Culture techniques for ciliate protozoa from the rumen: Recent advances and persistent challenges.

Ciliate protozoa are key members of the microbial community of the rumen. Their study is important to the health and productivity of cattle, which are their hosts. However, there have been persistent challenges in culturing this microbial group in the laboratory. This review will sum up recent advances along with these persistent challenges. Protozoa have been maintained in three types of cultures (ex vivo, in vitro batch, in vitro continuous). Ex vivo cultures are prepared readily from rumen contents by washing away contaminating cells (e.g., bacteria). They have been useful in making basic observations of metabolism, such as which types of fermentation products protozoa form. However, these cultures can be maintained for only short periods (minutes or hours). In vitro batch and in vitro continuous cultures can be used in longer experiments (weeks or longer). However, it is not currently possible to maintain protozoa in these cultures unless bacteria are also present. We conclude the review with a protocol for preparing ex vivo cultures of protozoa. Our protocol has been standardized and used successfully across animal diets, users, and institutions. We anticipate this review will prepare others to culture rumen ciliate protozoa and reach new insights into this important microbial group.

Methane prediction equations including genera of rumen bacteria as predictor variables improve prediction accuracy.

Methane (CH4) emissions from ruminants are of a significant environmental concern, necessitating accurate prediction for emission inventories. Existing models rely solely on dietary and host animal-related data, ignoring the predicting power of rumen microbiota, the source of CH4. To address this limitation, we developed novel CH4 prediction models incorporating rumen microbes as predictors, alongside animal- and feed-related predictors using four statistical/machine learning (ML) methods. These include random forest combined with boosting (RF-B), least absolute shrinkage and selection operator (LASSO), generalized linear mixed model with LASSO (glmmLasso), and smoothly clipped absolute deviation (SCAD) implemented on linear mixed models. With a sheep dataset (218 observations) of both animal data and rumen microbiota data (relative sequence abundance of 330 genera of rumen bacteria, archaea, protozoa, and fungi), we developed linear mixed models to predict CH4 production (g CH4/animal·d, ANIM-B models) and CH4 yield (g CH4/kg of dry matter intake, DMI-B models). We also developed models solely based on animal-related data. Prediction performance was evaluated 200 times with random data splits, while fitting performance was assessed without data splitting. The inclusion of microbial predictors improved the models, as indicated by decreased root mean square prediction error (RMSPE) and mean absolute error (MAE), and increased Lin's concordance correlation coefficient (CCC). Both glmmLasso and SCAD reduced the Akaike information criterion (AIC) and Bayesian information criterion (BIC) for both the ANIM-B and the DMI-B models, while the other two ML methods had mixed outcomes. By balancing prediction performance and fitting performance, we obtained one ANIM-B model (containing 10 genera of bacteria and 3 animal data) fitted using glmmLasso and one DMI-B model (5 genera of bacteria and 1 animal datum) fitted using SCAD. This study highlights the importance of incorporating rumen microbiota data in CH4 prediction models to enhance accuracy and robustness. Additionally, ML methods facilitate the selection of microbial predictors from high-dimensional metataxonomic data of the rumen microbiota without overfitting. Moreover, the identified microbial predictors can serve as biomarkers of CH4 emissions from sheep, providing valuable insights for future research and mitigation strategies.

Metabolic influence of core ciliates within the rumen microbiome.

