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Invited Review: Advances in rumen efficiency*

      ABSTRACT

      Purpose

      The purpose of this review was to explain how advances in our knowledge of rumen microbial ecology provide opportunities to improve ruminal fiber degradation, decrease enteric methane production, and limit wastage of dietary protein without disrupting ruminal efficiency.

      Sources

      Peer-reviewed literature was the primary course of information reviewed.

      Synthesis

      As numbers of microbial taxa in the rumen have expanded in the past 10 yr, we have gained appreciation for why rumen efficiency is so variable among dietary situations and even among dairy cattle fed the same diets. In typical dairy rations with mixed forage and grain, the primary fibrolytics support a balanced community. However, that community can be disrupted and thus limit fiber digestibility or DMI unless forage quality and particle size along with RDP are maintained. Efforts to decrease enteric methane or improve the efficiency of dietary protein usage should appreciate the complexity of the microbial community to improve consistency of responses.

      Conclusions and Applications

      Many feeding practices indirectly influence the rumen microbial structure and function, and future opportunities for feed additives will likely be adjusted for likelihood of benefit using microbial sequence data.

      Key words

      INTRODUCTION

      Measures of ruminal efficiency are typically reported in dairy nutrition research, but they unfortunately are rarely the main objective. For example, ruminal NDF degradability (NDFD) is often measured, but it is rarely expressed relative to the potential NDFD (i.e., an efficiency). For example, by-product NDF can be substituted for forage NDF without sacrificing NDFD, yet the potential NDFD for by-products is usually much greater than that for forage. Consequently, the efficiency of capturing the potential NDFD for the animal often decreases (
      • Firkins J.L.
      Effects of feeding nonforage fiber sources on site of fiber digestion..
      ). Negative associative effects of starch on NDFD have been lessened in the past 20 yr, but there is still opportunity to improve NDFD compared with its potential. Cellulolytic bacteria are specialists that express complicated enzymatic systems and thus must rely on amylolytic community partners to provide growth factors such as end products from RDP without so much starch degradation to stimulate amylolytics to outcompete cellulolytics (
      • Firkins J.L.
      Reconsidering rumen microbial consortia to enhance feed efficiency and reduce environmental impact of ruminant livestock production systems..
      ;
      • Roman-Garcia Y.
      • Mitchell K.E.
      • Lee C.
      • Socha M.T.
      • Park T.
      • Wenner B.A.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. III: Relation with solid passage rate and pH on prokaryotic fatty acid profile and community in continuous culture..
      ). Many efforts have targeted ruminal protozoa to suppress methanogenesis or intraruminal recycling of bacterial protein, but knowledge of their ecology is needed to prevent disruptions of ruminal efficiency that result in decreased NDFD or DMI. As technology has advanced in the past 10 yr, we have gained considerable understanding of the complexity of the rumen. Yet, each new answer leads to new questions. My objectives were to summarize and contextualize important aspects needed to continue improving ruminal efficiency to help readers ask better questions in field situations, even if I cannot provide all the desired answers. Figure 1 provides a schematic outline of topics addressed in this paper.
      Figure 1
      Figure 1Outline of interconnecting variables that are projected to improve efficiency of rumen processes. BCVFA = branched-chain VFA, NDFD = NDF degradability, EMPS = efficiency of microbial protein synthesis (microbial N produced per unit of carbohydrate degraded), and paNDF = physically adjusted NDF.

      WHAT CONSTITUTES RUMEN EFFICIENCY?

      Fundamentals of Rumen Efficiency

      As an overview, the rumen needs to process forage and by-product fiber to maintain enough rumen fill (i.e., a firm rumen mat) to prevent subacute rumen acidosis, produce VFA for gluconeogenesis (primarily propionate), fuel the gut (primarily butyrate and some valerate), and provide energy to tissues or carbon for de novo fatty acid synthesis in mammary or adipose tissues. However, too much rumen fill limits DMI. To improve any sort of efficiency for NDFD, our goal is to optimize these processes in some reasonably predictable way that can be manipulated consistently by dietary or other managerial changes. In this review, I will discuss anabolic and catabolic processes of ruminal microbes. Anabolism assimilates compounds from degraded feed into microbial cells that continue degradation of newly ingested feed while replacing the microbial matter that flows out of the rumen to support the cow’s MP needs. Catabolic processes are largely from fermentation of sugars and AA to VFA (or organic acid intermediates, especially lactate and succinate) to produce ATP while disposing of reducing equivalents.

      Relating Microbial Protein to Degraded Carbohydrate

      Efficiency of microbial protein synthesis (EMPS) is typically expressed as microbial protein flowing from the rumen (anabolism) per unit of either OM or carbohydrate degraded (providing precursors for both anabolism and catabolism). Unfortunately, blurring anabolism and catabolism sometimes leads to lost opportunity to gain improvements in EMPS. For example, increasing starch in the diet typically increases microbial protein flow to the duodenum while also increasing ruminal OM or carbohydrate degradability. However, while microbial protein increases, the EMPS decreases because the gain in EMPS was less than it could have been. This principle has been known for decades. The term “yield” (abbreviated as Y) originated from the YATP concept in which the bacterial growth rate (i.e., anabolism into cellular biomass) was evaluated with respect to the theoretical amounts of ATP generated by catabolic VFA production (
      • Hespell R.B.
      Efficiency of growth by ruminal bacteria..
      ;
      • Russell J.B.
      The energy spilling reactions of bacteria and other organisms..
      ). In the first Cornell Net Carbohydrate and Protein System (
      • Russell J.B.
      • O’Connor J.D.
      • Fox D.G.
      • Van Soest P.J.
      • Sniffen C.J.
      A net carbohydrate and protein system for evaluating cattle diets: I. Ruminal fermentation..
      ), the microbial yield term was predicted and multiplied by predicted carbohydrate degradability to predict microbial protein flow to the duodenum. Yet, the model also appropriately predicted that increasing starch would increase the proportion of ATP being used for maintenance and so decreased EMPS. Increasing growth efficiency routes a greater proportion of anabolic carbon from degraded feed into cells rather than VFA (
      • Russell J.B.
      • Cook G.M.
      Energetics of bacterial growth: Balance of anabolic and catabolic reactions..
      ). In reverse, the ATP produced during fermentation can be less efficiently converted into cellular matter and is therefore more likely to be wasted. Even though the YATP concept has long been out of vogue (except in some countries’ dairy models), it still supports our goal to optimize EMPS. Much more is now known about intentional ATP wastage (
      • Hackmann T.J.
      • Firkins J.L.
      Maximizing efficiency of rumen microbial protein production..
      ;

      Ungerfeld, E. M., and T. J. Hackmann. 2020. Factors influencing the efficiency of rumen energy metabolism. Pages 421–466 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ). There have been many published reports of an increased EMPS resulting from a decreased ruminal OM degradability without a decrease in microbial protein flow from the rumen. Such an increased EMPS would not be feasible for dairy cattle because lower NDFD would decrease digestible energy compared with model predictions but also could decrease DMI through bulk fill. Increasing starch percentage has an asymptotic effect on intake of rumen-degraded carbohydrate because it limits voluntary DMI first through physical NDF filling (decreasing NDFD) and then later through chemical satiety (
      • Allen M.S.
      • Piantoni P.
      Carbohydrate nutrition: Managing energy intake and partitioning through lactation..
      ). Feeding practices need to distinguish effects of increasing EMPS separate from when it was associated with depressed DMI or other factors that limit overall ruminal efficiency.
      Increasing DMI by high-producing cows provides more substrate to support more microbial protein but also increases the ruminal passage rate, which should improve EMPS by increasing the proportion of total energy (and expressed genes) that is used for microbial growth and decreasing that used for maintenance (
      • Firkins J.L.
      • Yu Z.
      • Morrison M.
      Ruminal nitrogen metabolism: Perspectives for integration of microbiology and nutrition for dairy..
      ). Of course, faster passage rate can decrease degradability in the rumen, but undegraded NDF passing to the duodenum might be an important vehicle to export microbial N flow because about 75% of the bacteria adhere to particles (
      • Sauvant D.
      • Nozière P.
      Quantification of the main digestive processes in ruminants: The equations involved in the renewed energy and protein feed evaluation systems..
      ). In contrast, negative associative effects (i.e., increasing dietary starch inclusion decreases NDFD at high DMI) depend on dietary variables and also differ among animals at least in part because of their unique microbial community structures.

      INCREASING RUMINAL FIBER DEGRADABILITY

      Progress in Improving and Predicting NDFD

      Historically, dairy cattle were assumed to have a depression in TDN (most of which was discounted NDFD) by 4 percentage units per each multiple of maintenance (

      NASEM (National Academies of Sciences, Engineering, and Medicine). 2001. Nutrient Requirements of Dairy Cattle. 7th rev. ed. ed. Natl. Acad. Sci.

      ). Yet, this effect has been lessened considerably since then (
      • de Souza R.A.
      • Tempelman R.J.
      • Allen M.S.
      • Weiss W.P.
      • Bernard J.K.
      • VandeHaar M.J.
      Predicting nutrient digestibility in high-producing dairy cows..
      ) in large part by diluting starch with by-product fiber (
      • Bradford B.J.
      • Mullins C.R.
      Invited review: Strategies for promoting productivity and health of dairy cattle by feeding nonforage fiber sources..
      ). For my purposes, TDN should not be used to derive EMPS anymore. Improved computational and statistical approaches better account for ruminal factors (
      • White R.R.
      • Roman-Garcia Y.
      • Firkins J.L.
      • Kononoff P.J.
      • VandeHaar M.J.
      • Tran H.
      • McGill T.
      • Garnett R.
      • Hanigan M.D.
      Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 2. Rumen degradable and undegradable protein..
      ;
      • Moraes L.E.
      • White R.R.
      • Firkins J.L.
      A new model to predict microbial protein synthesis in the rumen..
      ). Even so, the paradox of an “intake/digestibility feedback loop” (
      • White R.R.
      • Roman-Garcia Y.
      • Firkins J.L.
      Meta-analysis of postruminal microbial nitrogen flows in dairy cattle. II. Approaches to and implications of more mechanistic prediction..
      ) needs more attention. That is, increasing DMI decreases NDF and starch degradabilities through increased passage rate (i.e., greater passage of potentially degradable NDF and starch); in contrast, increasing ruminal degradability of NDF by feeding higher quality forage or by-products allows greater DMI on an equal NDF basis. This paradox is hard to sort out with meta-analyses using treatment means.
      • de Souza R.A.
      • Tempelman R.J.
      • Allen M.S.
      • Weiss W.P.
      • Bernard J.K.
      • VandeHaar M.J.
      Predicting nutrient digestibility in high-producing dairy cows..
      used sophisticated statistics with individual animal data to document that the negative associative effect in which each 1% increase in dietary starch decreased total-tract NDFD by 0.59 percentage unit; because of compensatory NDFD in the hindgut, this 0.59 coefficient would likely be greater in the rumen.
      Some advancements and limitations are important to identify but are outside the scope of this review. Plant breeding, harvesting, and processing approaches have improved (
      • Ferraretto L.F.
      • Shaver R.D.
      • Luck B.D.
      Silage review: Recent advances and future technologies for whole-plant and fractionated corn silage harvesting..
      ;
      • Muck R.E.
      • Nadeau E.M.G.
      • McAllister T.A.
      • Contreras-Govea F.E.
      • Santos M.C.
      • Kung Jr., L.
      Silage review: Recent advances and future uses of silage additives..
      ;
      • Adesogan A.T.
      • Arriola K.G.
      • Jiang Y.
      • Oyebade A.
      • Paula E.M.
      • Pech-Cervantes A.A.
      • Romero J.J.
      • Ferraretto L.F.
      • Vyas D.
      Symposium review: Technologies for improving fiber utilization..
      ). In contrast, sorting and feeding behavior of silages is still poorly understood (
      • Grant R.J.
      • Ferraretto L.F.
      Silage review: Silage feeding management: Silage characteristics and dairy cow feeding behavior..
      ), so nutrition advisors must still evaluate these behaviors herd by herd with empirical evaluations. Despite the advances in laboratory evaluation of forages by feed-testing laboratories, in vitro procedures have limitations with respect to testing the interaction of feeds because they are ground and pH is buffered, so ruminal conditions cannot really be replicated. Finally, responses can depend on initial conditions of the donor animals. Therefore, meta-analyses are still useful to ascertain mechanism of microbiological factors to alert nutrition advisors regarding potential negative associative effects.
      Journal-wide efforts have improved transparency and quality of meta-analyses. Advantages include the use of in vivo data (and lack conditional aspects from grinding or from effects of donor cow). However, meta-analyses also potentially suffer from imbalanced source data. For example, classes of grains or processing methods often are not allocated evenly across forage sources. Deriving ruminal starch digestibilities of grain classes,
      • Firkins J.L.
      • Eastridge M.L.
      • St-Pierre N.R.
      • Noftsger S.M.
      Effects of grain variability and processing on starch utilization by lactating dairy cattle..
      relied on studies that had no corn silage (i.e., a separate source of starch). Few researchers characterize their grain processing with particle size measurements to theoretically improve prediction compared with grouping into classes. Most individual studies typically changed one dietary factor at a time and intentionally overfed other nutrients without consideration to some future meta-analysis’s objectives. However, these varying conditions provide important interactions or continuous relationships that are embedded in the random effect of study. More research needs to deconvolute the random effect of study into actual factors that can be applied on dairy farms. Only some authors have addressed multicollinearity among variables. Data and error structure are now being rigorously checked according to new journal reporting standards, but some results still need to be conditioned according to assumptions made and approaches used.
      Several studies have evaluated feeds as class variables.
      • White R.R.
      • Roman-Garcia Y.
      • Firkins J.L.
      • VandeHaar M.J.
      • Armentano L.E.
      • Weiss W.P.
      • McGill T.
      • Garnett R.
      • Hanigan M.D.
      Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 1. Digestibility of fiber, fat, protein, and nonfiber carbohydrate..
      recorded differences among grain source to estimate apparent total-tract starch digestibility while investigating continuous variables in the meta data. Clearly, there are relatively large differences within a grain source (e.g., “ground corn” can be very different among studies). Results generally followed expectations from earlier meta-analyses with more limited data (
      • Firkins J.L.
      • Eastridge M.L.
      • St-Pierre N.R.
      • Noftsger S.M.
      Effects of grain variability and processing on starch utilization by lactating dairy cattle..
      ;
      • Ferraretto L.F.
      • Crump P.M.
      • Shaver R.D.
      Effect of cereal grain type and corn grain harvesting and processing methods on intake, digestion, and milk production by dairy cows through a meta-analysis..
      ). When evaluating approaches to estimate total-tract NDFD from treatment means in the literature, equations were derived for forage source categories and summed for the overall prediction (
      • White R.R.
      • Roman-Garcia Y.
      • Firkins J.L.
      • VandeHaar M.J.
      • Armentano L.E.
      • Weiss W.P.
      • McGill T.
      • Garnett R.
      • Hanigan M.D.
      Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 1. Digestibility of fiber, fat, protein, and nonfiber carbohydrate..
      ). As discussed previously, the responses for NDFD were more moderate when using individual cow data (
      • de Souza R.A.
      • Tempelman R.J.
      • Allen M.S.
      • Weiss W.P.
      • Bernard J.K.
      • VandeHaar M.J.
      Predicting nutrient digestibility in high-producing dairy cows..
      ). Individual animal data are not readily reported in the literature, though, and including physiological and microbiological variables should be included in models to reduce the randomness of among-animal differences either for potential grouping or inoculation strategies.
      There is a critical challenge associated with addressing the variation of quality of the same forage class among studies (
      • White R.R.
      • Roman-Garcia Y.
      • Firkins J.L.
      • VandeHaar M.J.
      • Armentano L.E.
      • Weiss W.P.
      • McGill T.
      • Garnett R.
      • Hanigan M.D.
      Evaluation of the National Research Council (2001) dairy model and derivation of new prediction equations. 1. Digestibility of fiber, fat, protein, and nonfiber carbohydrate..
      ;
      • de Souza R.A.
      • Tempelman R.J.
      • Allen M.S.
      • Weiss W.P.
      • Bernard J.K.
      • VandeHaar M.J.
      Predicting nutrient digestibility in high-producing dairy cows..
      ). Grasses are potentially more degradable than legumes, but grasses likely have a slower degradation rate (even if greater extent of degradation), are less fragile (more resistant to particle size reduction), and become more filling, thus limiting milk production for higher-producing cows (
      • Allen M.S.
      • Sousa D.O.
      • VandeHaar M.J.
      Equation to predict feed intake response by lactating cows to factors related to the filling effect of rations..
      ). Although better characterization of individual forages for another parameter such as undegradable NDF derived in situ or in vitro could help improve our ability to predict NDFD (
      • de Souza R.A.
      • Tempelman R.J.
      • Allen M.S.
      • Weiss W.P.
      • Bernard J.K.
      • VandeHaar M.J.
      Predicting nutrient digestibility in high-producing dairy cows..
      ), these effects are still affected by physically effective fiber and other mechanistic limitations on NDFD to be discussed later.

