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The objective of this study was to evaluate the effects of altering pH and solids passage rate (kp) on concentration of aqueous H2 [H2(aq)], CH4 production, volatile fatty acids (VFA) production, and fiber digestibility in a continuous culture fermentation system. The present study was conducted as a 2 × 2 factorial treatment arrangement in a Latin square design using continuous culture fermentors (n = 4). Our continuous culture system was converted to a closed system to measure CH4 and H2 emission while measuring H2(aq) concentration and VFA production for complete stoichiometric assessment of fermentation pattern. Treatments were control pH (CpH; ranging from 6.3 to 6.9) or low pH (LpH; 5.8 to 6.4) factorialized with solids kp that was adjusted to be either low (Lkp; 2.5%/h) or high (Hkp; 5.0%/h); liquid dilution was maintained at 7.0%/h. Fermentors were fed once daily (40 g of dry matter; 50:50 concentrate:forage diet). Four periods lasted 10 d each, with 3 d of sample collection. The main effect of LpH increased nonammonia nitrogen flow, and both LpH and Hkp increased nonammonia nonbacterial N flow. We observed a tendency for Hkp to increase bacterial N flow per unit of nonstructural carbohydrates and neutral detergent fiber degraded. The main effect of LpH decreased H2(aq) by 4.33 µM compared with CpH. The main effect of LpH decreased CH4 production rate from 5 to 9 h postfeeding, and Hkp decreased CH4 production rate from 3 to 9 h postfeeding. We found no effect of LpH on daily CH4 production or CH4 produced per gram of neutral detergent fiber degraded, but Hkp decreased daily CH4 production by 33.2%. Both the main effects of LpH and Hkp decreased acetate molar percentage compared with CpH and Lkp, respectively. The main effect of both LpH and Hkp increased propionate molar percentage, decreasing acetate-to-propionate ratio from 2.62 to 2.34. We noted no treatment effects on butyrate molar percentage or total VFA production. The results indicate increasing kp and decreasing pH decreased acetate-to-propionate ratio, but only increasing kp decreased CH4 production; lack of differences for LpH might be a result of compensatory methanogenesis during the second half of the day postfeeding.
Greenhouse gases originating from livestock production are a target of environmental emissions mitigation strategies, but estimates of the contribution of enteric CH4 to global or national emissions vary based on assumptions inherent in the estimate approach (
reported estimates of enteric CH4 representing 17% of global CH4 emissions. Enteric fermentation in dairy cattle is estimated to contribute approximately 3.9% of total anthropogenic CH4 emissions in the United States (
expanded our perspective on the relationship between physiological changes instigated by dietary or feed additive treatment and their effect on the concentration of aqueous H2 [H2(aq)], shifting fermentation pathways. Increasing H2(aq) concentration was hypothesized to be required to maintain methanogen growth rates with increasing solids passage rate (kp) based on steady-state microbial growth kinetics (
proposed that H2(aq) would also increase under these conditions because methanogens will lower their relative growth rate under current conditions given a decreased maximum growth rate (
). Rather than assuming that decreased relative growth rate will simply decrease competitive assimilation of H2(aq) into methanogenesis and allow H2(aq) to increase, the kinetic model hypothesizes that low pH decreases the maximal growth rate, which will shift upward the H2(aq) concentration needed to maintain relative growth rates. Increased concentrations of H2(aq) from either increased kp or lowered pH were predicted to thermodynamically shift VFA production toward pathways that decrease net microbial production of H2, particularly the acetate pathways that would otherwise yield the most H2 (
). Decreasing total H2 produced would then ultimately decrease total CH4 production.