Protozoa comprise a major fraction of the microbial biomass in the rumen microbiome, of which the entodiniomorphs (order: Entodiniomorphida) and holotrichs (order: Vestibuliferida) are consistently observed to be dominant across a diverse genetic and geographical range of ruminant hosts. Despite the apparent core role that protozoal species exert, their major biological and metabolic contributions to rumen function remain largely undescribed in vivo. Here, we have leveraged (meta)genome-centric metaproteomes from rumen fluid samples originating from both cattle and goats fed diets with varying inclusion levels of lipids and starch, to detail the specific metabolic niches that protozoa occupy in the context of their microbial co-habitants. Initial proteome estimations via total protein counts and label-free quantification highlight that entodiniomorph species Entodinium and Epidinium as well as the holotrichs Dasytricha and Isotricha comprise an extensive fraction of the total rumen metaproteome. Proteomic detection of protozoal metabolism such as hydrogenases (Dasytricha, Isotricha, Epidinium, Enoploplastron), carbohydrate-active enzymes (Epidinium, Diplodinium, Enoploplastron, Polyplastron), microbial predation (Entodinium) and volatile fatty acid production (Entodinium and Epidinium) was observed at increased levels in high methane-emitting animals. Despite certain protozoal species having well-established reputations for digesting starch, they were unexpectedly less detectable in low methane emitting-animals fed high starch diets, which were instead dominated by propionate/succinate-producing bacterial populations suspected of being resistant to predation irrespective of host. Finally, we reaffirmed our abovementioned observations in geographically independent datasets, thus illuminating the substantial metabolic influence that under-explored eukaryotic populations have in the rumen, with greater implications for both digestion and methane metabolism.

Network analysis to evaluate complexities in relationships among fermentation variables measured within continuous culture experiments.

The objective of this study was to leverage a frequentist (ELN) and Bayesian learning (BLN) network analyses to summarize quantitative associations among variables measured in 4 previously published dual-flow continuous culture fermentation experiments. Experiments were originally designed to evaluate effects of nitrate, defaunation, yeast, and/or physiological shifts associated with pH or solids passage rates on rumen conditions. Measurements from these experiments that were used as nodes within the networks included concentrations of individual volatile fatty acids, mM and nitrate, NO3-,%; outflows of non-ammonia nitrogen (NAN, g/d), bacterial N (BN, g/d), residual N (RN, g/d), and ammonia N (NH3-N, mg/dL); degradability of neutral detergent fiber (NDFd, %) and degradability of organic matter (OMd, %); dry matter intake (DMI, kg/d); urea in buffer (%); fluid passage rate (FF, L/d); total protozoa count (PZ, cells/mL); and methane production (CH4, mmol/d). A frequentist network (ELN) derived using a graphical LASSO (least absolute shrinkage and selection operator) technique with tuning parameters selected by Extended Bayesian Information Criteria (EBIC) and a BLN were constructed from these data. The illustrated associations in the ELN were unidirectional yet assisted in identifying prominent relationships within the rumen that were largely consistent with current understanding of fermentation mechanisms. Another advantage of the ELN approach was that it focused on understanding the role of individual nodes within the network. Such understanding may be critical in exploring candidates for biomarkers, indicator variables, model targets, or other measurement-focused explorations. As an example, acetate was highly central in the network suggesting it may be a strong candidate as a rumen biomarker. Alternatively, the major advantage of the BLN was its unique ability to imply causal directionality in relationships. Because the BLN identified directional, cascading relationships, this analytics approach was uniquely suited to exploring the edges within the network as a strategy to direct future work researching mechanisms of fermentation. For example, in the BLN acetate responded to treatment conditions such as the source of N used and the quantity of substrate provided, while acetate drove changes in the protozoal populations, non-NH3-N and residual N flows. In conclusion, the analyses exhibit complementary strengths in supporting inference on the connectedness and directionality of quantitative associations among fermentation variables that may be useful in driving future studies.

This study leveraged frequentist (ELN) and Bayesian networks (BLN) to evaluate the potential of network analysis to explore complex rumen environments with interconnected quantitative associations. The approaches were selected based on their capacity for holistic exploration of all possible quantitative associations among variables, including opportunities to explore the potential strength and directionality of those associations. Data from 4 continuous culture experiments, involving 18 rumen variables [major and minor volatile fatty acid (VFA), degradability variables and nitrogen related variables], were used for network derivation. Variables within a network are denoted as nodes and relationships between two nodes are referred to as edges. The different networking approaches had different strengths for biological interpretation. Although the ELN approach was useful for exploring the role and importance of specific variables in the network, the BLN had more relevance in selecting edges or relationships linking those variables. These strengths are complementary and make a case for joint exploration of datasets using both approaches. Many of the biological inferences derived from the networks are well-acknowledged within the literature, acetate, valerate, isobutyrate, and isovalerate were important nodes within both networks, and important edges focused on the driving role of N dynamics within the rumen. Overall, these analyses demonstrated potential to illustrate associations and directionality of quantitative associations among fermentation variables. These associations can be used to direct future studies based on more comprehensive datasets.

