role of the ruminal microbiomein the production and...

GOBIERNO DE CHILE / MINISTERIO DE AGRICULTURA/ INIA REMEHIE

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ROLE OF THE RUMINAL MICROBIOMEIN THE PRODUCTION AND COMPOSITION OF MILK

Paul J. WeimerUS Dairy Forage Research Center, Agricultural Research Service, US Department of Agriculture, Madison, WI USA. Email: [email protected]

1. AbsTrACT

Environmental problems associated with animal agriculture arise primarily from inherent inefficiencies in converting energy in feeds to useful products. Attenuating these inefficiencies provides substantial potential to improve both the economics and environmental footprint of animal agriculture, particularly in the case of ruminants. An attractive target is the improvement of feed efficiency (unit of product per unit feed input), particularly through maintaining and improving the fat content of milk, which represents the largest energy sink in dairy cattle. Some microbiological aspects of milk fat depression are presented within the context of the complexity and stability of the ruminal microbial community. Progress in modulating the composition of milk and improving feed efficiency will require further studies aimed not only at characterizing microbial community composition of the rumen, but also at linking specific microbial taxa to beneficial or deleterious production outcomes.

2. inTrodUCTion

Animal agriculture has been central to the development of human civilization, and serves a critical role in feeding the majority of the world’s 6.1 billion people, as well as a major contributor to economies worldwide. Modern livestock agriculture has a huge environmental footprint, although over time its impact on a per-unit product in some cases (for example, in dairy production in the USA) has actually decreased substantially (Capper et al. 2009). One aspect of animal agriculture that has received a great deal of recent attention is its contribution to the production of greenhouse gases. Animals, particularly ruminants, produce large amounts of methane during their digestion of feeds, and mineralization in soil of the ammonia and organic nitrogen within animal manures is a major worldwide source of nitrous oxide produced during the microbially driven nitrogen cycle.

These waste products (methane and manure) in the ruminant represent energy lost from feeds, and can be viewed as fundamental and inherent inefficiencies in biological energy utilization. The goal of mitigating GHG emissions from ruminants is largely focused on combining accurate measurements of ruminal emissions (direct and indirect) with various strategies (feed additives, probiotics, manure management) to modify the ruminal fermentation in order to reduce output of methane and ammonia (Powers et al. 2014). An alternative strategy is to focus directly on improving the efficiency of feed utilization; i.e, achieving a greater partitioning of feed energy into useful products, which should result in a parallel decrease in losses to methane and manure. This approach reflects the results of a detailed analysis of environmental sustainability and greenhouse gas emissions in the Cow of the Future project established by the Innovation Center for US Dairy (Knapp et al. 2011). This study identified six major strategies for reducing greenhouse gases in dairy production. One of the more important of these strategies is improvement in feed efficiency. As stated in the report, “Feed efficiency has been identified by the Advisory Group as an area in dairy nutrition with a large knowledge gap, with high potential value for improving dairy profitability and reducing methane emissions per unit of product”. Achievable improvements in feed efficiency were predicted to potentially reduce methane emissions per unit of milk by 6 to 8%. This paper will examine some general concepts in the efficiency of energy conversion in dairy cattle, and then will focus on milk composition –a major determinant of feed efficiency – and on how it might be impacted by the composition and activities of the ruminal microbial community.

PRIMERA CONFERENCIA DE GASES DE EFECTO INVERNADERO EN SISTEMAS AGROPECUARIOS DE LATINOAMÉRICA (GALA)

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3. Feed eFFiCienCY

With respect to livestock-based agriculture, feed efficiency is simply a quantitative expression of the conversion of feeds into useful animal products -- primarily milk and meat. It may be expressed as such (and termed gross feed efficiency), or, it may be calculated to take into account other sinks for retention of energy from digestion (for example, gestation of the fetal calf), but excluding energy lost as waste (methane and manure; Figure 1).

In beef cattle, gross feed efficiency is typically expressed as average daily gain per unit of dry matter intake (ADG/DMI). Because beef animals (most of which are steers) gain weight virtually continuously until slaughter and do not go through a reproductive cycle, there are few factors confounding the concept or measurement of feed efficiency. We can think of energy being partitioned into animal mass and waste (methane, manure and heat), and with a portion of feed used for maintenance.