      Soluble Fiber and Residual OM

      Another issue with meta-analyses to ascertain digestibility of different nutrients or feeds has to do with residual components that are embedded in the model but not described separately (and thus not able to be modeled or manipulated). Although the residual OM is an “error pool” often derived by difference, much of the residual OM is soluble fiber that is not measured directly in most studies. Not doing sequential ADF on the NDF residue further complicates the error. Pectin has often been thought of as being almost completely degraded by microbes, but those expectations are typically based on pectin that was extracted before being evaluated. In contrast, some soluble fiber is more closely related to hemicellulose, particularly if it is more associated with stems than leaves (
      • Hatfield R.D.
      • Weimer P.J.
      Degradation characteristics of isolated and in situ cell wall lucerne pectic polysaccharides by mixed ruminal microbes..
      ). Thus, soluble fiber from alfalfa should not be considered equivalent to that from soybean hulls. Citrus pulp was assumed to have less negative associative effects on cellulose and hemicellulose degradation compared with starch (
      • Bampidis V.A.
      • Robinson P.H.
      Citrus by-products as ruminant feeds: A review..
      ). Beet pulp is a source of soluble fiber that is highly degradable (
      • Voelker J.A.
      • Allen M.S.
      Pelleted beet pulp substituted for high-moisture corn: 3. Effects on ruminal fermentation, pH, and microbial protein efficiency in lactating dairy cows..
      ), but it still could be used to induce acidosis in sheep (
      • Lettat A.
      • Nozière P.
      • Silberberg M.
      • Morgavi D.P.
      • Berger C.
      • Martin C.
      Experimental feed induction of ruminal lactic, propionic, or butyric acidosis in sheep..
      ). Thus, residual OM can be derived more appropriately in future studies as we try to optimize its potentially high degradability (
      • Tebbe A.W.
      • Faulkner M.J.
      • Weiss W.P.
      Effect of partitioning the nonfiber carbohydrate fraction and neutral detergent fiber method on digestibility of carbohydrates by dairy cows..
      ).

      Effective Fiber

      The concept of effective fiber has been addressed multiple times, with a key advancement made in a symposium at the 1995 American Dairy Science Association meeting, particularly the adaptation of physically effective NDF (peNDF) systems (
      • Mertens D.R.
      Creating a system for meeting the fiber requirements of dairy cows..
      ). This approach emphasized the role of particle size to stimulate chewing during eating and ruminating but minimized its other role to dilute starch. Since then, many approaches have been developed (
      • Maulfair D.D.
      • Heinrichs A.J.
      Review: Methods to measure forage and diet particle size in the dairy cow..
      ). However, peNDF forces NDF in the entire diet to be multiplied times the proportion of particles retained on a single sieve such as the 1.18-mm laboratory sieve in the original approach or the 9-mm sieve from the Penn State Particle Separator in the modified approach (
      • Zebeli Q.
      • Aschenbach J.R.
      • Tafaj M.
      • Boguhn J.
      • Ametaj B.N.
      • Drochner W.
      Invited review: Role of physically effective fiber and estimation of dietary fiber adequacy in high-producing dairy cattle..
      ). In contrast, NDF and sieve fraction can and should be unbundled using multiple regression and mathematical algorithms (
      • White R.R.
      • Hall M.B.
      • Firkins J.L.
      • Kononoff P.J.
      Physically adjusted neutral detergent fiber system for lactating dairy cow rations. I: Deriving equations that identify factors that influence effectiveness of fiber..
      ).
      • Mertens D.R.
      Creating a system for meeting the fiber requirements of dairy cows..
      articulated the limitations with using dietary NDF for peNDF (i.e., NDF concentration is not equal on all sieves) and suggested that more research was needed to fill this gap, especially addressing the clear bias when the main source of long fiber is from wet forages (i.e., wet forage stems and leaves are on larger sieves than are the drier particles on smaller sieves). If using peNDF, a user would get best results by actually measuring the NDF on that cutoff sieve fraction rather than factoring dietary NDF, but at the least, sieve fractions should be evaluated on a common DM basis (even if 55°C) when there are wet feeds.
      For studies assessing chewing and sieve fractions on a DM basis, a system termed “physically adjusted NDF” was derived (
      • White R.R.
      • Hall M.B.
      • Firkins J.L.
      • Kononoff P.J.
      Physically adjusted neutral detergent fiber system for lactating dairy cow rations. II: Development of feeding recommendations..
      ). It built on the narrow window for optimizing long fiber to stimulate chewing (peNDF) and maintain rumen function while decreasing risk for forage NDF to fill-restrict DMI (
      • Zebeli Q.
      • Aschenbach J.R.
      • Tafaj M.
      • Boguhn J.
      • Ametaj B.N.
      • Drochner W.
      Invited review: Role of physically effective fiber and estimation of dietary fiber adequacy in high-producing dairy cattle..
      ). Based on that peNDF system, collection of regurgitated boli allowed
      • Jiang F.G.
      • Lin X.Y.
      • Yan Z.G.
      • Hu Z.Y.
      • Liu G.M.
      • Sun Y.D.
      • Liu X.W.
      • Wang Z.H.
      Effect of dietary roughage level on chewing activity, ruminal pH, and saliva secretion in lactating Holstein cows..
      to note a linear increase in saliva secreted during eating that was offset by a linear decrease in salivation during resting. For physically adjusted NDF, an app can be downloaded to help users understand how to increase particle length when forage NDF is low but how forage can be processed more finely when forage NDF is high (https://dairy.unl.edu/munch-effective-fiber-app). Users (a) should avoid using this tool to predict pH and (b) should note that pH values are likely different when derived by rumen cannula (the source for the app) versus continuous monitoring devices. Further information is available in an excellent review by
      • Beauchemin K.A.
      Invited review: Current perspectives on eating and rumination activity in dairy cows..
      .