We proposed to use continuous culture fermentors as a model to measure concentration of H2(aq), CH4 production, VFA production, and fiber digestibility as a screening and validation process for the model by
. We hypothesized that lower culture pH would inhibit methanogens, necessitating an increase in concentration of H2(aq), decreasing production of H2 and CH4, and shifting VFA pathways toward a lower acetate-to-propionate ratio. Alternatively, increased solids kp would increase methanogen relative growth rate (
) and increase the concentration of H2(aq), thereby decreasing CH4 production and again shifting VFA production pathways toward a lower acetate-to-propionate ratio. Because kp and pH are presumed to affect methanogens via modes of action based on distinct growth or microbial activity inhibitions, we hypothesized that the combination of low pH and high kp would not be additive (i.e., we would detect a significant statistical interaction).
MATERIALS AND METHODS
Experimental Design
The present study was conducted as a 2 × 2 factorial treatment arrangement in a Latin square design using dual-flow continuous culture fermentors (n = 4). Fermentors were fed once daily [40 g of DM; 50:50 concentrate:forage diet, 37.5% NDF, 19.5% NSC (starch plus water-soluble carbohydrate), and 15.4% CP]. The pelleted forage was an alfalfa meal pellet and the pelleted concentrate was composed of ground corn (36.9%), soybean hulls (40.4%), dried distiller's grains (10.0%), 48% CP soybean meal (9.1%), corn oil (1.8%), MgO (0.2%), and trace-mineralized salt (0.9%). The latter contained Na (36.6%), Cl (56.4%), Zn (3500 mg/kg), Mn (2,800 mg/kg), Fe (1,750 mg/kg), Cu (350 mg/kg), I (70 mg/kg), and Co (70 mg/kg). The buffer also contained minerals that would support optimal microbial function. Treatments were control pH (CpH; diurnally ranging from 6.3 to 6.9) or low pH (LpH; 5.8 to 6.4) factorialized with solids kp adjusted to be either low (Lkp; 2.5%/h) or high (Hkp; 5.0%/h). Liquid dilution was maintained at 7.0%/h to maintain constant infusion of buffer (for more accurate control of pH treatments) and to avoid a confounding dilution factor in H2(aq) expectations. Four experimental periods lasted 10 d each, with 3 d of sample collection at the end of each period. Buffer pH for CpH treatments was made according to
, with the addition of 0.4 g/L of urea, and determined to be constant at pH 6.8 under continuous bubbling with CO2. For the LpH treatment, we added H3PO4 to a concentration of 12.5 mM to decrease buffer pH to 6.4. Both buffers allowed a parallel diurnal shift in pH (see Supplemental Figure S1; https://doi.org/10.3168/jds.2016-12332) to better reflect normal rumen function in vivo postfeeding (
). The CpH treatment allowed fluctuation of fermentor pH from 6.9 prefeeding to 6.3 approximately 8 h postfeeding, with a gradual return over the remaining 16 h of each experimental day. In a parallel response, the LpH treatment fluctuated between 6.4 prefeeding and 5.8 postfeeding. The fermentor pH was not allowed to drop below 5.8 to prevent long-term effects on protozoa (
Investigating unsaturated fat, monensin, or bromoethanesulfonate in continuous cultures retaining ruminal protozoa. I. Fermentation, biohydrogenation, and microbial protein synthesis.
, were used for this experiment. Average fermentor volume was 1.71 L (range: ± 0.09 L), and total buffer dilution rate was maintained at 7.0%/h. At the beginning of each period, rumen contents were manually sampled from 2 ruminally cannulated lactating Jersey cows fed a lactating diet, rapidly squeezed through 2 layers of cheesecloth, and then liquid was placed in insulated containers maintained at 39°C. Samples were pooled and inoculated into fermentors at 50% of fermentor volume. Sampling to inoculation interval averaged 30 min and did not exceed 40 min. Clarified rumen fluid (centrifuged at 15,000 × g, 4°C, 15 min, and autoclaved) was used in a 1:20 dilution of buffer for the first 3 d of each period to better adapt protozoa to fermentors; in addition, filters retained protozoa except for efflux with the solids as described previously (
Investigating unsaturated fat, monensin, or bromoethanesulfonate in continuous cultures retaining ruminal protozoa. I. Fermentation, biohydrogenation, and microbial protein synthesis.