Dairy cattle produce substantially more methane than do beef cattle, for a variety of reasons. Firstly, they have higher levels of feed intake, necessary to produce robust amounts of milk. Secondly, their diets typically contain higher levels of forages (at least compared to feedlot-fed beef steers), and the resulting ruminal fermentation operates at a higher pH, which is more favorable for the growth of methanogenic archaea. Thirdly, unlike beef cattle that are grown as quickly as possible for slaughter, dairy cattle are first grown to maturity then managed for multiple lactation cycles and thus longer lifespans. Ideally, high production is maintained for as many cycles as possible, but in the US most cows are culled after 2 or 3 lactations due to declining production as well as various health problems attendant to very energy-rich diets used to sustain high levels of milk production. Cows in pasture-based systems, despite lower productivity, have more longevity and consequently are also major contributors to the waste burden. In either case, feed efficiency in dairy cattle is substantially more complicated than in beef cattle. Prior to breeding, feed energy is partitioned into weight gain, maintenance and waste, but after breeding, feed energy is distributed into these components plus milk production, gestation, and other sinks, such as the immunological demands for combating mastitis. During the lactation cycle, the partitioning of feed energy into these components is constantly changing. Nevertheless, for a high-producing dairy cow, milk is the single largest energy sink, and thus represents a major potential route for improving production efficiency, along with reducing production inefficiencies due to delayed pregnancy and cow attrition.

4. eFFeCT oF THe rUminAL miCrobiome on miLk FAT ProdUCTion

The three major organic components of milk are fat, protein and lactose (Table 1). Of these components, fat has

Figure 1. Energy partitioning in the dairy cow. Successful strategies to increase efficiency of feed conversion to useful products should reduce inefficiencies (production of manure and methane).


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the highest energy content and is the most variable in concentration. In fact, most pricing structures for milk in the US pay producers primarily on fat content (Jesse and Cropp, 2010), especially in the upper Midwestern US, where most milk is used to produce cheese, most varieties of which require milk having a fairly high fat content. Milk fat depression (MFD, defined here as production of milk with an average fat content of <3% w/v), a common nutritional syndrome in dairy cows, is thus a major economic loss for dairy producers.

Table 1. Concentrations and energy values of milk components in fluid milk from Holstein cows on mixed diets.

a National Research Council (2001), converted from MCal/kg units

Combining data on total milk yield (kg) and the percentage of each milk component allows the calculation of the amount of milk produced on an energy-corrected basis (“energy corrected milk”, ECM). “Gross feed efficiency” of milk production is the calculated as ECM/DMI. Because milk fat makes a disproportionately large contribution to ECM, one strategy for examining the relationship between the ruminal microbiome and feed efficiency is to look at the relationship between the ruminal microbiome and milk fat yield or milk fat content.

Milk fat synthesis is a complex process that appears to be tightly regulated, particularly by the concentrations of certain unsaturated long-chain fatty acids (LCFAs) delivered to the mammary gland. The concentrations of these LCFAs are determined by the extent of biohydrogenation of unsaturated dietary lipids by the ruminal microflora. Identification of particular microbial species involved in these biohydrogenation reactions has proven remarkably challenging. The realization over the past two decades that the ruminal microbiome contains hundreds to thousands of individual microbial species, most of which have not yet been cultivated, has made the task of identifying microbial agents of MFD even more daunting.

Our initial efforts to characterize the ruminal microbial community and its relationship with milk fat production used ARISA (automated ribosomal intergenic spacer analysis). ARISA is based on PCR amplification of the spacer sequence between the 16S and 23S rRNA genes in the DNA of bulk environmental samples. The length of this spacer varies among bacterial species, and the PCR amplicons of different length can be separated and quantified by capillary electrophoresis. The resulting ARISA profiles can be used to compare differences in bacterial community composition (BCC) among different animals maintained on the same diet, and the effects of dietary changes on these communities within individual animals. It has been known for some time that certain ration formulations (ej., those containing a high proportion of rapidly fermented grains in combination with corn oil and the feed additive monensin) are prone to induce MFD in some cows. We observed that cows induced for MFD by one such diet displayed ARISA profiles quite different from those of cows that did not suffer MFD when fed the same diet (Weimer et al. 2010b), suggesting the presence of different ruminal bacterial communities.

ARISA is useful for showing differences in community composition as a whole, but provides no direct taxonomic or phylogenetic identification of which particular species differ in abundance. However, from DNA isolated from ruminal samples in MFD cows we were able to separate on gels the PCR amplicons containing both the intergenic space region and portions of the adjacent 16S rRNA gene, from which we obtained partial 16S rRNA gene sequences matching those of one particular ruminal bacterium, Megasphaera elsenii. Subsequent quantitative real-time PCR (qPCR) analysis with M. elsdenii-specific primers revealed that this species was almost always present as a substantial fraction of the bacterial community (0.3 to 4% of total bacterial 16S rRNA gene copy number) in the rumens of cows when they were fat-depressed, but were always much less abundant (<0.01% of gene copy number) in these cows when they were not fat-depressed, or in other cows that did not exhibit MFD. The unusual ARISA


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patterns and high abundance by qPCR assays for M. elsdenii were also observed in two other studies (eg. see Figure 2) in which MFD was observed in a few cows on less aggressive diets (higher forage content and sometimes without monensin or added corn oil). In these latter studies cows that did not display MFD did not have more than traces of M. elsdenii in their rumens.