The macronuclear genome of anaerobic ciliate Entodinium caudatum reveals its biological features adapted to the distinct rumen environment.

Entodinium caudatum is an anaerobic binucleated ciliate representing the most dominant protozoal species in the rumen. However, its biological features are largely unknown due to the inability to establish an axenic culture. In this study, we primally sequenced its macronucleus (MAC) genome to aid the understanding of its metabolism, physiology, ecology. We isolated the MAC of E. caudatum strain MZG-1 and sequenced the MAC genome using Illumina MiSeq, MinION, and PacBio RSII systems. De novo assembly of the MiSeq sequence reads followed with subsequent scaffolding with MinION and PacBio reads resulted in a draft MAC genome about 117 Mbp. A large number of carbohydrate-active enzymes were likely acquired through horizontal gene transfer. About 8.74% of the E. caudatum predicted proteome was predicted as proteases. The MAC genome of E. caudatum will help better understand its important roles in rumen carbohydrate metabolism, and interaction with other members of the rumen microbiome.

Extending Burk Dehority's Perspectives on the Role of Ciliate Protozoa in the Rumen.

Dr. Burk Dehority was an international expert on the classification and monoculture of ruminal ciliated protozoa. We have summarized many of the advancements in knowledge from his work but also in his scientific way of thinking about interactions of ruminal ciliates with the entire rumen microbial community and animal host. As a dedication to his legacy, an electronic library of high-resolution images and video footage catalogs numerous species and techniques involved in taxonomy, isolation, culture, and ecological assessment of ruminal ciliate species and communities. Considerable promise remains to adapt these landmark approaches to harness eukaryotic cell signaling technology with genomics and transcriptomics to assess cellular mechanisms regulating growth and responsiveness to ruminal environmental conditions. These technologies can be adapted to study how protozoa interact (both antagonism and mutualism) within the entire ruminal microbiota. Thus, advancements and limitations in approaches used are highlighted such that future research questions can be posed to study rumen protozoal contribution to ruminant nutrition and productivity.

The transcriptome of the rumen ciliate Entodinium caudatum reveals some of its metabolic features.

BACKGROUND: Rumen ciliates play important roles in rumen function by digesting and fermenting feed and shaping the rumen microbiome. However, they remain poorly understood due to the lack of definitive direct evidence without influence by prokaryotes (including symbionts) in co-cultures or the rumen. In this study, we used RNA-Seq to characterize the transcriptome of Entodinium caudatum, the most predominant and representative rumen ciliate species. RESULTS: Of a large number of transcripts, > 12,000 were annotated to the curated genes in the NR, UniProt, and GO databases. Numerous CAZymes (including lysozyme and chitinase) and peptidases were represented in the transcriptome. This study revealed the ability of E. caudatum to depolymerize starch, hemicellulose, pectin, and the polysaccharides of the bacterial and fungal cell wall, and to degrade proteins. Many signaling pathways, including the ones that have been shown to function in E. caudatum, were represented by many transcripts. The transcriptome also revealed the expression of the genes involved in symbiosis, detoxification of reactive oxygen species, and the electron-transport chain. Overall, the transcriptomic evidence is consistent with some of the previous premises about E. caudatum. However, the identification of specific genes, such as those encoding lysozyme, peptidases, and other enzymes unique to rumen ciliates might be targeted to develop specific and effective inhibitors to improve nitrogen utilization efficiency by controlling the activity and growth of rumen ciliates. The transcriptomic data will also help the assembly and annotation in future genomic sequencing of E. caudatum. CONCLUSION: As the first transcriptome of a single species of rumen ciliates ever sequenced, it provides direct evidence for the substrate spectrum, fermentation pathways, ability to respond to various biotic and abiotic stimuli, and other physiological and ecological features of E. caudatum. The presence and expression of the genes involved in the lysis and degradation of microbial cells highlight the dependence of E. caudatum on engulfment of other rumen microbes for its survival and growth. These genes may be explored in future research to develop targeted control of Entodinium species in the rumen. The transcriptome can also facilitate future genomic studies of E. caudatum and other related rumen ciliates.

