3-nitrooxypropanol (3NOP), on enteric methane emission in lactating Holstein cows. An experiment was conducted using 48 cows in a randomized block design with a 2-wk covariate period and a 12-wk data collection period. Feed intake, milk production, and fiber digestibility were not affected by the inhibitor. Milk protein and lactose yields were increased by 3NOP. Rumen methane emission was linearly decreased by 3NOP, averaging about 30% lower than the control. Methane emission per unit of feed dry matter intake or per unit of energy-corrected milk were also about 30% less for the 3NOP-treated cows. On average, the body weight gain of 3NOP-treated cows was 80% greater than control cows during the 12-wk experiment. The experiment demonstrated that the methane inhibitor 3NOP, applied at 40 to 80 mg/kg feed dry matter, decreased methane emissions from high-producing dairy cows by 30% and increased body weight gain without negatively affecting feed intake or milk production and composition. The inhibitory effect persisted over 12 wk of treatment, thus offering an effective methane mitigation practice for the livestock industries.

High throughput whole rumen metagenome profiling using untargeted massively parallel sequencing

BackgroundVariation of microorganism communities in the rumen of cattle (Bos taurus) is of great interest because of possible links to economically or environmentally important traits, such as feed conversion efficiency or methane emission levels. The resolution of studies investigating this variation may be improved by utilizing untargeted massively parallel sequencing (MPS), that is, sequencing without targeted amplification of genes. The objective of this study was to develop a method which used MPS to generate “rumen metagenome profiles”, and to investigate if these profiles were repeatable among samples taken from the same cow. Given faecal samples are much easier to obtain than rumen fluid samples; we also investigated whether rumen metagenome profiles were predictive of faecal metagenome profiles.ResultsRather than focusing on individual organisms within the rumen, our method used MPS data to generate quantitative rumen micro-biome profiles, regardless of taxonomic classifications. The method requires a previously assembled reference metagenome. A number of such reference metagenomes were considered, including two rumen derived metagenomes, a human faecal microflora metagenome and a reference metagenome made up of publically available prokaryote sequences. Sequence reads from each test sample were aligned to these references. The “rumen metagenome profile” was generated from the number of the reads that aligned to each contig in the database. We used this method to test the hypothesis that rumen fluid microbial community profiles vary more between cows than within multiple samples from the same cow. Rumen fluid samples were taken from three cows, at three locations within the rumen. DNA from the samples was sequenced on the Illumina GAIIx. When the reads were aligned to a rumen metagenome reference, the rumen metagenome profiles were repeatable (P < 0.00001) by cow regardless of location of sampling rumen fluid. The repeatability was estimated at 9%, albeit with a high standard error, reflecting the small number of animals in the study. Finally, we compared rumen microbial profiles to faecal microbial profiles. Our hypothesis, that there would be a stronger correlation between faeces and rumen fluid from the same cow than between faeces and rumen fluid from different cows, was not supported by our data (with much greater significance of rumen versus faeces effect than animal effect in mixed linear model).ConclusionsWe have presented a simple and high throughput method of metagenome profiling to assess the similarity of whole metagenomes, and illustrated its use on two novel datasets. This method utilises widely used freeware. The method should be useful in the exploration and comparison of metagenomes.

Effects of feeding algal meal high in docosahexaenoic acid on feed intake, milk production, and methane emissions in dairy cows

This study examined effects on milk yield and composition, milk fatty acid concentrations and methane (CH4) emissions when dairy cows were offered diets containing different amounts of algal meal. The algal meal contained 20% docosahexaenoic acid (DHA) and cows were offered either 0, 125, 250, or 375 g/cow per d of algal meal corresponding to 0, 25, 50, or 75 g of DHA/cow per d. Thirty-two Holstein cows in mid lactation were allocated to 4 treatment groups, and cows in all groups were individually offered 5.9k g of dry matter (DM) per day of concentrates [683 g/kg of cracked wheat (Triticum aestivum), 250 g/kg of cold-pressed canola, 46 g/kg of granulated dried molasses, and 21 g/kg of mineral mix] and ad libitum alfalfa (Medicago sativa) hay. The algal meal supplement was added to the concentrate allowance and was fed during the morning and afternoon milking, whereas the alfalfa hay was fed individually in pens. Cows were gradually introduced to their diets over 7d and then fed their treatment diets for a further 16d. Dry matter intake and milk yield were measured daily, and milk composition was measured on a sample representative of the daily milk yield on Thursday of each week. For the last 2d of the experiment, cows were individually housed in respiration chambers to allow measurement of CH4 emissions. Dry matter intake, milk yield and milk composition were also measured while cows were in the respiration chambers. Cows ate all their offered concentrates, but measured intake of alfalfa decreased with increasing dose of DHA by 16.2, 16.4, 15.1, and 14.3 kg of DM/d, respectively. Milk yield (22.6, 23.5, 22.6, and 22.6 kg/cow per d) was not affected by DHA dose, but milk fat concentrations (49.7, 37.8, 37.0, and 38.3g/kg) and, consequently, milk fat yields (1.08, 0.90, 0.83, and 0.85 kg/d) decreased with addition of DHA. The feeding of algal meal high in DHA was associated with substantial increases in the concentrations of DHA (0.04, 0.36, 0.60, and 0.91 g/100g of milk fatty acids) and conjugated linoleic acid C18:2 cis-9,trans-11 (0.36, 1.09, 1.79, and 1.87 g/100g of milk fatty acids). Addition of DHA did not affect total emissions of CH4 (543, 563, 553, and 520 g/cow per d), nor emissions in terms of milk production (24.9, 22.1, 24.3, and 23.4 g of CH4/kg of milk), but emissions were increased with respect to total intake (22.6, 23.5, 24.5, and 24.4 g of CH4/kg of DM). These findings indicate that CH4 emissions were not reduced when dairy cows were fed a forage-based diet supplemented with DHA from algal meal.