These data suggest a strong association between MFD and M. elsdenii. Although an association of M. elsdenii with MFD was first suggested some 40 years ago from culture-based studies (Latham et al. 1972), M. elsdenii typically is regarded as a beneficial ruminal bacterium due to its ability prevent the deleterious accumulation of lactic acid resulting from overfeeding of rapidly fermented carbohydrates in high-grain diets (Henning et al. 2011) – in fact, it is marketed as a probiotic in some countries specifically for this purpose. If M. elsdenii is indeed a cause of MFD, we would expect that it would be capable of producing certain LCFAs (particularly trans-10, cis-12-conjugated linoleic acid, t10, c12-CLA ) known to inhibit mammary lipogenesis. On this matter the literature is equivocal (cf. the conflicting data of Maia et al. 2009, and Kim et al. 2002). Kim et al. suggested that M. elsdenii strains may differ in their ability to produce the t10, c12-CLA isomer, and this hypothesis merits further examination.

The ideal way of showing a direct causal relationship between any microbial species (including M. elsdenii) and MFD would be to elicit MFD in cows by direct inoculation the suspected microbial agent. Several studies (Henning et al., 2011; Zebeli et al. 2012) with M. elsdenii, focused on demonstrating their use as probiotics for beneficial alteration of fermentation product profiles, did not detect significant differences in milk production or milk composition, even upon 21 successive daily ruminal dosings (Zebeli et al. 2012). However, there was also no difference in ruminal lactate concentrations, and no measurements were made of M. elsdenii population size in the rumens before or after dosing. Thus it is not clear if the lack of effects were due to a metabolic limitation of the inoculated strains, or to their lack of persistence in the rumen. Additional dosing experiments are warranted, using larger doses of strains isolated specifically from MFD cows, along with measurements of the persistence of the strain over any period in which MFD might be observed. In addition, in vitro studies with mixed ruminal microflora amended with M. elsdenii or other suspected agents of ruminal biohydrogenation might shed light on the involvement of these species in fostering the accumulation of biohydrogenation intermediates known to regulate mammary lipogenesis.One interesting result of the ARISA profiling of the ruminal bacterial community is the presence of a PCR amplicon

Figure 2. Comparison of milk fat levels in 8 cows with the relative abundance of Megasphaera elsdenii in their ruminal contents. The cows were fed a high-fiber total mixed ration containing alfalfa silage as the primary fiber source. (Mohammed et al. 2012).


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whose relative abundance is negatively correlated with the relative population size of M. elsdenii (Palmonari et al. 2010). The corresponding bacterial taxon has not been identified, but it does present the possibility that it may be either an indicator of resistance to MFD, or an agent that suppresses either M. elsdenii or another potential agent of MFD. If the responsible bacterium was a bona fide inhibitor of an MFD agent, it might be useful as a probiotic to maintain fat test, and, by extension, improve ECM production and, ultimately, feed efficiency.

The wider availability of next-generation sequencing technologies offers the promise of more detailed examination of the relationship between the composition of the ruminal microbiome and various production metrics. A very recent example of this is provided by Jami et al. (2014), who used 454 pyrotag sequencing to demonstrate quantitative differences at the phylum level in the microbiome of Holstein cows, and a correlation between milk fat yield and the ruminal ratio of Firmicutes/Bacteroidetes, two of the most abundant phyla in the rumen. The specific taxa within these phyla that may be responsible for beneficial or detrimental effects on milk fat production were not identified, but the observed differences even at the phylum level hopefully will help to narrow down the task of making more specific identifications.

5. AnimAL indiVidUALiTY in miLk ProdUCTion PArAmeTers, Feed eFFiCienCY, And rUminAL miCrobiAL CommUniTY ComPosiTion

One of the striking outcomes of recent studies on the ruminal microbiome is that, despite the presence of a “core microbiome” shared by all members of a test group of cattle, individual animals appear to have their own signature microflora in which the proportions of community members vary within modest levels (Jami and Mizrahi, 2012). The individual microbial species may be largely common to a group of animals, but the identity of specific strains and their relative proportions appear to differ among animals. The community as a whole appears to exhibit the twin ecological properties of redundancy (overlap of function among multiple species or strains) and resiliency (resistance to long-term perturbation). In particular, resiliency has been demonstrated through experiments in which nearly the entire contents of the rumens of pairs of ruminally cannulated cows have been manually exchanged, after which the original communities reassembled in approximately their original proportions (to the extent measurable by ARISA) within 2 to 9 weeks (Weimer et al. 2010a).