Interspecies cross-feeding orchestrates carbon degradation in the rumen ecosystem.

Because of their agricultural value, there is a great body of research dedicated to understanding the microorganisms responsible for rumen carbon degradation. However, we lack a holistic view of the microbial food web responsible for carbon processing in this ecosystem. Here, we sampled rumen-fistulated moose, allowing access to rumen microbial communities actively degrading woody plant biomass in real time. We resolved 1,193 viral contigs and 77 unique, near-complete microbial metagenome-assembled genomes, many of which lacked previous metabolic insights. Plant-derived metabolites were measured with NMR and carbohydrate microarrays to quantify the carbon nutrient landscape. Network analyses directly linked measured metabolites to expressed proteins from these unique metagenome-assembled genomes, revealing a genome-resolved three-tiered carbohydrate-fuelled trophic system. This provided a glimpse into microbial specialization into functional guilds defined by specific metabolites. To validate our proteomic inferences, the catalytic activity of a polysaccharide utilization locus from a highly connected metabolic hub genome was confirmed using heterologous gene expression. Viral detected proteins and linkages to microbial hosts demonstrated that phage are active controllers of rumen ecosystem function. Our findings elucidate the microbial and viral members, as well as their metabolic interdependencies, that support in situ carbon degradation in the rumen ecosystem.

Physically adjusted neutral detergent fiber system for lactating dairy cow rations. I: Deriving equations that identify factors that influence effectiveness of fiber.

Physically effective neutral detergent fiber (peNDF) is the fraction of neutral detergent fiber (NDF) that stimulates chewing activity and contributes to the floating mat of large particles in the rumen. Multiplying dietary NDF by particle size has been used as an estimate of peNDF. In re-evaluating the concept of peNDF, we compared the use of peNDF as dietary NDF × particle size with the use of individual NDF and particle size descriptors (physically adjusted NDF; paNDF) when used with other physical and chemical diet descriptors to predict dry matter (DM) intake (DMI), rumination time, and ruminal pH in lactating dairy cows. The purpose is to ultimately use these equations to estimate diet adequacy to maintain ruminal conditions. Each response variable had 8 models in a 2 (peNDF, paNDF) × 2 (diet, diet and ruminal factors) × 2 (DM, as fed basis) factorial arrangement. Particle size descriptors were those determined with the Penn State Particle Separator. Treatment means (n = 241) from 60 publications were used in backward elimination multiple regression to derive models of response variables. When available, peNDF terms entered equations. Models containing peNDF terms had similar or lower unadjusted concordance correlation coefficients (an indicator of similar or lower accuracy and precision) than did models without peNDF terms. The peNDF models for rumen pH did not differ substantially from paNDF models. This suggests that peNDF can account for some variation in ruminal pH; however, overt advantages of peNDF were not apparent. Significant variables that entered the models included estimated mean particle size; as fed or DM proportions retained on 19- and 8-mm sieves of the Penn State Particle Separator; DMI; dietary concentrations of forage; forage NDF; CP; starch; NDF; rumen-degraded starch and rumen-degraded NDF; and the interaction terms of starch × mean particle size, acid detergent fiber/NDF, and rumination time/DMI. Many dietary factors beyond particle size and NDF were identified as influencing the response variables. In conclusion, these results appear to justify the development of a modeling approach to integrate individual physical and chemical factors to predict effects on factors affecting rumen conditions.

Physically adjusted neutral detergent fiber system for lactating dairy cow rations. II: Development of feeding recommendations.