Grape marc reduces methane emissions when fed to dairy cows.

Grape marc (the skins, seeds, stalk, and stems remaining after grapes have been pressed to make wine) is currently a by-product used as a feed supplement by the dairy and beef industries. Grape marc contains condensed tannins and has high concentrations of crude fat; both these substances can reduce enteric methane (CH4) production when fed to ruminants. This experiment examined the effects of dietary supplementation with either dried, pelleted grape marc or ensiled grape marc on yield and composition of milk, enteric CH4 emissions, and ruminal microbiota in dairy cows. Thirty-two Holstein dairy cows in late lactation were offered 1 of 3 diets: a control (CON) diet; a diet containing dried, pelleted grape marc (DGM); and a diet containing ensiled grape marc (EGM). The diet offered to cows in the CON group contained 14.0kg of alfalfa hay dry matter (DM)/d and 4.3kg of concentrate mix DM/d. Diets offered to cows in the DGM and EGM groups contained 9.0kg of alfalfa hay DM/d, 4.3kg of concentrate mix DM/d, and 5.0kg of dried or ensiled grape marc DM/d, respectively. These diets were offered individually to cows for 18d. Individual cow feed intake and milk yield were measured daily and milk composition measured on 4d/wk. Individual cow CH4 emissions were measured by the SF6 tracer technique on 2d at the end of the experiment. Ruminal bacterial, archaeal, fungal, and protozoan communities were quantified on the last day of the experiment. Cows offered the CON, DGM, and EGM diets, ate 95, 98, and 96%, respectively, of the DM offered. The mean milk yield of cows fed the EGM diet was 12.8kg/cow per day and was less than that of cows fed either the CON diet (14.6kg/cow per day) or the DGM diet (15.4kg/cow per day). Feeding DGM and EGM diets was associated with decreased milk fat yields, lower concentrations of saturated fatty acids, and enhanced concentrations of mono- and polyunsaturated fatty acids, in particular cis-9,trans-11 linoleic acid. The mean CH4 emissions were 470, 375, and 389g of CH4/cow per day for cows fed the CON, DGM, and EGM diets, respectively. Methane yields were 26.1, 20.2, and 21.5g of CH4/kg of DMI for cows fed the CON, DGM, and EGM diets, respectively. The ruminal bacterial and archaeal communities were altered by dietary supplementation with grape marc, but ruminal fungal and protozoan communities were not. Decreases of approximately 20% in CH4 emissions and CH4 yield indicate that feeding DGM and EGM could play a role in CH4 abatement.

Metagenomic predictions: from microbiome to complex health and environmental phenotypes in humans and cattle.

Mammals have a large cohort of endo- and ecto- symbiotic microorganisms (the microbiome) that potentially influence host phenotypes. There have been numerous exploratory studies of these symbiotic organisms in humans and other animals, often with the aim of relating the microbiome to a complex phenotype such as body mass index (BMI) or disease state. Here, we describe an efficient methodology for predicting complex traits from quantitative microbiome profiles. The method was demonstrated by predicting inflammatory bowel disease (IBD) status and BMI from human microbiome data, and enteric greenhouse gas production from dairy cattle rumen microbiome profiles. The method uses unassembled massively parallel sequencing (MPS) data to form metagenomic relationship matrices (analogous to genomic relationship matrices used in genomic predictions) to predict IBD, BMI and methane production phenotypes with useful accuracies (r = 0.423, 0.422 and 0.466 respectively). Our results show that microbiome profiles derived from MPS can be used to predict complex phenotypes of the host. Although the number of biological replicates used here limits the accuracy that can be achieved, preliminary results suggest this approach may surpass current prediction accuracies that are based on the host genome. This is especially likely for traits that are largely influenced by the gut microbiota, for example digestive tract disorders or metabolic functions such as enteric methane production in cattle.