      Advances in Microbiology Techniques to Help Explain Varying NDFD

      In the past 10 yr, technology has advanced our understanding of bacteria, methanogenic archaea, and protozoa (
      • Kim M.
      • Park T.
      • Yu Z.
      Invited review—Metagenomic investigation of gastrointestinal microbiome in cattle..
      ); similar gains were lagging but are now being made with fungi (
      • Edwards J.E.
      • Forster R.J.
      • Callaghan T.M.
      • Dollhofer V.
      • Dagar S.S.
      • Cheng Y.
      • Chang J.
      • Kittelmann S.
      • Fliegerova K.
      • Puniya A.K.
      • Henske J.K.
      • Gilmore S.P.
      • O’Malley M.A.
      • Griffith G.W.
      • Smidt H.
      PCR and omics based techniques to study the diversity, ecology and biology of anaerobic fungi: Insights, challenges and opportunities..
      ). Characterization of taxa at the species rank might have arbitrary similarity cutoffs (
      • Li F.
      • Neves A.L.A.
      • Ghoshal B.
      • Guan L.L.
      Symposium review: Mining metagenomic and metatranscriptomic data for clues about microbial metabolic functions in ruminants..
      ), and computational clustering approaches are still evolving to improve their relevance (
      • Caruso V.
      • Song X.
      • Asquith M.
      • Karstens L.
      Performance of microbiome sequence inference methods in environments with varying biomass..
      ). Advancement to more functional levels is being held back because many of our laboratory isolates do not represent the main rumen bacterial phylogenetic groups (
      • Zehavi T.
      • Probst M.
      • Mizrahi I.
      Insights into culturomics of the rumen microbiome..
      ). There are some new culturing efforts underway, but computational assessment of sequenced genomes have also allowed functional characterization of 2 prominent Bacteroidetes genera (
      • Ormerod K.L.
      • Wood D.L.A.
      • Lachner N.
      • Gellatly S.L.
      • Daly J.N.
      • Parsons J.D.
      • Dal’Molin C.G.O.
      • Palfreyman R.W.
      • Nielsen L.K.
      • Cooper M.A.
      • Morrison M.
      • Hansbro P.M.
      • Hugenholtz P.
      Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals..
      ;
      • Solden L.M.
      • Hoyt D.W.
      • Collins W.B.
      • Plank J.E.
      • Daly R.A.
      • Hildebrand E.
      • Beavers T.J.
      • Wolfe R.
      • Nicora C.D.
      • Purvine S.O.
      • Carstensen M.
      • Lipton M.S.
      • Spalinger D.E.
      • Firkins J.L.
      • Wolfe B.A.
      • Wrighton K.C.
      New roles in hemicellulosic sugar fermentation for the uncultivated Bacteroidetes family BS11..
      ) that were in high abundance but of previously unknown function. More research like this is needed.
      Persistent questions remain regarding how samples should be taken, processed, and replicated. Stomach tubes can yield more realistic results if the tube insertion length and collection of particles are standardized (
      • Paz H.A.
      • Anderson C.L.
      • Muller M.J.
      • Kononoff P.J.
      • Fernando S.C.
      Rumen bacterial community composition in Holstein and jersey cows is different under same dietary condition and is not affected by sampling method..
      ); even regurgitated ruminal boli might be useful to characterize fibrolytics (
      • Tapio I.
      • Shingfield K.J.
      • McKain N.
      • Bonin A.
      • Fischer D.
      • Bayat A.R.
      • Vilkki J.
      • Taberlet P.
      • Snelling T.J.
      • Wallace R.J.
      Oral samples as non-invasive proxies for assessing the composition of the rumen microbial community..
      ). These sampling approaches might be more relevant to application such as studying methanogenesis, which could be influenced from gas leakage through a rumen cannula (
      • Wang R.
      • Wang M.
      • Zhang X.M.
      • Wen J.N.
      • Ma Z.Y.
      • Long D.L.
      • Deng J.P.
      • Tan Z.L.
      Effects of rumen cannulation on dissolved gases and methanogen community in dairy cows..
      ). Although dissolved H2 was similar, VFA profile and the bacterial community were not deemed to reflect samples collected via cannulas, particularly over the diurnal cycle (
      • de Assis Lage C.F.
      • Räisänen S.E.
      • Melgar A.
      • Nedelkov K.
      • Chen X.
      • Oh J.
      • Fetter M.E.
      • Indugu N.
      • Bender J.S.
      • Vecchiarelli B.
      • Hennessy M.L.
      • Pitta D.
      • Hristov A.N.
      Comparison of two sampling techniques for evaluating ruminal fermentation and microbiota in the planktonic phase of rumen digesta in dairy cows..
      ). Hence, sampling through rumen cannulas to collect fibrous samples is recommended for studying the fibrolytic community.
      Future research needs to be more targeted at a biological mechanism. Enzymes are often thought of as being rigidly expressed by microbes that have those genes, whereas growing evidence suggests transcriptional regulation of those genes within taxa as they adapt to differing dietary conditions. Expression of carbohydrate-degrading enzymes allow hundreds (or perhaps thousands) of individual bacterial taxa for a variety of ruminants across continents while maintaining a main core of only about 15 different bacterial families (
      • Terry S.A.
      • Badhan A.
      • Wang Y.
      • Chaves A.V.
      • McAllister T.A.
      Fibre digestion by rumen microbiota—A review of recent metagenomic and metatranscriptomic studies..
      ). Those authors noted that, although RNA is less stable than DNA, some taxa might be more or less represented by their small subunit rRNA gene (or other marker gene) relative to their transcript abundance of functional genes such as glycosyl hydrolases (to degrade starch and fiber), which would improve mechanistic inference in future studies like that of
      • Yeoman C.J.
      • Fields C.J.
      • Lepercq P.
      • Ruiz P.
      • Forano E.
      • White B.A.
      • Mosoni P.
      In vivo competitions between Fibrobacter succinogenes, Ruminococcus flavefaciens, and Ruminococcus albus in a gnotobiotic sheep model revealed by multi-omic analyses..
      .
      Metagenomics has advanced our understanding of ruminal efficiency (
      • Denman S.E.
      • Morgavi D.P.
      • McSweeney C.S.
      Review: The application of omics to rumen microbiota function..
      ;
      • Li F.
      • Neves A.L.A.
      • Ghoshal B.
      • Guan L.L.
      Symposium review: Mining metagenomic and metatranscriptomic data for clues about microbial metabolic functions in ruminants..
      ). Metaproteomics confirmed a pivotal role of transporters linking catabolic depolymerization with microbial anabolic metabolism (
      • Deusch S.
      • Camarinha-Silva A.
      • Conrad J.
      • Beifuss U.
      • Rodehutscord M.
      • Seifert J.
      A structural and functional elucidation of the rumen microbiome influenced by various diets and microenvironments..
      ). Carbohydrate availability should be coordinated with transporter expression and growth rates so long as other nutrients such as ammonia and AA are available (
      • Hackmann T.J.
      • Firkins J.L.
      Maximizing efficiency of rumen microbial protein production..
      ). When carbohydrate availability is in excess of other nutrients, these microbes can produce extracellular polysaccharides (
      • Nouaille R.
      • Matulova M.
      • Delort A.-M.
      • Forano E.
      Oligosaccharide synthesis in Fibrobacter succinogenes S85 and its modulation by the substrate..
      ;
      • Kelly W.J.
      • Leahy S.C.
      • Altermann E.
      • Yeoman C.J.
      • Dunne J.C.
      • Kong Z.
      • Pacheco D.M.
      • Li D.
      • Noel S.J.
      • Moon C.D.
      • Cookson A.L.
      • Attwood G.T.
      The glycobiome of the rumen bacterium Butyrivibrio proteoclasticus B316T highlights adaptation to a polysaccharide-rich environment..
      ) that promote cross-feeding. Even protozoa, which decrease EMPS by predating bacteria, also help limit depressed EMPS resulting from excessive dietary starch (
      • Gruninger R.J.
      • Ribeiro G.O.
      • Cameron A.
      • McAllister T.A.
      Invited review: Application of meta-omics to understand the dynamic nature of the rumen microbiome and how it responds to diet in ruminants..
      ). However, when stored glycogen is cycled (glucose added and removed in a cycle), it wastes ATP (

      Ungerfeld, E. M., and T. J. Hackmann. 2020. Factors influencing the efficiency of rumen energy metabolism. Pages 421–466 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ) and decreases EMPS. Therefore, integrating polysaccharide fluxes rather than just the net degradation should help us optimize anabolic and catabolic processes affecting EMPS.

      From Independent Consorts to the Rumen Microbial Consortium

      Most of our concepts of cross-feeding involve 2 or 3 pure cultures compared alone and mixed in a coculture (
      • Dehority B.A.
      Effects of microbial synergism on fibre digestion in the rumen..
      ;
      • Koike S.
      • Kobayashi Y.
      Fibrolytic rumen bacteria: Their ecology and functions..
      ). Some examples include motile Treponema species (lacking cellulase) aiding nonmotile Fibrobacter succinogenes (or other cellulolytics) to penetrate the plant cell wall and depolymerize cellulose while sharing the resultant oligosaccharides (
      • Moraïs S.
      • Mizrahi I.
      Islands in the stream: From individual to communal fiber degradation in the rumen ecosystem..
      ). Similarly, fungal zoospores (highly motile) appear to seek recalcitrant parts of the cell wall to attach, penetrate, and weaken the particle to aid access by bacteria (
      • Akin D.E.
      • Borneman W.S.
      Role of rumen fungi in fiber degradation..
      ). The fibrolytic enzymes enhance the developing consortium, including methanogens that interact physically with the H2- and formate-producing fungi (
      • Edwards J.E.
      • Forster R.J.
      • Callaghan T.M.
      • Dollhofer V.
      • Dagar S.S.
      • Cheng Y.
      • Chang J.
      • Kittelmann S.
      • Fliegerova K.
      • Puniya A.K.
      • Henske J.K.
      • Gilmore S.P.
      • O’Malley M.A.
      • Griffith G.W.
      • Smidt H.
      PCR and omics based techniques to study the diversity, ecology and biology of anaerobic fungi: Insights, challenges and opportunities..
      ). Butyrivibrio proteoclasticus, the main characterized stearate-producing bacterium involved in biohydrogenation of UFA, also similarly interacts physically with methanogens (
      • Leahy S.C.
      • Kelly W.J.
      • Altermann E.
      • Ronimus R.S.
      • Yeoman C.J.
      • Pacheco D.M.
      • Li D.
      • Kong Z.
      • McTavish S.
      • Sang C.
      • Lambie S.C.
      • Janssen P.H.
      • Dey D.
      • Attwood G.T.
      The genome sequence of the rumen methanogen Methanobrevibacter ruminantium reveals new possibilities for controlling ruminant methane emissions..
      ).
      Many cellulolytics and methanogens lack key growth factors that are provided by more generalist bacteria (

      Stewart, C. S., H. J. Flint, and M. P. Bryant. 1997. The rumen bacteria. Pages 10–72 in The Rumen Microbial Ecosystem. P. N. Hobson and C. S. Stewart, ed. Hall.

      ). Because carbohydrates differ in their rates of degradation, microbial consortia are dynamic with respect to time after feeding (i.e., meals overlap the degradation period). However, we must refocus our analyses from large samples to better representing the actual microenvironment.
      • Gruninger R.J.
      • Ribeiro G.O.
      • Cameron A.
      • McAllister T.A.
      Invited review: Application of meta-omics to understand the dynamic nature of the rumen microbiome and how it responds to diet in ruminants..
      illustrated the importance of a consortium of colonizing microbes after new feed is ingested. Primary specialist cellulolytics cleave the various side chains and cross links in hemicellulose and soluble fiber as they intermingle with the generalists that develop secondarily from using those cleaved products as substrate. They noted greater diversity on high forage diets, which might be expected given various cell wall components (
      • Weimer P.J.
      Redundancy, resilience, and host specificity of the ruminal microbiota: Implications for engineering improved ruminal fermentations..
      ).
      • Moraïs S.
      • Mizrahi I.
      Islands in the stream: From individual to communal fiber degradation in the rumen ecosystem..
      further expanded into a “rock-paper-scissors” scenario in which certain bacteria compete with each other for substrates or growth factors yet none consistently dominates over another because multiple environmental or spatial factors allow coexistence in networks within the rumen. The ruminal consortia probably shift in relative abundance of different members as remaining fiber becomes increasingly crystalline. This property helps ruminants subsisting on poor quality forage, whereas lactating dairy cows have the opposite problem in that particles pass from the rumen well before full degradation of fiber. Thus, our goal for dairy is not to maximize, but to optimize, the colonization process before passage.
      Because there is redundancy in fibrolytic and amylolytic populations in the rumen of dairy cattle fed typical diets, an unbalanced consortium can create (or be created by) inefficient ruminal conditions (e.g., low pH or low concentration of nitrogenous compounds) to potentially disadvantage the highly fibrolytic bacteria (
      • Firkins J.L.
      Reconsidering rumen microbial consortia to enhance feed efficiency and reduce environmental impact of ruminant livestock production systems..
      ). This would be analogous to a “rock and scissors” without the “paper” in which the rock always wins. We need to prevent these sorts of imbalances by promoting more consistent feeding behavior because the particle that has been more extensively degraded inoculates newly ingested particles in a “what goes around comes around” scenario; that is, a cycle of challenging conditions for fibrolytics would leave a less robust population to compete for colonization of the next meal. Diurnal changes in populations affect differences among animals and diets (
      • Shaani Y.
      • Zehavi T.
      • Eyal S.
      • Miron J.
      • Mizrahi I.
      Microbiome niche modification drives diurnal rumen community assembly, overpowering individual variability and diet effects..
      ). However, those diurnal effects need better characterization over the feeding cycle (
      • Denman S.E.
      • Morgavi D.P.
      • McSweeney C.S.
      Review: The application of omics to rumen microbiota function..
      ) or perhaps over multiple days to better understand rumen microbial plasticity (
      • Belanche A.
      • Kingston-Smith A.H.
      • Griffith G.W.
      • Newbold C.J.
      A multi-kingdom study reveals the plasticity of the rumen microbiota in response to a shift from non-grazing to grazing diets in sheep..
      ) when assessing populations of bacteria that influence ruminal efficiency under varying dietary conditions such as temporary low pH, shortfalls in growth factors, or greater concentrations of PUFA.