The objective of this work was to leverage equations derived in a meta-analysis into an ensemble modeling system for estimating dietary physical and chemical characteristics required to maintain desired rumen conditions in lactating dairy cattle. Given the availability of data, responsiveness of ruminal pH to animal behaviors, and the chemical composition and physical form of the diet, mean ruminal pH was chosen as the primary rumen environment indicator. Physically effective fiber (peNDF) is defined as the fraction of neutral detergent fiber (NDF) that stimulates chewing activity and contributes to the floating mat of large particles in the rumen. The peNDF of feedstuffs is typically estimated by multiplying the NDF content by a particle size measure, resulting in an estimated index of effectiveness. We hypothesized that the utility of peNDF could be expanded and improved by dissociating NDF and particle size and considering other dietary factors, all integrated into a physically adjusted fiber system that can be used to estimate minimum particle sizes of TMR and diet compositions needed to maintain ruminal pH targets. Particle size measures of TMR were limited to those found with the Penn State particle separator (PSPS). Starting with specific diet characteristics, the system employed an ensemble of models that were integrated using a variable mixture of experts approach to generate more robust recommendations for the percentage of dietary DM material that should be retained on the 8-mm sieve of a PSPS. Additional continuous variables also integrated in the physically adjusted fiber system include the proportion of material (dry matter basis) retained on the 19- and 8-mm sieves of the PSPS, estimated mean particle size, the dietary concentrations of forage, forage NDF, starch, and NDF, and ruminally degraded starch and NDF. The system was able to predict that the minimum proportion of material (dry matter basis) retained on the 8-mm sieve should increase with decreasing forage NDF or dietary NDF. Additionally, the minimum proportion of dry matter material on the 8-mm sieve should increase with increasing dietary starch. Results of this study agreed with described interrelationships between the chemical and physical form of diets fed to dairy cows and quantified the links between NDF intake, diet particle size, and ruminal pH. Feeding recommendations can be interpolated from tables and figures included in this work.

Genomes of rumen bacteria encode atypical pathways for fermenting hexoses to short-chain fatty acids.

Bacteria have been thought to follow only a few well-recognized biochemical pathways when fermenting glucose or other hexoses. These pathways have been chiseled in the stone of textbooks for decades, with most sources rendering them as they appear in the classic 1986 text by Gottschalk. Still, it is unclear how broadly these pathways apply, given that they were established and delineated biochemically with only a few model organisms. Here, we show that well-recognized pathways often cannot explain fermentation products formed by bacteria. In the most extensive analysis of its kind, we reconstructed pathways for glucose fermentation from genomes of 48 species and subspecies of bacteria from one environment (the rumen). In total, 44% of these bacteria had atypical pathways, including several that are completely unprecedented for bacteria or any organism. In detail, 8% of bacteria had an atypical pathway for acetate formation; 21% of bacteria had an atypical pathway for propionate or succinate formation; 6% of bacteria had an atypical pathway for butyrate formation and 33% of bacteria had an atypical or incomplete Embden-Meyerhof-Parnas pathway. This study shows that reconstruction of metabolic pathways - a common goal of omics studies - could be incorrect if well-recognized pathways are used for reference. Furthermore, it calls for renewed efforts to delineate fermentation pathways biochemically.

Corrigendum: Inhibition of the Rumen Ciliate Entodinium caudatum by Antibiotics.

[This corrects the article on p. 1189 in vol. 8, PMID: 28702015.].

Inhibition of the Rumen Ciliate Entodinium caudatum by Antibiotics.

Axenic cultures of free-living aerobic ciliates, such as Tetrahymena thermophila and Paramecium aurelia, have been established and routinely used in laboratory research, greatly facilitating, or enabling characterization of their metabolism, physiology, and ecology. Ruminal protozoa are anaerobic ciliates, and they play important roles in feed digestion and fermentation. Although, repeatedly attempted, no laboratory-maintainable axenic culture of ruminal ciliates has been established. When axenic ciliate cultures are developed, antibiotics are required to eliminate the accompanying bacteria. Ruminal ciliates gradually lose viability upon antibiotic treatments, and the resultant axenic cultures can only last for short periods of time. The objective of this study was to evaluate eight antibiotics that have been evaluated in developing axenic cultures of ruminal ciliates, for their toxicity to Entodinium caudatum, which is the most predominant ruminal ciliate species. Scanning and transmission electron microscopy (TEM) showed that the antibiotics damaged both the cell surface and nuclei of E. caudatum and increased accumulation of intracellular glycogen. Combinations of the three least toxic antibiotics failed to eliminate the bacteria that are present in the E. caudatum culture. The combination of ampicillin, carbenicillin, streptomycin, and oxytetracycline was able to eliminate all the bacteria, but the resultant axenic E. caudatum culture gradually lost viability. Adding the bacterial fraction (live) separated from an untreated E. caudatum culture reversed the viability decline and recovered the growth of the treated E. caudatum culture, whereas feeding nine strains of live bacteria isolated from E. caudatum cells, either individually or in combination, could not. Nutritional and metabolic dependence on its associated bacteria, accompanied with direct and indirect inhibition by antibiotics, makes it difficult to establish an axenic culture of E. caudatum. Monoxenic or polyxenic cultures of E. caudatum could be developed if the essential symbiotic partner(s) can be identified.