Given that individual cows vary both in their efficiency of feed conversion and in their microbiome composition, it is not unreasonable to expect that some ruminal communities are inherently more efficient than others in producing fermentation end products (VFA and microbial cell protein) useful to the host. Indeed, differential nutrient capture from foods by gut microbiomes have been proposed as an underlying source of obesity in mice (Turnbaugh et al. 2006) and, more equivocally, in humans (Ley et al. 2010).

So can differences in feed efficiency be correlated with specific members of the ruminal microbiome? Attempts have been made to answer this question in beef cattle. In these studies, it has been noted that gross feed efficiency (ADG/DMI) can be a misleading metric due to the confounding effect of body weight. To compensate for this variation, efficiency is usually expressed as residual feed intake (RFI), the difference between DMI of the animal and the expected DMI at the observed level of production, determined from regression analysis of a population of animals having different levels of production on the same diet. By this metric, animals can be classified as “high-RFI” (consuming more feed than predicted for that level of production), or “low-RFI” (consuming less feed than predicted for that level of production); these groups thus correspond to lower and higher efficiency animals, respectively.

Several studies have shown that low-RFI and high-RFI steers differ in bacterial community composition when analyzed by community fingerprinting techniques such as terminal restriction fragment length polymorphism (t-RFLP) or denaturing gradient gel electrophoresis (DGGE). Such analyses, coupled with more conventional clone library construction based on 16S rRNA genes, have identified bacteria (at various taxonomic levels) whose


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population size differs in low-RFI versus high-RFI animals (Hernandez-Sanabria et al. 2010; Carberry et al. 2012). Of potentially more direct relevance to inefficiencies associated with ruminal greenhouse gas emissions, parallel studies have been conducted on the methanogenic archaeal communities. These studies have identified specific strains of methanogens whose population sizes differ substantially between low-RFI and high-RFI steers (Zhou et al. 2009).

Efforts are underway to extend these types of analyses to dairy cattle, for which some relationships between the microbiome and gross feed efficiency have been reported (Jewell 2014). The use of RFI as a means of classifying cows with respect to their feed efficiency is gaining traction (Conner et al. 2012), but is fraught with difficulties due to the above-mentioned complexity of feed energy partitioning in dairy cows. Gross feed efficiency is known to vary during the lactation cycle, and it is clear that comparisons among animals need to be conducted at similar parities and similar stages of lactation. However, a major unanswered question at this point is the fidelity of feed efficiency status of cows over their productive lifespan. Do cows identified as low-RFI maintain their low-RFI status, relative to their herd mates, throughout the lactation cycle, or across multiple lactations? And if feed efficiency status does change with time, does it correlate with changes in the composition of the microbiome as well?

6. ConCLUdinG remArks

In ruminant animals the inherent inefficiencies in feed conversion to useful agricultural products are reflected in production of manure and greenhouse gases, particularly methane. It is likely that improving feed efficiency and the retention of feed energy in milk, particularly as fat, will result in parallel decreases in manure and methane emissions. Efficiency gains are likely achievable with respect to both host physiology (e.g., more effective capture of microbial fermentation products) as well as the microbial fermentation itself. Culture-independent analyses of microbial communities have already revealed differences in community composition between MFD- and non-MFD cows, and between low-RFI (higher efficiency) and high-RFI (lower efficiency cows). The salient challenge for microbiologists and animal scientists alike is to move from this sort of “census information” to unambiguous identification of specific community members that contribute most to observed differences in host production, and to develop strategies to productively manipulate these communities to maximize the potential of each community to improve the efficiency of the ruminal fermentation. In addition, a concerted effort is required to determine the extent to which the animal affects its microbiome (e.g., through feeding behavior, rate of passage, and immunological “cross-talk”), in order to identify animals most amenable to manipulation of their microflora.

7. reFerenCes

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HENNING, P.H., ERASMUS, L., MEISSNER, H.H., HORN, C.H. 2011. The effect of dosing Megaspheara elsdenii NCIMB 41125 (Me) on lactation performance of multiparous Holstein cows. S. Afr. J. Anim. Sci. 41:156-160.

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ACknoWLedGmenTs

This research was funded by the Agricultural Research Service, USDA, through CRIS project 3655-31000-024-D.

role of the ruminal microbiomein the production and...

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