      Microbial Consortia and Ruminal Efficiency

      The concept of core bacteria (i.e., taxa consistently recovered across virtually all animals sampled) has been assumed as evidence for critical functions (
      • Xue M.
      • Sun H.
      • Wu X.
      • Guan L.L.
      • Liu J.
      Assessment of rumen microbiota from a large dairy cattle cohort reveals the pan and core bacteriomes contributing to varied phenotypes..
      ;
      • Belanche A.
      • Kingston-Smith A.H.
      • Griffith G.W.
      • Newbold C.J.
      A multi-kingdom study reveals the plasticity of the rumen microbiota in response to a shift from non-grazing to grazing diets in sheep..
      ;
      • Wallace R.J.
      • Sasson G.
      • Garnsworthy P.C.
      • Tapio I.
      • Gregson E.
      • Bani P.
      • Huhtanen P.
      • Bayat A.R.
      • Strozzi F.
      • Biscarini F.
      • Snelling T.J.
      • Saunders N.
      • Potterton S.L.
      • Craigon J.
      • Minuti A.
      • Trevisi E.
      • Callegari M.L.
      • Cappelli F.P.
      • Cabezas-Garcia E.H.
      • Vilkki J.
      • Pinares-Patino C.
      • Fliegerová K.O.
      • Mrázek J.
      • Sechovcová H.
      • Kopečný J.
      • Bonin A.
      • Boyer F.
      • Taberlet P.
      • Kokou F.
      • Halperin E.
      • Williams J.L.
      • Shingfield K.J.
      • Mizrahi I.
      A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions..
      ). For example, phylum Fibrobacteres can be attributed to a critical role in fiber degradation, but Verrucomicrobia also was a core phylum (
      • Wallace R.J.
      • Sasson G.
      • Garnsworthy P.C.
      • Tapio I.
      • Gregson E.
      • Bani P.
      • Huhtanen P.
      • Bayat A.R.
      • Strozzi F.
      • Biscarini F.
      • Snelling T.J.
      • Saunders N.
      • Potterton S.L.
      • Craigon J.
      • Minuti A.
      • Trevisi E.
      • Callegari M.L.
      • Cappelli F.P.
      • Cabezas-Garcia E.H.
      • Vilkki J.
      • Pinares-Patino C.
      • Fliegerová K.O.
      • Mrázek J.
      • Sechovcová H.
      • Kopečný J.
      • Bonin A.
      • Boyer F.
      • Taberlet P.
      • Kokou F.
      • Halperin E.
      • Williams J.L.
      • Shingfield K.J.
      • Mizrahi I.
      A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions..
      ). Much is known about the former, but little is known of the latter, although it appears to have a potentially important functional role based on meta-proteomics (
      • Deusch S.
      • Camarinha-Silva A.
      • Conrad J.
      • Beifuss U.
      • Rodehutscord M.
      • Seifert J.
      A structural and functional elucidation of the rumen microbiome influenced by various diets and microenvironments..
      ). The core concept provides generalized value but offers little insight directly in how critical members interact positively and negatively with other members. More attention must be paid to associating changes in community structure (including the non-core members) with animal performance. Certain taxa appear to be heritable (
      • Wallace R.J.
      • Sasson G.
      • Garnsworthy P.C.
      • Tapio I.
      • Gregson E.
      • Bani P.
      • Huhtanen P.
      • Bayat A.R.
      • Strozzi F.
      • Biscarini F.
      • Snelling T.J.
      • Saunders N.
      • Potterton S.L.
      • Craigon J.
      • Minuti A.
      • Trevisi E.
      • Callegari M.L.
      • Cappelli F.P.
      • Cabezas-Garcia E.H.
      • Vilkki J.
      • Pinares-Patino C.
      • Fliegerová K.O.
      • Mrázek J.
      • Sechovcová H.
      • Kopečný J.
      • Bonin A.
      • Boyer F.
      • Taberlet P.
      • Kokou F.
      • Halperin E.
      • Williams J.L.
      • Shingfield K.J.
      • Mizrahi I.
      A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions..
      ), although the question is not well answered whether these heritability estimates are a result of host-specific genetics (
      • Li F.
      • Li C.
      • Chen Y.
      • Liu J.
      • Zhang C.
      • Irving B.
      • Fitzsimmons C.
      • Plastow G.
      • Guan L.L.
      Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle..
      ), potentially resulting from microbes associating with the rumen epithelium (
      • Bickhart D.M.
      • Weimer P.J.
      Symposium review: Host–rumen microbe interactions may be leveraged to improve the productivity of dairy cows..
      ), or simply a result of an animal’s initial inoculation by its dam.
      Differences in rumen microbial structure have been associated with feed efficiency of beef (
      • Paz H.A.
      • Hales K.E.
      • Wells J.E.
      • Kuehn L.A.
      • Freetly H.C.
      • Berry E.D.
      • Flythe M.D.
      • Spangler M.L.
      • Fernando S.C.
      Rumen bacterial community structure impacts feed efficiency in beef cattle..
      ) and dairy (
      • Delgado B.
      • Bach A.
      • Guasch I.
      • González C.
      • Elcoso G.
      • Pryce J.E.
      • Gonzalez-Recio O.
      Whole rumen metagenome sequencing allows classifying and predicting feed efficiency and intake levels in cattle..
      ) cattle. In contrast with prior expectations,
      • Huws S.A.
      • Creevey C.J.
      • Oyama L.B.
      • Mizrahi I.
      • Denman S.E.
      • Popova M.
      • Muñoz-Tamayo R.
      • Forano E.
      • Waters S.M.
      • Hess M.
      • Tapio I.
      • Smidt H.
      • Krizsan S.J.
      • Yáñez-Ruiz D.R.
      • Belanche A.
      • Guan L.
      • Gruninger R.J.
      • McAllister T.A.
      • Newbold C.J.
      • Roehe R.
      • Dewhurst R.J.
      • Snelling T.J.
      • Watson M.
      • Suen G.
      • Hart E.H.
      • Kingston-Smith A.H.
      • Scollan N.D.
      • do Prado R.M.
      • Pilau E.J.
      • Mantovani H.C.
      • Attwood G.T.
      • Edwards J.E.
      • McEwan N.R.
      • Morrisson S.
      • Mayorga O.L.
      • Elliott C.
      • Morgavi D.P.
      Addressing global ruminant agricultural challenges through understanding the rumen microbiome: Past, present, and future..
      noted that more efficient animals actually had less bacterial diversity. This conclusion probably should not be generalized to pasture-based animals because of the diverse array of substrates (

      Waters, S. M., D. A. Kenny, and P. E. Smith. 2020. Role of the rumen microbiome in pasture-fed ruminant production systems. Pages 591–650 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ). In a negative way, lower bacterial diversity can be associated with rumen acidosis, whereas microbial additives can help increase resilience against subacute rumen acidosis (
      • Ishaq S.L.
      • AlZahal O.
      • Walker N.
      • McBride B.
      An investigation into rumen fungal and protozoal diversity in three rumen fractions, during high-fiber or grain-induced sub-acute ruminal acidosis conditions, with or without active dry yeast supplementation..
      ;
      • McCann J.C.
      • Elolimy A.A.
      • Loor J.J.
      Rumen microbiome, probiotics, and fermentation additives..
      ). Further research should evaluate how additives such as yeast culture seem to modify feeding behavior (
      • Dias A.L.G.
      • Freitas J.A.
      • Micai B.
      • Azevedo R.A.
      • Greco L.F.
      • Santos J.E.P.
      Effects of supplementing yeast culture to diets differing in starch content on performance and feeding behavior of dairy cows..
      ) based on their specific role on microbial community structure and EMPS.
      There remains an important question as yet unanswered about how much we can manipulate the microbiome to improve measures of ruminal efficiency. Relationships of certain taxa to feed efficiency and other phenotypic measures are not consistent across studies (
      • Denman S.E.
      • Morgavi D.P.
      • McSweeney C.S.
      Review: The application of omics to rumen microbiota function..
      ). As those authors explained, some of the variation could be a result of variation within the same phylogenetic categorization (e.g., the predominant bacterial genus Prevotella or the predominant archaeal genus Methanobrevibacter). Even if differences in sequencing platforms and computational approaches were standardized (
      • Li F.
      • Neves A.L.A.
      • Ghoshal B.
      • Guan L.L.
      Symposium review: Mining metagenomic and metatranscriptomic data for clues about microbial metabolic functions in ruminants..
      ), simple linear correlation (which is typically done) ignores complex interactions and therefore the statistical collinearity among various taxa. Recent researchers have used cluster analyses (
      • Martínez-Álvaro M.
      • Auffret M.D.
      • Stewart R.D.
      • Dewhurst R.J.
      • Duthie C.-A.
      • Rooke J.A.
      • Wallace R.J.
      • Shih B.
      • Freeman T.C.
      • Watson M.
      • Roehe R.
      Identification of complex rumen microbiome interaction within diverse functional niches as mechanisms affecting the variation of methane emissions in bovine..
      ;
      • Park T.
      • Ma L.
      • Ma Y.
      • Zhou X.
      • Bu D.
      • Yu Z.
      Dietary energy sources and levels shift the multi-kingdom microbiota and functions in the rumen of lactating dairy cows..
      ;
      • Ramayo-Caldas Y.
      • Zingaretti L.
      • Popova M.
      • Estellé J.
      • Bernard A.
      • Pons N.
      • Bellot P.
      • Mach N.
      • Rau A.
      • Roume H.
      • Perez-Enciso M.
      • Faverdin P.
      • Edouard N.
      • Ehrlich D.
      • Morgavi D.P.
      • Renand G.
      Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows..
      ), which appear more relevant to the consortium concept.

      Rumen Inoculation

      In the past decade, researchers have addressed the progression of the ruminal microbial community to assess whether we could “seed” a more efficient population (
      • Yáñez-Ruiz D.R.
      • Abecia L.
      • Newbold C.J.
      Manipulating rumen microbiome and fermentation through interventions during early life: A review..
      ). In lambs (
      • Belanche A.
      • Yáñez-Ruiz D.R.
      • Detheridge A.P.
      • Griffith G.W.
      • Kingston-Smith A.H.
      • Newbold C.J.
      Maternal versus artificial rearing shapes the rumen microbiome having minor long-term physiological implications..
      ) and beef calves (
      • Lourenco J.M.
      • Callaway T.R.
      • Kieran T.J.
      • Glenn T.C.
      • McCann J.C.
      • Stewart Jr., R.L.
      Analysis of the rumen microbiota of beef calves supplemented during the suckling phase..
      ), a normal progression was influenced by shifting diet, but persistence of communities was weak. Some protozoal and fungal taxa did persist, and some taxa appear correlated with growth traits such as ADG. Inoculation of protozoa and bacterial communities in dairy calves had lasting effects to adulthood (
      • Cersosimo L.M.
      • Radloff W.
      • Zanton G.I.
      Microbial inoculum composition and pre-weaned dairy calf age alter the developing rumen microbial environment..
      ), but postweaning effects had the greatest effect on adult community structure (
      • Dill-McFarland K.A.
      • Weimer P.J.
      • Breaker J.D.
      • Suen G.
      Diet influences early microbiota development in dairy calves without long-term impacts on milk production..
      ). Based on those prior studies, selective inoculation might have somewhat more promise at weaning than at or shortly after birth. However, repeated (5 times up to d 50 of age) inoculation of calves with rumen contents also improved lasting effects on community analysis (
      • Bu D.
      • Zhang X.
      • Ma L.
      • Park T.
      • Wang L.
      • Wang M.
      • Xu J.
      • Yu Z.
      Repeated inoculation of young calves with rumen microbiota does not significantly modulate the rumen prokaryotic microbiota consistently but decreases diarrhea..
      ). Switching from alfalfa hay to cereal straw increased Fibrobacter and Treponema, which were the only 2 taxa to persist in greater relative abundance when sheep were switched back to a straw diet (
      • Xie X.
      • Yang C.
      • Guan L.L.
      • Wang J.
      • Xue M.
      • Liu J.X.
      Persistence of cellulolytic bacteria Fibrobacter and Treponema after short-term corn stover-based dietary intervention reveals the potential to improve rumen fibrolytic function..
      ). Lactating dairy cattle switch from high to low and back to high quality forage at dry-off through postpartum, but I am not aware of any studies that have studied or tried to manipulate the microbial community through inoculation of fibrolytic bacteria during this time. Community structure rebounded quickly after switching rumen contents of lactating cows (
      • Weimer P.J.
      • Cox M.S.
      • Vieira de Paula T.
      • Lin M.
      • Hall M.B.
      • Suen G.
      Transient changes in milk production efficiency and bacterial community composition resulting from near-total exchange of ruminal contents between high- and low-efficiency Holstein cows..
      ), but those changes were not integrated with a major change in forage type. Probiotics are beyond the current scope, but there are some studies that indicate potential benefit during the peripartum period.
      Protozoa must be inoculated from another animal, yet they have a critical role in shaping the prokaryotic community. Although their biomass is likely overestimated by most techniques (
      • Firkins J.L.
      • Yu Z.
      • Park T.
      • Plank J.E.
      Extending Burk Dehority’s perspectives on the role of ciliate protozoa in the rumen..
      ), they still contribute extensively to intraruminal recycling of microbial protein (

      Firkins, J. L., and R. I. Mackie. 2020. Ruminal protein breakdown and ammonia assimilation. Pages 383–420 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ). As genomic sequences expand our databases, protozoal importance in fiber degradation is given increasing credence despite the among-animal differences (
      • Mizrahi I.
      • Jami E.
      Review: The compositional variation of the rumen microbiome and its effect on host performance and methane emission..
      ). For those populations that contribute less to NDFD and are more predatory to bacteria (increasing wastage of dietary protein), selective suppression of certain populations has not been very successful so far (
      • Huws S.A.
      • Creevey C.J.
      • Oyama L.B.
      • Mizrahi I.
      • Denman S.E.
      • Popova M.
      • Muñoz-Tamayo R.
      • Forano E.
      • Waters S.M.
      • Hess M.
      • Tapio I.
      • Smidt H.
      • Krizsan S.J.
      • Yáñez-Ruiz D.R.
      • Belanche A.
      • Guan L.
      • Gruninger R.J.
      • McAllister T.A.
      • Newbold C.J.
      • Roehe R.
      • Dewhurst R.J.
      • Snelling T.J.
      • Watson M.
      • Suen G.
      • Hart E.H.
      • Kingston-Smith A.H.
      • Scollan N.D.
      • do Prado R.M.
      • Pilau E.J.
      • Mantovani H.C.
      • Attwood G.T.
      • Edwards J.E.
      • McEwan N.R.
      • Morrisson S.
      • Mayorga O.L.
      • Elliott C.
      • Morgavi D.P.
      Addressing global ruminant agricultural challenges through understanding the rumen microbiome: Past, present, and future..
      ). Critical considerations regarding a more complex reappraisal of their role in the rumen, particularly with respect to enteric methanogenesis, were discussed by
      • Firkins J.L.
      • Yu Z.
      • Park T.
      • Plank J.E.
      Extending Burk Dehority’s perspectives on the role of ciliate protozoa in the rumen..
      .