High frame-rate simultaneous bilateral breast DCE-MRI

A simultaneous bilateral back‐projection method for 3D dynamic contrast‐enhanced (DCE)‐MRI of the breasts was developed and evaluated. Using a double‐side band modulation of the RF slab excitation pulse, discontinuous volumes that included both breasts were simultaneously selected. The number of slice phase‐encoding steps was undersampled by a factor of 2, and the resulting signal aliasing from one volume to the other was removed using SENSE processing. In‐plane encoding was performed with an interleaved radial acquisition reconstructed using dynamic k‐space‐weighted image contrast (KWIC) temporal filtering. Image resolution was 0.5 × 0.5 × 3.0 mm3 with an effective temporal resolution of 15 s for both breast volumes. Combined with the 2× acceleration from SENSE encoding, this is a 16× acceleration factor over a conventional MR bilateral breast scan. An initial evaluation of these methods was performed on a cohort of women who presented with palpable or mammographically visible breast abnormalities. A total of 73 abnormalities were found in 45 of the 54 bilateral examinations that were performed. In 11 of these cases there was a significant finding in the contralateral breast. DCE images of both breasts can be acquired simultaneously, resulting in high‐resolution images as well as rapid sampling of the contrast kinetics. Magn Reson Med 57:220–225, 2007.

Investigating the effect of two methane-mitigating diets on the rumen microbiome using massively parallel sequencing

Variation in the composition of microorganisms in the rumen (the rumen microbiome) of dairy cattle (Bos taurus) is of great interest because of possible links to methane emission levels. Feed additives are one method being investigated to reduce enteric methane production by dairy cattle. Here we report the effect of 2 methane-mitigating feed additives (grapemarc and a combination of lipids and tannin) on rumen microbiome profiles of Holstein dairy cattle. We used untargeted (shotgun) massively parallel sequencing of microbes present in rumen fluid to generate quantitative rumen microbiome profiles. We observed large effects of the feed additives on the rumen microbiome profiles using multiple approaches, including linear mixed modeling, hierarchical clustering, and metagenomic predictions. The effect on the fecal microbiome profiles was not detectable using hierarchical clustering, but was significant in the linear mixed model and when metagenomic predictions were used, suggesting a more subtle effect of the diets on the lower gastrointestinal microbiome. A differential representation analysis (analogous to differential expression in RNA sequencing) showed significant overlap in the contigs (which are genome fragments representing different microorganism species) that were differentially represented between experiments. These similarities suggest that, despite the different additives used, the 2 diets assessed in this investigation altered the microbiomes of the samples in similar ways. Contigs that were differentially represented in both experiments were tested for associations with methane production in an independent set of animals. These animals were not treated with a methane-mitigating diet, but did show substantial natural variation in methane emission levels. The contigs that were significantly differentially represented in response to both dietary additives showed a significant enrichment for associations with methane production. This suggests that these methane-mitigating diets have altered the rumen microbiome toward naturally low methane-emitting microbial profiles. The contig sequences are predominantly new and include Faecalibacterium spp. The contigs we have identified here are potential biomarkers for low-methane-emitting cattle.

Energy partitioning in herbage-fed dairy cows offered supplementary grain during an extended lactation

An experiment was conducted to quantify the changes in energy partitioning resulting from grain supplementation in herbage-fed dairy cows at 4 stages during a 670-d lactation. The experiment used 16 lactating Holstein-Friesian cows, with a control and a grain treatment being randomly allocated to 8 cows each. During 4 measurement periods (each of 4d in a metabolism stall and 3d in an indirect calorimeter) beginning at approximately 110, 270, 450, and 560 d in milk (DIM), the energy balance of each cow was measured. Cows in both groups were individually offered freshly cut ryegrass pasture (Lolium hybridum L.) in periods 1 and 3 and ryegrass pasture silage and alfalfa (Medicago sativa L.) hay in periods 2 and 4. In all periods, cows in the grain group were offered an additional 4.4 to 5.0 kg of dry matter of cereal grain/cow per day. Adding grain to the diet increased yields of fat and protein and tended to increase yields of milk and lactose, but did not affect milk composition. Gross energy intake (GEI) declined as lactation progressed. Adding grain to the diet decreased the percentage of GEI in feces and urine, but the extent of these reductions did not change as lactation progressed. Adding grain to the diet similarly reduced the percentage of GEI lost to heat, but again the extent of the reduction remained similar as lactation progressed. The magnitude of the increase in milk energy resulting from grain supplementation did not change with advancing lactation, but tissue energy retention was greater in the first 300 DIM compared with after 300 DIM. For herbage-based diets, CH(4) emissions ranged from 6.2 to 7.6% of GEI, which corresponds to 24.0 to 25.8 g of CH(4)/kg of dry matter intake. For diets supplemented with cereal grains, CH(4) emissions ranged from 6.3 to 7.3% of GEI, which corresponds to 21.6 to 25.2 g of CH(4)/kg of dry matter intake. It was concluded that, for cows producing <24 kg of milk/d and consuming herbage-based diets supplemented with grain, the efficiency of utilizing the additional energy in the grain, as measured by the loss of energy in heat, and its partitioning to milk, did not change as lactation progressed from 110 to 560 DIM.