; 40 mg/dL of urea was included to prevent depression of microbial protein synthesis because fermentors also remove the effect of N recycling observed in vivo. Buffer was continuously bubbled with CO2 for at least 1 d before use to maintain anaerobic conditions in the fermentors. Treatments were imposed after 2 d of adaptation to the fermentors following each experimental period's inoculation.
Filters were replaced if clogged, typically in the first 4 d of each period while fibrous particulate content approached a semi-steady state dictated by once daily feeding. At the exit of the filtrate line from the lid of the fermentor, a y-shaped septum was attached to allow filtrate samples to be taken as liquid effluent was pumped from the fermentor. Fermentors were tested daily for pressure leaks using the Micro-Oxymax detection system (Columbus Instruments Inc., Columbus, OH). Detected leaks were repaired primarily during the adaptation period, and no samples were taken on days when repairs were made. Therefore, gas production measurement occurred during the last 3 d of each period, and the diurnal response was uninterrupted for any day recorded and used in data analysis. Ammonium sulfate that was enriched with 10% 15N was dosed in a priming dose on d 5 at 50 mg and added to the buffer at 25 mg/L for a desired enrichment of 0.2% atom excess. Experimental periods lasted 10 d, including 7 d of adaptation and 3 d of sample collection.
Sample Collection and Analysis
Daily Samples
Daily fermentor effluent was collected over 24 h postfeeding in outflow containers on ice. A 20% subsample of daily effluent by weight was aspirated with a 63.5-mm diameter tube, to prevent sampling bias against larger particles, and pooled by fermentor within period. Effluent subsamples were lyophilized and stored for various analyses at −20°C until the end of the experiment. A subsample of lyophilized effluent was dried at 105°C overnight to determine DM, then ashed at 550°C overnight to determine OM (
) to determine NAN flow by subtraction. Because of the small particle size of effluent inherent in continuous culture fermentors, NDF was determined by reflux units similar to those described by
). A 2-g subsample of all dried effluent and diet was commercially analyzed for starch and water-soluble carbohydrates, the sum of which is NSC (Dairy One Forage Lab, Ithaca, NY). A 50-mL aliquot of daily effluent was acidified with 3 mL of 6 N HCl before compositing by fermentor within period and storage at −20°C. Samples were later thawed, centrifuged (15,000 × g, 4°C, 15 min), and filtered through Whatman No. 1 filter paper (Whatman International, Maidstone, UK) for analysis of NH3-N (
). A 10-mL aliquot of effluent and a 20-mL aliquot of agitated fermentor contents were taken and fixed in equal volume of 50% formalin for protozoal counts using the method of
Headspace gas was collected using a Micro-Oxymax gas analyzer (Columbus Instruments Inc.). Gas production was calculated by pressure and programmed relationships according to gas laws embedded in the Micro-Oxymax system. The instrument sampled CH4 and CO2 by infrared absorption, but CO2 evolving from buffer limits the application of this measurement and also further dilutes H2. Therefore, H2 gas was determined by electrochemical sensor within the Micro-Oxymax system after the CO2 had been scrubbed by passing it through a soda lime column (GFS Chemicals, Columbus, OH) that was replaced daily. The gas sensor was calibrated at the start of each experimental period to account for sensor baseline drift, which never exceeded 0.05% CH4. Fermentors were vented every 30 min, and gas production rates were calculated for CH4 and H2 and cumulative gas recorded per day.
Using the y-valve septum mentioned previously, 10 mL of filtrate was removed from the fermentors at 0, 1, 2, 3, 4, 6, and 8 h postfeeding on d 8, 9, and 10. Samples were acidified with 1 mL of 6 N HCl, pooled by fermentor within period, and analyzed for VFA by GLC (
). At the same time points (0, 1, 2, 3, 4, 6, and 8 h postfeeding) plus an additional 24-h sample on d 8, 9, and 10, we removed 20 mL of filtrate via the septum and injected filtrate into a 60-mL glass culture bottle (Wheaton Glass, Millville, NJ) containing 5 mL of 5 M H3PO4, previously flushed with N2, and sealed with a butyl rubber stopper. To maintain fermentor volume, an equivalent volume of buffer was replaced at each time point to control kp. The 25-mL sample of fermentor filtrate and H3PO4 was inverted and stored at 4°C until the end of the experiment (no more than 3 d) to quantify H2(aq).