      DECREASING RUMINAL METHANE PRODUCTION

      Considerable effort and resources have explored mechanisms to suppress enteric methane as a greenhouse gas (
      • Knapp J.R.
      • Laur G.L.
      • Vadas P.A.
      • Weiss W.P.
      • Tricarico J.M.
      Invited review: Enteric methane in dairy cattle production: Quantifying the opportunities and impact of reducing emissions..
      ), and mitigation options cannot be simplistically applied to dairy nutrition (
      • Hristov A.N.
      • Oh J.
      • Firkins J.L.
      • Dijkstra J.
      • Kebreab E.
      • Waghorn G.
      • Makkar H.P.S.
      • Adesogan A.T.
      • Yang W.
      • Lee C.
      • Gerber P.J.
      • Henderson B.
      • Tricarico J.M.
      Special topics—mitigation of methane and nitrous oxide emissions from animal operations: I. A review of enteric methane mitigation options..
      ). For more context, readers are referred to the comprehensive review of
      • Beauchemin K.A.
      • Ungerfeld E.M.
      • Eckard R.J.
      • Wang M.
      Review: Fifty years of research on rumen methanogenesis: Lessons learned and future challenges for mitigation..
      . Models are useful for predicting methane inventories (
      • Hristov A.N.
      • Kebreab E.
      • Niu M.
      • Oh J.
      • Bannink A.
      • Bayat A.R.
      • Boland T.M.
      • Brito A.F.
      • Casper D.P.
      • Crompton L.A.
      • Dijkstra J.
      • Eugène M.
      • Garnsworthy P.C.
      • Haque N.
      • Hellwing A.L.F.
      • Huhtanen P.
      • Kreuzer M.
      • Kuhla B.
      • Lund P.
      • Madsen J.
      • Martin C.
      • Moate P.J.
      • Muetzel S.
      • Muñoz C.
      • Peiren N.
      • Powell J.M.
      • Reynolds C.K.
      • Schwarm A.
      • Shingfield K.J.
      • Storlien T.M.
      • Weisbjerg M.R.
      • Yáñez-Ruiz D.R.
      • Yu Z.
      Symposium review: Uncertainties in enteric methane inventories, measurement techniques, and prediction models..
      ), but predictive ability for dairy probably requires more complex models (
      • Moraes L.E.
      • Strathe A.B.
      • Fadel J.G.
      • Casper D.P.
      • Kebreab E.
      Prediction of enteric methane emissions from cattle..
      ). Many models rely on knowing an actual DMI as a main explanatory variable (
      • Niu M.
      • Kebreab E.
      • Hristov A.N.
      • Oh J.
      • Arndt C.
      • Bannink A.
      • Bayat A.R.
      • Brito A.F.
      • Boland T.
      • Casper D.
      • Crompton L.A.
      • Dijkstra J.
      • Eugène M.A.
      • Garnsworthy P.C.
      • Haque M.N.
      • Hellwing A.L.F.
      • Huhtanen P.
      • Kreuzer M.
      • Kuhla B.
      • Lund P.
      • Madsen J.
      • Martin C.
      • McClelland S.C.
      • McGee M.
      • Moate P.J.
      • Muetzel S.
      • Muñoz C.
      • O’Kiely P.
      • Peiren N.
      • Reynolds C.K.
      • Schwarm A.
      • Shingfield K.J.
      • Storlien T.M.
      • Weisbjerg M.R.
      • Yáñez-Ruiz D.R.
      • Yu Z.
      Prediction of enteric methane production, yield, and intensity in dairy cattle using an intercontinental database..
      ). However, relying on actual DMI complicates our ability to apply these models because some methane mitigation approaches have decreased DMI (
      • Hristov A.N.
      • Oh J.
      • Firkins J.L.
      • Dijkstra J.
      • Kebreab E.
      • Waghorn G.
      • Makkar H.P.S.
      • Adesogan A.T.
      • Yang W.
      • Lee C.
      • Gerber P.J.
      • Henderson B.
      • Tricarico J.M.
      Special topics—mitigation of methane and nitrous oxide emissions from animal operations: I. A review of enteric methane mitigation options..
      ) and increasing DMI per se should improve methane output per unit of DMI (
      • Knapp J.R.
      • Laur G.L.
      • Vadas P.A.
      • Weiss W.P.
      • Tricarico J.M.
      Invited review: Enteric methane in dairy cattle production: Quantifying the opportunities and impact of reducing emissions..
      ). In addition to the benefit in animal energetics associated with increasing DMI (i.e., dilution of maintenance energy costs), the uncertainty around DMI effects needs to be considered with residual feed intake studies integrating methanogenesis suppression.
      Methane is a loss in ME, but results for residual feed intake are equivocally related to differing VFA (

      Waters, S. M., D. A. Kenny, and P. E. Smith. 2020. Role of the rumen microbiome in pasture-fed ruminant production systems. Pages 591–650 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ) even though propionate production would be expected with decreased methane production. More efficient dairy cattle had less methane and more propionate (
      • Shabat S.K.B.
      • Sasson G.
      • Doron-Faigenboim A.
      • Durman T.
      • Yaacoby S.
      • Berg Miller M.E.
      • White B.A.
      • Shterzer N.
      • Mizrahi I.
      Specific microbiome-dependent mechanisms underlie the energy harvest efficiency of ruminants..
      ). In contrast, in another study, more efficient animals also had greater methanogenesis, apparently because of increased NDFD (
      • Olijhoek D.W.
      • Løvendahl P.
      • Lassen J.
      • Hellwing A.L.F.
      • Höglund J.K.
      • Weisbjerg M.R.
      • Noel S.J.
      • McLean F.
      • Højberg O.
      • Lund P.
      Methane production, rumen fermentation, and diet digestibility of Holstein and Jersey dairy cows being divergent in residual feed intake and fed at 2 forage-to-concentrate ratios..
      ). More complicated relationships among microbial hubs need further distinction. For example, succinate appears more likely to be produced as an intermediate when methanogenesis is suppressed (
      • Denman S.E.
      • Morgavi D.P.
      • McSweeney C.S.
      Review: The application of omics to rumen microbiota function..
      ). Succinate is often considered as an intermediate in propionate synthesis, but many succinate producers also produce acetate. New computational techniques are associating microbial networks with increasing NDFD and succinate (
      • Xue M.
      • Sun H.
      • Wu X.
      • Guan L.L.
      • Liu J.
      Assessment of rumen microbiota from a large dairy cattle cohort reveals the pan and core bacteriomes contributing to varied phenotypes..
      ;
      • Martínez-Álvaro M.
      • Auffret M.D.
      • Stewart R.D.
      • Dewhurst R.J.
      • Duthie C.-A.
      • Rooke J.A.
      • Wallace R.J.
      • Shih B.
      • Freeman T.C.
      • Watson M.
      • Roehe R.
      Identification of complex rumen microbiome interaction within diverse functional niches as mechanisms affecting the variation of methane emissions in bovine..
      ). Future research should consider transcriptional changes in key enzymes or biomarkers (
      • Huws S.A.
      • Creevey C.J.
      • Oyama L.B.
      • Mizrahi I.
      • Denman S.E.
      • Popova M.
      • Muñoz-Tamayo R.
      • Forano E.
      • Waters S.M.
      • Hess M.
      • Tapio I.
      • Smidt H.
      • Krizsan S.J.
      • Yáñez-Ruiz D.R.
      • Belanche A.
      • Guan L.
      • Gruninger R.J.
      • McAllister T.A.
      • Newbold C.J.
      • Roehe R.
      • Dewhurst R.J.
      • Snelling T.J.
      • Watson M.
      • Suen G.
      • Hart E.H.
      • Kingston-Smith A.H.
      • Scollan N.D.
      • do Prado R.M.
      • Pilau E.J.
      • Mantovani H.C.
      • Attwood G.T.
      • Edwards J.E.
      • McEwan N.R.
      • Morrisson S.
      • Mayorga O.L.
      • Elliott C.
      • Morgavi D.P.
      Addressing global ruminant agricultural challenges through understanding the rumen microbiome: Past, present, and future..
      ), but I am not aware of practical markers.
      • Janssen P.H.
      Influence of hydrogen on rumen methane formation and fermentation balances through microbial growth kinetics and fermentation thermodynamics..
      reasoned that increasing passage rate would indirectly, not directly, associate with methanogen growth rate. He argued that slowing ruminal passage rate allows methanogens to grow slower, which would decrease aqueous H2 concentration and therefore thermodynamically favor more H2 production; such a response would presumably increase the abundance of H2-consuming methanogens. Although Methanobrevibacter can compete for H2 at very low aqueous concentrations (
      • Leahy S.C.
      • Kelly W.J.
      • Ronimus R.S.
      • Wedlock N.
      • Altermann E.
      • Attwood G.T.
      Genome sequencing of rumen bacteria and archaea and its application to methane mitigation strategies..
      ), that competition was associated with its efficiency of yielding ATP per unit of H2 used as substrate (
      • Lynch T.A.
      • Wang Y.
      • van Brunt B.
      • Pacheco D.
      • Janssen P.H.
      Modelling thermodynamic feedback on the metabolism of hydrogenotrophic methanogens..
      ). Maximum growth rates of 0.12 and 0.07/h (minimum division time of 8 to 14 h) were modeled for Methanobrevibacter smithii and Methanobrevibacterruminantium (
      • Muñoz-Tamayo R.
      • Popova M.
      • Tillier M.
      • Morgavi D.P.
      • Morel J.P.
      • Fonty G.
      • Morel-Desrosiers N.
      Hydrogenotrophic methanogens of the mammalian gut: Functionally similar, thermodynamically different-a modelling approach..
      ) even though potential growth rates are much faster (
      • Thauer R.K.
      • Kaster A.-K.
      • Seedorf H.
      • Buckel W.
      • Hedderich R.
      Methanogenic archaea: Ecologically relevant differences in energy conservation..
      ). Even so, passage rates of potentially degradable NDF using the rumen pool and flux approach document a much slower passage of particles (about 0.02 to 0.03/h) for dairy cattle (
      • Krizsan S.J.
      • Ahvenjärvi S.
      • Huhtanen P.
      A meta-analysis of passage rate estimated by rumen evacuation with cattle and evaluation of passage rate prediction models..
      ) when compared with overestimated (primarily from marker migration) passage rates of 0.06 to 0.07/h for dairy cattle (

      NASEM (National Academies of Sciences, Engineering, and Medicine). 2001. Nutrient Requirements of Dairy Cattle. 7th rev. ed. ed. Natl. Acad. Sci.

      ). Thus, rather than assuming methanogens need to adhere to avoid washout, perhaps we should be envisioning adhesion to particles as competition strategies among a diverse methanogen population to better interact with adherent H2 producers. In fact,
      • Dittmann M.T.
      • Hammond K.J.
      • Kirton P.
      • Humphries D.J.
      • Crompton L.A.
      • Ortmann S.
      • Misselbrook T.H.
      • Südekum K.-H.
      • Schwarm A.
      • Kreuzer M.
      • Reynolds C.K.
      • Clauss M.
      Influence of ruminal methane on digesta retention and digestive physiology in non-lactating dairy cattle..
      questioned whether methanogenesis is affected by ruminal passage rate (i.e., if fast passage washes out methanogens) or the other way around (i.e., rates of methanogenesis control passage rate). Because ruminal pool size and passage rate offer potential explanations to among-animal differences (
      • Løvendahl P.
      • Difford G.F.
      • Li B.
      • Chagunda M.G.G.
      • Huhtanen P.
      • Lidauer M.H.
      • Lassen J.
      • Lund P.
      Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle..
      ), we should combine passage measurements with archaeal community profiling.
      Methanogen diversity needs greater consideration with respect to other factors influencing methanogenesis per unit of VFA produced. Although the hydrogenotrophic genus Methanobrevibacter dominates in the rumen, certain dietary situations show an increasing substrate alternative to aqueous H2 or formate (
      • Kelly W.J.
      • Leahy S.C.
      • Kamke J.
      • Soni P.
      • Koike S.
      • Mackie R.
      • Seshadri R.
      • Cook G.M.
      • Morales S.E.
      • Greening C.
      • Attwood G.T.
      Occurrence and expression of genes encoding methyl-compound production in rumen bacteria..
      ), which would be expected based on various constituents of plant fibers (
      • Weimer P.J.
      Redundancy, resilience, and host specificity of the ruminal microbiota: Implications for engineering improved ruminal fermentations..
      ;
      • Terry S.A.
      • Badhan A.
      • Wang Y.
      • Chaves A.V.
      • McAllister T.A.
      Fibre digestion by rumen microbiota—A review of recent metagenomic and metatranscriptomic studies..
      ). Thus, methane-suppression strategies should also consider the methyl-producing bacteria (
      • Kelly W.J.
      • Leahy S.C.
      • Kamke J.
      • Soni P.
      • Koike S.
      • Mackie R.
      • Seshadri R.
      • Cook G.M.
      • Morales S.E.
      • Greening C.
      • Attwood G.T.
      Occurrence and expression of genes encoding methyl-compound production in rumen bacteria..
      ). Moreover, within genus Methanobrevibacter, 2 profoundly different clades have been associated with ruminants emitting low versus high amounts of methane (