Technical note: Methodological and feed factors affecting prediction of ruminal degradability and intestinal digestibility of essential amino acids.

We hypothesized that ruminal degradability of essential AA (EAA) and the intestinal digestibility of the ruminally undegraded EAA residue in feeds could be evaluated in a meta-analysis. The objective was to characterize methodological factors for ruminal incubation (time of incubation of feed in situ) and method of simulating digestion of the ruminally undegraded AA (incubation of residue in digestive enzymes in vitro or in mobile bags inserted into the duodenum). To increase numbers of observations, feeds were categorized before ANOVA. An approach is described to predict differential ruminal degradability (or undegradability) of individual EAA by normalizing them as a proportion of total AA (TAA) degradability (undegradability) and similarly to normalize the intestinal digestibility of EAA using TAA. Interaction of feed category with individual EAA justifies future studies with a broader range of feeds and more replication within feed to bolster this approach. With broader data, the approach to normalize EAA as a proportion of TAA should allow a better defined EAA library to be integrated with more robust CP databases (that can be updated with specific feed information from more routine laboratory analyses) in dairy supply-requirement models.

New roles in hemicellulosic sugar fermentation for the uncultivated Bacteroidetes family BS11.

Ruminants have co-evolved with their gastrointestinal microbial communities that digest plant materials to provide energy for the host. Some arctic and boreal ruminants have already shown to be vulnerable to dietary shifts caused by changing climate, yet we know little about the metabolic capacity of the ruminant microbiome in these animals. Here, we use meta-omics approaches to sample rumen fluid microbial communities from Alaskan moose foraging along a seasonal lignocellulose gradient. Winter diets with increased hemicellulose and lignin strongly enriched for BS11, a Bacteroidetes family lacking cultivated or genomically sampled representatives. We show that BS11 are cosmopolitan host-associated bacteria prevalent in gastrointestinal tracts of ruminants and other mammals. Metagenomic reconstruction yielded the first four BS11 genomes; phylogenetically resolving two genera within this previously taxonomically undefined family. Genome-enabled metabolic analyses uncovered multiple pathways for fermenting hemicellulose monomeric sugars to short-chain fatty acids (SCFA), metabolites vital for ruminant energy. Active hemicellulosic sugar fermentation and SCFA production was validated by shotgun proteomics and rumen metabolites, illuminating the role BS11 have in carbon transformations within the rumen. Our results also highlight the currently unknown metabolic potential residing in the rumen that may be vital for sustaining host energy in response to a changing vegetative environment.

Meta-analysis of postruminal microbial nitrogen flows in dairy cattle. II. Approaches to and implications of more mechanistic prediction.

Several attempts have been made to quantify microbial protein flow from the rumen; however, few studies have evaluated tradeoffs between empirical equations (microbial N as a function of diet composition) and more mechanistic equations (microbial N as a function of ruminal carbohydrate digestibility). Although more mechanistic approaches have been touted because they represent more of the biology and thus might behave more appropriately in extreme scenarios, their precision is difficult to evaluate. The objective of this study was to derive equations describing starch, neutral detergent fiber (NDF), and organic matter total-tract and ruminal digestibilities; use these equations as inputs to equations predicting microbial N (MicN) production; and evaluate the implications of the different calculation methods in terms of their precision and accuracy. Models were evaluated based on root estimated variance σˆe and concordance correlation coefficients (CCC). Ruminal digestibility of NDF was positively associated with DMI and concentrations of NDF and CP and was negatively associated with concentration of starch and the ratio of acid detergent fiber to NDF (CCC=0.946). Apparent ruminal starch digestibility was increased by omasal sampling (compared with duodenal sampling), was positively associated with forage NDF and starch concentrations, and was negatively associated with wet forage DMI and total dietary DMI (CCC=0.908). Models were further evaluated by calculating fit statistics from a common data set, using stochastic simulation, and extreme scenario testing. In the stochastic simulation, variance in input variables were drawn from a multi-variate random normal distribution reflective of input measurement errors and predicting MicN while accounting for the measurement errors. Extreme scenario testing evaluated each MicN model against a data subset. When compared against an identical data set, predicting MicN empirically had the lowest prediction error, though differences were slight (σˆe 23.3% vs. 23.7 or 24.3%), and highest concordance (0.52 vs. 0.48 or 0.44) of any approach. Minimal differences were observed between empirical MicN prediction (σˆe 25.3%; CCC 0.530) and MicN prediction (σˆe 25.3%; CCC 0.532) from rumen carbohydrate digestibility in the stochastic analysis or extreme scenario testing. Despite the hypothesized benefits of a more mechanistic prediction approach, few differences between the calculation approaches were identified.

Meta-analysis of postruminal microbial nitrogen flows in dairy cattle. I. Derivation of equations.

The objective was to summarize the literature and derive equations that relate the chemical composition of diet and rumen characteristics to the intestinal supply of microbial nitrogen (MicN), efficiency of microbial protein synthesis (EMPS), and flow of nonammonia nonmicrobial N (NANMN). In this study, 619 treatment means from 183 trials were assembled for dairy cattle sampled from the duodenum or omasum. Backward elimination multiple regression was used to derive equations to estimate flow of nitrogenous components over a large range of dietary conditions. An intercept shift for sample location revealed that omasal sampling estimated greater MicN flow relative to duodenal sampling, but sample location did not interact with any other variables tested. The ruminal outflow of MicN was positively associated with dry matter intake (DMI) and with dietary starch percentage at a decreasing rate (quadratic response). Also, MicN was associated with DMI and rumen-degraded starch and neutral detergent fiber (NDF). When rumen measurements were included, ruminal pH and ammonia-N were negatively related to MicN flow along with a strong positive association with ruminal isovalerate molar proportion. When evaluating these variables with EMPS, isovalerate interacted with ammonia such that the slope for EMPS with increasing isovalerate increased as ammonia-N concentration decreased. A similar equation with isobutyrate confirms the importance of branched-chain volatile fatty acids to increase growth rate and therefore assimilation of ammonia-N into microbial protein. The ruminal outflow of NANMN could be predicted by dietary NDF and crude protein percentages, which also interacted. This result is probably associated with neutral detergent insoluble N contamination of NDF in certain rumen-undegradable protein sources. Because NANMN is calculated by subtracting MicN, sample location was inversely related compared with the MicN equation, and omasal sampling underestimated NANMN relative to duodenal sampling. As in the MicN equation, sampling location did not interact with any other variables tested for NANMN. Equations derived from dietary nutrient composition are robust across dietary conditions and could be used for prediction in protein supply-requirement models. These empirical equations were supported by more mechanistic equations based on the ruminal carbohydrate degradation and ruminal variables related to dietary rumen degradable protein.

Electron transport phosphorylation in rumen butyrivibrios: unprecedented ATP yield for glucose fermentation to butyrate.