      Jami, E., and I. Mizrahi. 2020. Host-Rumen Microbiome Interactions and Influences on Feed Conversion Efficiency (FCE), Methane Production and Other Productivity Traits in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ). In addition to the variation among genera of Archaea, assessing functional genes within genus Methanobrevibacter requires further research (
      • Martínez-Álvaro M.
      • Auffret M.D.
      • Stewart R.D.
      • Dewhurst R.J.
      • Duthie C.-A.
      • Rooke J.A.
      • Wallace R.J.
      • Shih B.
      • Freeman T.C.
      • Watson M.
      • Roehe R.
      Identification of complex rumen microbiome interaction within diverse functional niches as mechanisms affecting the variation of methane emissions in bovine..
      ). For example, strains M1 and AbM4 of this genus had similar hydrogenotrophic enzymes (
      • Leahy S.C.
      • Kelly W.J.
      • Ronimus R.S.
      • Wedlock N.
      • Altermann E.
      • Attwood G.T.
      Genome sequencing of rumen bacteria and archaea and its application to methane mitigation strategies..
      ). However, strain M1 invested considerably more of its genome toward adhesion to surfaces at the expense of production of cofactors needed for methanogenesis, suggesting a closer interaction with other fermentative community members that supply those cofactors.
      • Firkins J.L.
      • Yu Z.
      How to use data on the rumen microbiome to improve our understanding of ruminant nutrition..
      described the potential for methanogens to intentionally spill energy. However, such uncoupling of ATP yield per mole of methane produced has not been supported specifically for rumen methanogens (
      • Wallace R.J.
      • Snelling T.J.
      • McCartney C.A.
      • Tapio I.
      • Strozzi F.
      Application of meta-omics techniques to understand greenhouse gas emissions originating from ruminal metabolism..
      ). Although many methanogens have a very high affinity for aqueous H2, a specific inhibitor for a key methanogenesis enzyme decreased methane by 26% (
      • Melgar A.
      • Harper M.T.
      • Oh J.
      • Giallongo F.
      • Young M.E.
      • Ott T.L.
      • Duval S.
      • Hristov A.N.
      Effects of 3-nitrooxypropanol on rumen fermentation, lactational performance, and resumption of ovarian cyclicity in dairy cows..
      ). With that inhibitor, H2 emission increased by 48-fold, but its emission still was about 70-fold less than methane on a molar basis. Most studies have lower H2 emissions, but such a large increase begs the question why did no other H2-using microbes fill this niche? Are alternative H2 consumers not in close proximity to H2 producers (
      • Leahy S.C.
      • Kelly W.J.
      • Altermann E.
      • Ronimus R.S.
      • Yeoman C.J.
      • Pacheco D.M.
      • Li D.
      • Kong Z.
      • McTavish S.
      • Sang C.
      • Lambie S.C.
      • Janssen P.H.
      • Dey D.
      • Attwood G.T.
      The genome sequence of the rumen methanogen Methanobrevibacter ruminantium reveals new possibilities for controlling ruminant methane emissions..
      )? Do they have lower affinity for aqueous H2 (
      • Ungerfeld E.M.
      Metabolic hydrogen flows in rumen fermentation: Principles and possibilities of interventions..
      ) such that more escapes into the headspace? These latter authors described a threshold concept that needs further experimentation. Compared with other approaches used, this inhibitor appears to be persistent in mode of action and potential responsiveness (
      • Løvendahl P.
      • Difford G.F.
      • Li B.
      • Chagunda M.G.G.
      • Huhtanen P.
      • Lidauer M.H.
      • Lassen J.
      • Lund P.
      Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle..
      ), so the potential to inoculate alternate H2-using probiotics to limit H2 emission needs further attention for potential application (
      • Greening C.
      • Geier R.
      • Wang C.
      • Woods L.C.
      • Morales S.E.
      • McDonald M.J.
      • Rushton-Green R.
      • Morgan X.C.
      • Koike S.
      • Leahy S.C.
      • Kelly W.J.
      • Cann I.
      • Attwood G.T.
      • Cook G.M.
      • Mackie R.I.
      Diverse hydrogen production and consumption pathways influence methane production in ruminants..
      ).
      Methanogenesis suppression must be viewed with a wider lens for lactate and biohydrogenation in the rumen. The aqueous H2- and lactate-consuming Megasphaera abundance was associated with decreased methane emission and improved feed efficiency (
      • Denman S.E.
      • Morgavi D.P.
      • McSweeney C.S.
      Review: The application of omics to rumen microbiota function..
      ). Megasphaera relative abundance has been associated with biohydrogenation patterns that depress milk fat (
      • Dewanckele L.
      • Vlaeminck B.
      • Hernandez-Sanabria E.
      • Ruiz-González A.
      • Debruyne S.
      • Jeyanathan J.
      • Fievez V.
      Rumen biohydrogenation and microbial community changes upon early life supplementation of 22:6n-3 enriched microalgae to goats..
      ;
      • Carreño D.
      • Toral P.G.
      • Pinloche E.
      • Belenguer A.
      • Yáñez-Ruiz D.R.
      • Hervás G.
      • McEwan N.R.
      • Newbold C.J.
      • Frutos P.
      Rumen bacterial community responses to DPA, EPA and DHA in cattle and sheep: A comparative in vitro study..
      ). The direct contribution of Megasphaera elsdenii to the trans-10 18:1 biohydrogenation pathway remains unverified and perhaps more likely to be associative and not causal (
      • Dewanckele L.
      • Toral P.G.
      • Vlaeminck B.
      • Fievez V.
      Invited review: Role of rumen biohydrogenation intermediates and rumen microbes in diet-induced milk fat depression: An update..
      ). Depressed milkfat might lessen feed efficiency by increasing partition of dietary fatty acids to adipose tissue (
      • Harvatine K.J.
      • Perfield II, J.W.
      • Bauman D.E.
      Expression of enzymes and key regulators of lipid synthesis is upregulated in adipose tissue during CLA-induced milk fat depression in dairy cows..
      ), which is why feed efficiency measurements should account for potential differences in BW gain. Low pH is often associated with milkfat depression but also with inhibited methanogenesis (
      • Van Kessel J.S.
      • Russell J.B.
      The effect of pH on ruminal methanogenesis..
      ). Because lactate is a stronger acid than the VFA, lactate accumulation should be avoided because of its effect on ruminal NDFD and its potential to exacerbate UFA toxicity to the butyrivibrios (
      • Firkins J.L.
      • Yu Z.
      How to use data on the rumen microbiome to improve our understanding of ruminant nutrition..
      ). Decreasing pH independent of diet change did not decrease methanogenesis in continuous cultures but dramatically decreased H2 emission, suggesting a decrease in H2-producing pathways (
      • Wenner B.A.
      • de Souza J.
      • Batistel F.
      • Hackmann T.J.
      • Yu Z.
      • Firkins J.L.
      Association of aqueous hydrogen concentration with methane production in continuous cultures modulated to vary pH and solids passage rate..
      ). In that study, methanogenesis recovered after pH returned higher. In another study, decreasing pH did decrease methanogenesis (
      • Roman-Garcia Y.
      • Mitchell K.E.
      • Denton B.L.
      • Lee C.
      • Socha M.T.
      • Wenner B.A.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. II: Relation with solid passage rate and pH on neutral detergent fiber degradation and microbial function in continuous culture..
      ), perhaps because diets were fed more frequently. Longer time with lower pH should decrease methanogenesis but, unfortunately, also should suppress NDFD. As stated previously, managerial decisions to increase feeding frequency should improve ruminal fiber degradation. Unfortunately, low-methane-emitting cows also might have lower NDFD (
      • Løvendahl P.
      • Difford G.F.
      • Li B.
      • Chagunda M.G.G.
      • Huhtanen P.
      • Lidauer M.H.
      • Lassen J.
      • Lund P.
      Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle..
      ).
      Although not measured in most studies, an appreciation of formate metabolism helps explain variation in the rumen (
      • Ramayo-Caldas Y.
      • Zingaretti L.
      • Popova M.
      • Estellé J.
      • Bernard A.
      • Pons N.
      • Bellot P.
      • Mach N.
      • Rau A.
      • Roume H.
      • Perez-Enciso M.
      • Faverdin P.
      • Edouard N.
      • Ehrlich D.
      • Morgavi D.P.
      • Renand G.
      Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows..
      ). In the study by
      • Ramayo-Caldas Y.
      • Zingaretti L.
      • Popova M.
      • Estellé J.
      • Bernard A.
      • Pons N.
      • Bellot P.
      • Mach N.
      • Rau A.
      • Roume H.
      • Perez-Enciso M.
      • Faverdin P.
      • Edouard N.
      • Ehrlich D.
      • Morgavi D.P.
      • Renand G.
      Identification of rumen microbial biomarkers linked to methane emission in Holstein dairy cows..
      , genus Ruminococcus and other H2 producers were associated positively with methane emission. In another study (
      • Martínez-Álvaro M.
      • Auffret M.D.
      • Stewart R.D.
      • Dewhurst R.J.
      • Duthie C.-A.
      • Rooke J.A.
      • Wallace R.J.
      • Shih B.
      • Freeman T.C.
      • Watson M.
      • Roehe R.
      Identification of complex rumen microbiome interaction within diverse functional niches as mechanisms affecting the variation of methane emissions in bovine..
      ), Fibrobacter was positively associated with methanogenesis; those authors explained this association by its degradation of xylan that is degraded by H2-producers because Fibrobacter does not ferment arabinose or xylose (derived from hemicellulose) and it produces no H2 and only limited formate (
      • Neumann A.P.
      • Suen G.
      The phylogenomic diversity of herbivore-associated Fibrobacter spp. Is correlated to lignocellulose-degrading potential..
      ). Again, expanding from a few taxa to the consortium is needed to explain more variation.
      As important as is their production of H2 or formate (main substrates for methane), associations of protozoa (
      • Firkins J.L.
      • Yu Z.
      • Park T.
      • Plank J.E.
      Extending Burk Dehority’s perspectives on the role of ciliate protozoa in the rumen..
      ) and fungi (
      • Gruninger R.J.
      • Ribeiro G.O.
      • Cameron A.
      • McAllister T.A.
      Invited review: Application of meta-omics to understand the dynamic nature of the rumen microbiome and how it responds to diet in ruminants..
      ) abundance with methanogenesis should be considered more fully. Increasing protozoal counts were highly associated with increased methanogenesis (
      • Guyader J.
      • Eugene M.
      • Noziere P.
      • Morgavi D.P.
      • Doreau M.
      • Martin C.
      Influence of rumen protozoa on methane emission in ruminants: A meta-analysis approach..
      ). However, decreasing protozoal counts also was associated with decreased NDFD and decreasing DMI. Many (or perhaps most) of the methanogens are not specific protozoal symbionts. Some bacteria, especially those in the phylum Proteobacteria, were rather exclusively associated with protozoa compared with those in the surrounding ruminal fluid (
      • Park T.
      • Yu Z.
      Do ruminal ciliates select their preys and prokaryotic symbionts?.
      ). Protozoa might aid methanogens indirectly by relieving oxygen stress (
      • Park T.
      • Yu Z.
      Aerobic cultivation of anaerobic rumen protozoa, Entodinium caudatum and Epidinium caudatum..
      ), so the relationship might be symbiotic but not necessarily a direct result of endosymbiosis. Such benefits of anaerobiosis could extend to enhancing development of fungi (
      • Martínez-Álvaro M.
      • Auffret M.D.
      • Stewart R.D.
      • Dewhurst R.J.
      • Duthie C.-A.
      • Rooke J.A.
      • Wallace R.J.
      • Shih B.
      • Freeman T.C.
      • Watson M.
      • Roehe R.
      Identification of complex rumen microbiome interaction within diverse functional niches as mechanisms affecting the variation of methane emissions in bovine..
      ), which also interact extensively with methanogens yet lack the capacity for endosymbiosis (
      • Edwards J.E.
      • Forster R.J.
      • Callaghan T.M.
      • Dollhofer V.
      • Dagar S.S.
      • Cheng Y.
      • Chang J.
      • Kittelmann S.
      • Fliegerova K.
      • Puniya A.K.
      • Henske J.K.
      • Gilmore S.P.
      • O’Malley M.A.
      • Griffith G.W.
      • Smidt H.
      PCR and omics based techniques to study the diversity, ecology and biology of anaerobic fungi: Insights, challenges and opportunities..
      ).

      IMPROVING MILK NITROGEN EFFICIENCY THROUGH RUMINAL PROCESSES

      Ruminal Nitrogen Efficiency in a System

      Milk N efficiency (milk N production/N intake) averages less than 30% (
      • Hristov A.N.
      • Bannink A.
      • Crompton L.A.
      • Huhtanen P.
      • Kreuzer M.
      • McGee M.
      • Nozière P.
      • Reynolds C.K.
      • Bayat A.R.
      • Yáñez-Ruiz D.R.
      • Dijkstra J.
      • Kebreab E.
      • Schwarm A.
      • Shingfield K.J.
      • Yu Z.
      Invited review: Nitrogen in ruminant nutrition: A review of measurement techniques..
      ), documenting opportunity to improve efficiency of conversion of RDP into microbial CP in the rumen. However, just as with feed efficiency (e.g., ECM/DMI) or methane (e.g., methane/DMI) metrics, ratios have problems both for genetic selection and potentially violating statistical assumptions (
      • Løvendahl P.
      • Difford G.F.
      • Li B.
      • Chagunda M.G.G.
      • Huhtanen P.
      • Lidauer M.H.
      • Lassen J.
      • Lund P.
      Review: Selecting for improved feed efficiency and reduced methane emissions in dairy cattle..
      ). From a practical standpoint, if the denominator decreased more than the numerator decreased, then the increased ratio would reflect an undesirable response. If decreasing CP decreased DMI (
      • Zanton G.I.
      Analysis of production responses to changing crude protein levels in lactating dairy cow diets when evaluated in continuous or change-over experimental designs..
      ), more replacement animals (and their daily CP intake) might be needed in a wider system. Thus, more efforts are needed to assess life cycles that include broader managerial strategies (
      • Foskolos A.
      • Moorby J.M.
      Evaluating lifetime nitrogen use efficiency of dairy cattle: A modelling approach..
      ).

      Firkins, J. L., and R. I. Mackie. 2020. Ruminal protein breakdown and ammonia assimilation. Pages 383–420 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      discussed the importance of understanding and decreasing intraruminal recycling of microbial protein and maintaining adequate RDP within the context of optimizing milk N efficiency.
      • Huws S.A.
      • Creevey C.J.
      • Oyama L.B.
      • Mizrahi I.
      • Denman S.E.
      • Popova M.
      • Muñoz-Tamayo R.
      • Forano E.
      • Waters S.M.
      • Hess M.
      • Tapio I.
      • Smidt H.
      • Krizsan S.J.
      • Yáñez-Ruiz D.R.
      • Belanche A.
      • Guan L.
      • Gruninger R.J.
      • McAllister T.A.
      • Newbold C.J.
      • Roehe R.
      • Dewhurst R.J.
      • Snelling T.J.
      • Watson M.
      • Suen G.
      • Hart E.H.
      • Kingston-Smith A.H.
      • Scollan N.D.
      • do Prado R.M.
      • Pilau E.J.
      • Mantovani H.C.
      • Attwood G.T.
      • Edwards J.E.
      • McEwan N.R.
      • Morrisson S.
      • Mayorga O.L.
      • Elliott C.
      • Morgavi D.P.
      Addressing global ruminant agricultural challenges through understanding the rumen microbiome: Past, present, and future..
      concluded that a better understanding of rumen microbial processes is needed to improve N usage efficiency.

      Ruminal Nitrogen Metabolism

      Many aspects of ruminal N metabolism are well established. Most of the bacteria and virtually all archaea and fungi assimilate ammonia, whereas protozoa rely primarily on preformed AA from bacteria and to a lesser extent on RDP (

      Firkins, J. L., and R. I. Mackie. 2020. Ruminal protein breakdown and ammonia assimilation. Pages 383–420 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ). Limiting RDP could improve milk N efficiency in some cases but could disrupt ruminal processes in other situations that remain unpredictable. This issue seems to extend beyond just maintaining a critical NH3-N concentration because expression of ammonium transporter and assimilation enzymes help the cells salvage N very effectively even if this adaptation costs ATP and possibly decreases EMPS.
      • Ahvenjärvi S.
      • Huhtanen P.
      Effects of intraruminal urea-nitrogen infusions on feed intake, nitrogen utilization, and milk yield in dairy cows..
      noted a threshold of 14% CP below which increasing urea transfer into the rumen of dairy cattle would not increase ruminal NH3-N concentration.
      • Batista E.D.
      • Detmann E.
      • Valadares Filho S.C.
      • Titgemeyer E.C.
      • Valadares R.F.D.
      The effect of CP concentration in the diet on urea kinetics and microbial usage of recycled urea in cattle: A meta-analysis..
      noted that, above about 12% CP, urea recycling from blood to the ruminal pool available for microbial assimilation was relatively constant. Rumen epithelium expression of urea transporters decreases as ruminal NH3-N concentration increases (
      • Lu Z.
      • Stumpff F.
      • Deiner C.
      • Rosendahl J.
      • Braun H.
      • Abdoun K.
      • Aschenbach J.R.
      • Martens H.
      Modulation of sheep ruminal urea transport by ammonia and pH..
      ;
      • Patra A.K.
      • Aschenbach J.R.
      Ureases in the gastrointestinal tracts of ruminant and monogastric animals and their implication in urea-N/ammonia metabolism: A review..
      ). However, the urea that is hydrolyzed to NH3 tends to be absorbed back into the blood rather than diffuse into the ruminal mat (
      • Lu Z.
      • Stumpff F.
      • Deiner C.
      • Rosendahl J.
      • Braun H.
      • Abdoun K.
      • Aschenbach J.R.
      • Martens H.
      Modulation of sheep ruminal urea transport by ammonia and pH..
      ;
      • Hartinger T.
      • Gresner N.
      • Südekum K.-H.
      Does intra-ruminal nitrogen recycling waste valuable resources? A review of major players and their manipulation..
      ) when NH3-N concentration is more typical of what would be expected in cows fed typical lactation diets (e.g., 15 to 17% CP). The role of NH3-N gradients between the fluid localizing near the rumen wall relative to the fluid exchanging with the rumen mat in dairy cattle is discussed further by
      • Ahvenjärvi S.
      • Huhtanen P.
      Effects of intraruminal urea-nitrogen infusions on feed intake, nitrogen utilization, and milk yield in dairy cows..
      . Approximately 15% of bacterial N is derived from BUN in typical dairy diets (≥15% CP), and BUN buffers diurnal periods of lower ruminal NH3-N (
      • Reynolds C.K.
      • Kristensen N.B.
      Nitrogen recycling through the gut and the nitrogen economy of ruminants: An asynchronous symbiosis..
      ). However, BUN transfer into microbial N is likely only much greater than 15% (perhaps 30 to 50%) with beef cattle consuming high forage/low CP range or very low forage diets.
      Defaunation (removal of protozoa) is typically associated with decreased ruminal NH3-N (
      • Newbold C.J.
      • de la Fuente G.
      • Belanche A.
      • Ramos-Morales E.
      • McEwan N.R.
      The role of ciliate protozoa in the rumen..
      ). However, the typical explanation of decreased protozoal proteolysis and deamination can only be part of the explanation. Bacteria filling the protozoal void can assimilate NH3-N, whereas protozoa cannot. If we move to practical approaches to suppress protozoa to decrease methanogenesis (previous section), we will need to recognize their role in limiting AA and ammonia deficiencies as we decrease dietary RDP. We should be evaluating the branched-chain AA (BCAA) profile in RDP if we are to avoid limitations in branched-chain VFA (BCVFA) that are needed for optimal fiber degradation (see next section). Protozoa might actually benefit from low RDP diets because they compete for substrate with bacteria, which are their main source of AA and nucleic acids, not RDP (
      • Dennis S.M.
      • Arambel M.J.
      • Bartley E.E.
      • Dayton A.D.
      Effect of energy concentration and source of nitrogen on numbers and types of rumen protozoa..
      ). There is the potential to use feed additives to selectively inhibit the bacteria that use AA for fuel rather than protein synthesis (
      • Hartinger T.
      • Gresner N.
      • Südekum K.-H.
      Does intra-ruminal nitrogen recycling waste valuable resources? A review of major players and their manipulation..
      ). Monensin and plant components likely decrease proteolysis or deamination (
      • Firkins J.L.
      • Yu Z.
      How to use data on the rumen microbiome to improve our understanding of ruminant nutrition..
      ;

      Firkins, J. L., and R. I. Mackie. 2020. Ruminal protein breakdown and ammonia assimilation. Pages 383–420 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ). Persistence of some compounds has not been well established, though.
      To more consistently decrease RDP without side effects rippling negatively through the microbial consortium, we need to reconsider how microbes use AA. Considerable landmark research has been done with pure cultures both in batch or single-flow continuous culture (
      • Russell J.B.
      • Hespell R.B.
      Microbial rumen fermentation..
      ). However, few studies have addressed the role of N limitation and potential interactions with carbohydrate availability (
      • Hackmann T.J.
      • Firkins J.L.
      Maximizing efficiency of rumen microbial protein production..
      ).
      • Belanche A.
      • Doreau M.
      • Edwards J.E.
      • Moorby J.M.
      • Pinloche E.
      • Newbold C.J.
      Shifts in the rumen microbiota due to the type of carbohydrate and level of protein ingested by dairy cattle are associated with changes in rumen fermentation..
      restricted RDP to 15% below requirements. Ruminal NH3-N concentration declined the most when this diet was combined with a higher-starch diet, which should increase microbial growth and competition for end products from protein hydrolysis. Both bacterial and fungal richness decreased with this combination of low RDP and greater starch, but all major groups of microbes declined in abundance with decreasing RDP. The RDP requirement seemed to vary with respect to different feeds, even when OM degradability was considered (
      • Soliva C.
      • Amelchanka S.
      • Kreuzer M.
      The requirements for rumen-degradable protein per unit of fermentable organic matter differ between fibrous feed sources..
      ). Those authors reasoned that BCVFA concentrations were not limiting. Although the spatial separation of fluid from particles in their Rusitec continuous culture system should be considered, more work like this is needed with accompanying analyses of microbial structure. Post priori associations of BCVFA concentrations with response criteria such as NDFD should not be the basis for assessing limitation; instead, direct BCVFA dosing has a stronger causal relationship.

      Role for BCVFA in Lower RDP Diets

      Concentration of BCVFA and ammonia interacted in a meta-analysis of EMPS in dairy cattle (
      • Roman-Garcia Y.
      • White R.R.
      • Firkins J.L.
      Meta-analysis of postruminal microbial nitrogen flows in dairy cattle. I. Derivation of equations..
      ). We suggested that very low NH3-N and isovalerate limited EMPS when degraded carbohydrate was not the limiting factor, but there was no direct way to assess this relationship. Moreover, a similar relationship with isobutyrate was noted. After that publication, we have noted that the isovalerate response might also have a response to 2-methylbutyrate, which coeluted with isovalerate in most published reports. One or more BCVFA are needed by the most well characterized cellulolytics (
      • Russell J.B.
      • Hespell R.B.
      Microbial rumen fermentation..
      ). The predominant amylolytic Prevotella ruminicola does not require BCVFA but still will carboxylate them to BCAA while inhibiting BCAA synthesis de novo (
      • Allison M.J.
      • Baetz A.L.
      • Wiegel J.
      Alternative pathways for biosynthesis of leucine and other amino acids in Bacteroides ruminicola and Bacteroides fragilis..
      ). Presumably, use of the BCVFA carbon skeleton spares the synthesis of enzymes needed to make that the BCAA’s keto acid (derived from BCVFA-CoA) without draining central metabolites that could be prioritized elsewhere in cellular reactions. The BCAA combine to almost 20% of the total AA in microbes (
      • Sok M.
      • Ouellet D.R.
      • Firkins J.L.
      • Pellerin D.
      • Lapierre H.
      Amino acid composition of rumen bacteria and protozoa in cattle..
      ), and BCVFA are primers for required branched fatty acids in bacterial membranes (
      • Roman-Garcia Y.
      • Denton B.L.
      • Mitchell K.E.
      • Lee C.
      • Socha M.T.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. I: Comparison with branched-chain amino acids and forage source in ruminal batch cultures..
      ,
      • Roman-Garcia Y.
      • Mitchell K.E.
      • Lee C.
      • Socha M.T.
      • Park T.
      • Wenner B.A.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. III: Relation with solid passage rate and pH on prokaryotic fatty acid profile and community in continuous culture..
      ).
      The BCAA were relatively highly incorporated into bacterial protein compared with other AA except for Phe (
      • Atasoglu C.
      • Guliye A.Y.
      Use of stable isotopes to measure de novo synthesis and turnover of amino acid-C and -N in mixed micro-organisms from the sheep rumen in vitro..
      ). Based on isotopomer analysis, decarboxylation of BCAA to BCVFA and reductive carboxylation of BCVFA to BCAA likely cycled extensively. Leu was catabolized more than Ile or Val in those mixed rumen bacteria, which was also noted for a hyper-ammonia-producing bacterium that uses AA for fuel (
      • Chen G.J.
      • Russell J.B.
      Fermentation of peptides and amino acids by a monensin-sensitive ruminal Peptostreptococcus..
      ).
      • Roman-Garcia Y.
      • Mitchell K.E.
      • Denton B.L.
      • Lee C.
      • Socha M.T.
      • Wenner B.A.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. II: Relation with solid passage rate and pH on neutral detergent fiber degradation and microbial function in continuous culture..
      discussed the likelihood for ferredoxin-linked BCAA metabolism, particularly for the dominant bacterial proteolytic genus Prevotella spp. Therefore, a role for BCAA decarboxylation in ATP generation by ruminal prevotellas was probably overlooked when ferredoxin was not considered as a cofactor (
      • Hino T.
      • Russell J.B.
      Effect of reducing-equivalent disposal and NADH/NAD on deamination of amino acids by intact rumen microorganisms and their cell extracts..
      ). The BCAA (especially Leu and to a lesser extent Ile) are likely pleiotropic transcription regulators influenced by intracellular BCAA concentrations by which bacterial cells coordinate carbon metabolism with availability of AA and NH3-N (
      • Roman-Garcia Y.
      • Mitchell K.E.
      • Denton B.L.
      • Lee C.
      • Socha M.T.
      • Wenner B.A.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. II: Relation with solid passage rate and pH on neutral detergent fiber degradation and microbial function in continuous culture..
      ).
      • Kajikawa H.
      • Mitsumori M.
      • Tajima K.
      • Kurihara M.
      Short communication: Amino acids antagonistic to the amino acids inhibitory for growth rate of mixed ruminal bacteria..
      noted that adding Val without the other 2 BCAA was not inhibitory, but Leu and Ile were more likely to be inhibitory if not balanced with the other 2 BCAA. Therefore, the BCVFA are likely a better reserve for subsequent BCAA synthesis with less risk for imbalance by BCAA.
      The conversion of BCAA to BCVFA by proteolytic and deaminating bacteria provides BCVFA to cellulolytics in a balanced consortium (
      • Moraïs S.
      • Mizrahi I.
      Islands in the stream: From individual to communal fiber degradation in the rumen ecosystem..
      ), but this cross-feeding is lost if the BCVFA are further catabolized. Hyper-ammonia-producing bacteria might rely partly on the Stickland reaction, which pairs an oxidized and reduced AA (
      • Chen G.J.
      • Russell J.B.
      Fermentation of peptides and amino acids by a monensin-sensitive ruminal Peptostreptococcus..
      ) and would theoretically spare further catabolism. However, this reaction provides relatively little ATP (

      Ungerfeld, E. M., and T. J. Hackmann. 2020. Factors influencing the efficiency of rumen energy metabolism. Pages 421–466 in Improving Rumen Function. C. S. McSweeney and R. I. Mackie, ed. Burleigh Dodds Sci. Publ.