From a genomic analysis of rumen butyrivibrios (Butyrivibrio and Pseudobutyrivibrio sp.), we have re-evaluated the contribution of electron transport phosphorylation (ETP) to ATP formation in this group. This group is unique in that most (76%) genomes were predicted to possess genes for both Ech and Rnf transmembrane ion pumps. These pumps act in concert with the NifJ and Bcd-Etf to form a electrochemical potential (ΔµH(+) and ΔµNa(+)), which drives ATP synthesis by ETP. Of the 62 total butyrivibrio genomes currently available from the Hungate 1000 project, all 62 were predicted to possess NifJ, which reduces oxidized ferredoxin (Fdox) during pyruvate conversion to acetyl-CoA. All 62 possessed all subunits of Bcd-Etf, which reduces Fdox and oxidizes reduced NAD during crotonyl-CoA reduction. Additionally, 61 genomes possessed all subunits of the Rnf, which generates ΔµH(+) or ΔµNa(+) from oxidation of reduced Fd (Fdred) and reduction of oxidized NAD. Further, 47 genomes possessed all six subunits of the Ech, which generates ΔµH(+) from oxidation of Fdred. For glucose fermentation to butyrate and H2, the electrochemical potential established should drive synthesis of ∼1.5 ATP by the F0F1-ATP synthase (possessed by all 62 genomes). The total yield is ∼4.5 ATP/glucose after accounting for three ATP formed by classic substrate-level phosphorylation, and it is one the highest yields for any glucose fermentation. The yield was the same when unsaturated fatty acid bonds, not H(+), served as the electron acceptor (as during biohydrogenation). Possession of both Ech and Rnf had been previously documented in only a few sulfate-reducers, was rare in other rumen prokaryotic genomes in our analysis, and may confer an energetic advantage to rumen butyrivibrios. This unique energy conservation system might enhance the butyrivibrios' ability to overcome growth inhibition by unsaturated fatty acids, as postulated herein.

Maximizing efficiency of rumen microbial protein production.

Rumen microbes produce cellular protein inefficiently partly because they do not direct all ATP toward growth. They direct some ATP toward maintenance functions, as long-recognized, but they also direct ATP toward reserve carbohydrate synthesis and energy spilling (futile cycles that dissipate heat). Rumen microbes expend ATP by vacillating between (1) accumulation of reserve carbohydrate after feeding (during carbohydrate excess) and (2) mobilization of that carbohydrate thereafter (during carbohydrate limitation). Protozoa account for most accumulation of reserve carbohydrate, and in competition experiments, protozoa accumulated nearly 35-fold more reserve carbohydrate than bacteria. Some pure cultures of bacteria spill energy, but only recently have mixed rumen communities been recognized as capable of the same. When these communities were dosed glucose in vitro, energy spilling could account for nearly 40% of heat production. We suspect that cycling of glycogen (a major reserve carbohydrate) is a major mechanism of spilling; such cycling has already been observed in single-species cultures of protozoa and bacteria. Interconversions of short-chain fatty acids (SCFA) may also expend ATP and depress efficiency of microbial protein production. These interconversions may involve extensive cycling of intermediates, such as cycling of acetate during butyrate production in certain butyrivibrios. We speculate this cycling may expend ATP directly or indirectly. By further quantifying the impact of reserve carbohydrate accumulation, energy spilling, and SCFA interconversions on growth efficiency, we can improve prediction of microbial protein production and guide efforts to improve efficiency of microbial protein production in the rumen.

Accumulation of reserve carbohydrate by rumen protozoa and bacteria in competition for glucose.

The aim of this study was to determine if rumen protozoa could form large amounts of reserve carbohydrate compared to the amounts formed by bacteria when competing for glucose in batch cultures. We separated large protozoa and small bacteria from rumen fluid by filtration and centrifugation, recombined equal protein masses of each group into one mixture, and subsequently harvested (reseparated) these groups at intervals after glucose dosing. This method allowed us to monitor reserve carbohydrate accumulation of protozoa and bacteria individually. When mixtures were dosed with a moderate concentration of glucose (4.62 or 5 mM) (n = 2 each), protozoa accumulated large amounts of reserve carbohydrate; 58.7% (standard error of the mean [SEM], 2.2%) glucose carbon was recovered from protozoal reserve carbohydrate at time of peak reserve carbohydrate concentrations. Only 1.7% (SEM, 2.2%) was recovered in bacterial reserve carbohydrate, which was less than that for protozoa (P < 0.001). When provided a high concentration of glucose (20 mM) (n = 4 each), 24.1% (SEM, 2.2%) of glucose carbon was recovered from protozoal reserve carbohydrate, which was still higher (P = 0.001) than the 5.0% (SEM, 2.2%) glucose carbon recovered from bacterial reserve carbohydrate. Our novel competition experiments directly demonstrate that mixed protozoa can sequester sugar away from bacteria by accumulating reserve carbohydrate, giving protozoa a competitive advantage and stabilizing fermentation in the rumen. Similar experiments could be used to investigate the importance of starch sequestration.