      ), which would favor other mechanisms being involved as a growth strategy to compete in the rumen. Other hyper-ammonia-producing isolates tend to be in the class Clostridiales (
      • Attwood G.T.
      • Klieve A.V.
      • Ouwerkerk D.
      • Patel B.K.C.
      Ammonia-hyperproducing bacteria from New Zealand ruminants..
      ;
      • Bento C.B.P.
      • de Azevedo A.C.
      • Detmann E.
      • Mantovani H.C.
      Biochemical and genetic diversity of carbohydrate-fermenting and obligate amino acid-fermenting hyper-ammonia-producing bacteria from Nellore steers fed tropical forages and supplemented with casein..
      ), although relatively little is known about their role in the rumen of dairy cattle. Because many taxa in this group likely ferment other AA in addition to the BCAA, supplementing BCVFA might be less likely to expand the abundance of this group than supplementing BCAA.
      After BCVFA were studied in the 1980s, more current research has been done with higher-producing dairy cows and has used more sophisticated techniques assessing bacterial communities. Supplemental valine stimulated milk production, most likely mediated by isobutyrate and potentially thyroxine in late-lactation cows (
      • Hultquist K.M.
      • Casper D.P.
      Effects of feeding rumen-degradable valine on milk production in late-lactating dairy cows..
      ). Supplementing all 3 BCVFA in equal proportion increased DMI and production of milk components in a continuous lactation study (
      • Wang C.
      • Liu Q.
      • Guo G.
      • Huo W.J.
      • Zhang Y.L.
      • Pei C.X.
      • Zhang S.L.
      Effects of rumen-protected folic acid and branched-chain volatile fatty acids supplementation on lactation performance, ruminal fermentation, nutrient digestion and blood metabolites in dairy cows..
      ). Growth hormone increased, and data supported increased NDFD as suggested to be mediated by increased abundance of F. succinogenes, Ruminococcus albus, and Ruminococcus flavefaciens (which require one or more BCVFA). That Butyrivibrio fibrisolvens and Prevotella ruminicola (which are not known to require BCVFA) also increased suggests that supplementing BCVFA benefited the entire consortium.
      In continuous culture, supplementation of BCVFA increased relative sequence abundance of Fibrobacter and Treponema, which are mutualistic core members that require BCVFA (
      • Roman-Garcia Y.
      • Mitchell K.E.
      • Lee C.
      • Socha M.T.
      • Park T.
      • Wenner B.A.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. III: Relation with solid passage rate and pH on prokaryotic fatty acid profile and community in continuous culture..
      ). Adding BCVFA increased NDFD by 5 percentage units. Similarly, supplementing BCVFA also increased NDFD by 3 percentage units in continuous culture (
      • Mitchell K.E.
      • Wenner B.A.
      • Lee C.
      • Socha M.T.
      • Firkins J.L.
      Stimulation of microbial protein synthesis by branched chain volatile fatty acids (BCVFA) in dual-flow cultures varying in forage and PUFA concentrations..
      ). The 7% increased bacterial N flow suggests a proportional increase in growth of all taxa because relative bacterial abundance was not affected (K. Mitchell, T. Park, B. Wenner, and C. Lee, Department of Animal Sciences, The Ohio State University, Columbus; M. Socha and D. Kleinschmit, Zinpro, Eden Prairie, MN; and J. Firkins, Department of Animal Sciences, The Ohio State University, Columbus, unpublished data). In lactating cows, BCVFA did not increase NDFD, perhaps because the diets had relatively high starch and PUFA intended to depress milkfat such that NDFD could not be recovered (
      • Lee C.
      • Copelin J.E.
      • Park T.
      • Mitchell K.E.
      • Firkins J.L.
      • Socha M.T.
      • Luchini D.
      Effects of diet fermentability and supplementation of 2-hydroxy-4-(methylthio)-butanoic acid and isoacids on milk fat depression: 2. Ruminal fermentation, fatty acid, and bacterial community structure..
      ). However, bacterial diversity was increased by adding BCVFA. In the companion paper, supplementing BCVFA prevented milkfat depression by increasing de novo synthesis of fatty acids (
      • Copelin J.E.
      • Firkins J.L.
      • Socha M.T.
      • Lee C.
      Effects of diet fermentability and supplementation of 2-hydroxy-4-(methylthio)-butanoic acid and isoacids on milk fat depression: 1. Production, milk fatty acid profile, and nutrient digestibility..
      ).
      Adding isobutyrate and 2-methylbutyrate improved feed efficiency in lactating Jersey cows (
      • Mitchell K.E.
      • Socha M.T.
      • Moraes L.E.
      • Roman-Garcia Y.
      • Firkins J.L.
      Assessing milk response to branched-chain volatile fatty acids..
      ). Because the cows were mostly in mid lactation, a greater NDFD probably allowed cows to meet their energetic needs with lower DMI. Greater NDFD has typically been associated with increased DMI (
      • Oba M.
      • Allen M.S.
      Evaluation of the importance of the digestibility of neutral detergent fiber from forage: Effects on dry matter intake and milk yield of dairy cows..
      ). With increasing milk yield, the DMI-limiting effect of forage NDFD is probably exacerbated (
      • Allen M.S.
      • Sousa D.O.
      • VandeHaar M.J.
      Equation to predict feed intake response by lactating cows to factors related to the filling effect of rations..
      ). Thus, a benefit in NDFD from supplementing BCVFA would be more likely to increase DMI in early-lactation cows but improve efficiency through comparable milk but lower DMI in later lactation.
      Dietary conditions likely influence the BCVFA mechanism. If dietary RDP is meeting the needs of ruminal microbes for BCAA or BCVFA derived therefrom, then a BCVFA response in microbial protein synthesis or NDFD is less likely (
      • Copelin J.E.
      • Firkins J.L.
      • Socha M.T.
      • Lee C.
      Effects of diet fermentability and supplementation of 2-hydroxy-4-(methylthio)-butanoic acid and isoacids on milk fat depression: 1. Production, milk fatty acid profile, and nutrient digestibility..
      ). A high contribution of Leu from corn protein makes isovalerate less likely to provide benefit for dairy cattle; this finding is extended with our batch culture results showing isovalerate is less likely to be beneficial than isobutyrate or 2-methylbutyrate (
      • Roman-Garcia Y.
      • Denton B.L.
      • Mitchell K.E.
      • Lee C.
      • Socha M.T.
      • Firkins J.L.
      Conditions stimulating neutral detergent fiber degradation by dosing branched-chain volatile fatty acids. I: Comparison with branched-chain amino acids and forage source in ruminal batch cultures..
      ), which are from valine and isoleucine, respectively. Diets should be moderate in starch and have adequate but not excessive forage NDF to maximize the benefit from BCVFA addition (
      • Copelin J.E.
      • Firkins J.L.
      • Socha M.T.
      • Lee C.
      Effects of diet fermentability and supplementation of 2-hydroxy-4-(methylthio)-butanoic acid and isoacids on milk fat depression: 1. Production, milk fatty acid profile, and nutrient digestibility..
      ).
      If DMI is increased as a result of increased NDFD, microbial protein production is most likely also increased because DMI tends to be the best predictor for microbial protein synthesis (
      • Roman-Garcia Y.
      • White R.R.
      • Firkins J.L.
      Meta-analysis of postruminal microbial nitrogen flows in dairy cattle. I. Derivation of equations..
      ). Thus, BCVFA supplementation should substitute for RDP and thereby help to safeguard against depressed microbial protein that could result from insufficiency of rumen-degraded AA (
      • Broderick G.A.
      • Reynal S.M.
      Effect of source of rumen-degraded protein on production and ruminal metabolism in lactating dairy cows..
      ) and perhaps the potential for CP to limit DMI (
      • Allen M.S.
      Effects of diet on short-term regulation of feed intake by lactating dairy cattle..
      ;
      • Zanton G.I.
      Analysis of production responses to changing crude protein levels in lactating dairy cow diets when evaluated in continuous or change-over experimental designs..
      ). Unfortunately, a proper assessment of the role of RDP on DMI is challenging because almost all papers rely on feed library values for RDP, many of which ignore the true variability among feeds from those various studies and some of which were derived problematically (
      • Liebe D.M.
      • Firkins J.L.
      • Tran H.
      • Kononoff P.J.
      • White R.R.
      Technical note: Methodological and feed factors affecting measurement of protein a, b, and C fractions, degradation rate, and intestinal digestibility of rumen-undegraded protein..
      ). Not all of this CP response appears to result from RDP alone because several studies have shown that repleting MP or AA also can increase DMI. Even so, if RDP replenishment lessened NDF fill via greater NDFD (
      • Allen M.S.
      Effects of diet on short-term regulation of feed intake by lactating dairy cattle..
      ), increasing DMI also should increase supply of microbial protein, which is an excellent source of most EAA (
      • Sok M.
      • Ouellet D.R.
      • Firkins J.L.
      • Pellerin D.
      • Lapierre H.
      Amino acid composition of rumen bacteria and protozoa in cattle..
      ).
      Most of our ration software is either parameterized or evaluated based on meta-analyses of microbial protein flow. Not accounting for depressed EMPS with higher-starch diets (especially if RDP is limited) could overpredict microbial protein supply, which would limit MP. Moreover, if RDP is less than what is needed for optimal EMPS, then DMI also might be restricted. If microbial protein flow is underpredicted, the ration might be more expensive than is needed because of increased inclusion of expensive RUP sources beyond what was actually needed. Thus, BCVFA could help to buffer against depressed EMPS and decreased DMI in dairy cows.

      APPLICATIONS

      Just as a good dairy ration starts with the forage available, a good rumen efficiency starts with optimizing the functionality of the fibrolytic microbes. Microbial sequencing techniques are commonly being used to help explore sources of variation among animals and dietary conditions within studies. These approaches need to advance beyond simple correlations to network analyses that are more reflective of microbial consortia. Then, maybe we can derive more causally related associations to improve predictability of models and thereby manipulate dietary conditions that otherwise would have been embedded in unknown random effects. In addition, animal selection for these efficient types of populations or selective microbial screening among less efficient animals has some potential promise. However, to effectuate such approaches, progress in diet formulation should be adapted concomitantly. Fiber degradation starts with both quality and processing of forages to maintain a proper physical environment. Chemically, starch should be provided in a “goldilocks” approach to improve DE without depressing NDFD or EMPS beyond what is expected by the evaluation software. The physically adjusted NDF approach helps integrate various factors involved in processing of forage under different dietary starch and forage NDF scenarios while unbundling dietary NDF from sieve fractions. This approach should continue to improve as more research is done. Attempts to oversimplify protozoal or methanogen suppression need to consider the wider role of microbial consortia. We must better address the role of interspecies H2 metabolism if we are to suppress enteric methanogenesis without disturbing feed efficiency. Similarly, as we move to increase milk N efficiency, we need to take care to not disrupt NDFD or DMI (and they are related through ruminal filling effects). A promising approach is to supplement BCVFA to substitute for RDP to support fibrolytic bacteria and their primary role to maintain a properly balanced microbial consortium.

      ACKNOWLEDGMENTS

      This research was jointly supported by state and federal funds appropriated to the Ohio Agricultural Research and Development Center, The Ohio State University.

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