The H2(aq) was measured based on a procedure similar to that of
), such as with our slow stirring procedure used to retain protozoa. Supersaturation has previously influenced thermodynamic assumptions based on headspace derivations for measured H2(aq) and aqueous CH4 (
). At the end of the experiment, the sample of filtrate combined with H3PO4 in the culture bottle was over-pressurized with 50 mL of N2 and shaken to enable equilibrium, after which a 50-mL headspace sample was removed and injected directly into the H2 sensor of the Micro-Oxymax gas analyzer to derive H2(aq) as follows. Output was in percent gas as a total of injection and was used in an equation combining Henry's Law coefficient for H2, conservation of mass, and standard gas laws to estimate moles of H2(aq) originally in the liquid filtrate sample {n[H2(aq)]initial}. The equation used was:
[1]
where Vg is the volume (L) of the gas phase (bottle headspace),
is the volume (L) of N2 injected into the headspace of the bottle, KH(H2) is the Henry's law constant for H2 (1,211.63 bar L mol−1), R is the gas constant (0.08314 L bar K−1 mol−1; where bar = 100 kPa), T is the temperature (298.15°K), and Vl is the volume (L) of the liquid phase (filtrate and acid). We calculated KH(H2) at pH = 7, ionic strength = 0.25 M, and T = 298.15°K according to
Daily effluent data and 15N enrichment data were analyzed using the MIXED (mixed model) procedure of SAS 9.4 (SAS Institute, Inc., Cary, NC) according to the following model:
where Yijkl is the dependent variable, µ is the overall population mean, Hi is the fixed effect of ith pH treatment (i = control, low), Kj is the fixed effect of jth kp (j = high, low), (H × K)ij is the interaction of pH and kp, pk is the random effect of kth period (k = 1, 2, 3, 4), fl is the random effect of lth fermentor (l = 1, 2, 3, 4), and εijkl is the residual error, assumed independent and
For daily CH4 production, the random effect of mth day (m = 1, 2, 3) was added to the model to account for large daily variations in CH4 production between days. Hourly data were analyzed using the REPEATED (repeated measures) statement added to the previous model. The AR(1) covariate structure was selected for all measured variables based on best fit using the lowest Bayesian information criterion. When a treatment × time interaction was significant, the effect of treatment was contrasted over time. A priori determination to test treatment effects by hour led us to use contrast statements for the main effect of pH, kp, or pH × kp for each time point.
RESULTS AND DISCUSSION
Controlling Fermentor pH
The pH in all 4 fermentors followed a diurnal range following feeding that consisted of a decline of 0.6 units over the first 8 h postfeeding followed by a gradual rise back to the maximum target range: for the CpH treatments, this range was 6.9 to 6.3; for the LpH treatments, this range was 6.4 to 5.8. The pH never exceeded this range during an experimental period. A primary limitation in traditional continuous culture fermentor experiments is the reliability of pH control. Total time at low pH (area under the curve) is a significant driver of pH effects in experiments (
), and pH control at intervals allows closer determination of physiological limits of continuous culture to low pH before sacrificing digestibility. However, magnitude of pH decline is also an important factor (
attempted to account for this by dropping pH stepwise for 4-h increments, but we reasoned that repeated abrupt stepwise pH adjustments can shock the microbial population and could shift microbial populations more than a gradual pH change. Monitoring daily pH just before feeding (
) can be fairly predictive of fermentor pH throughout the day on a constant diet after the first 4 d of adaptation, allowing a diurnal shift in pH that is likely more reflective of ruminant biology (
Fermentor counts of protozoa were decreased (P = 0.03) in our experiment by the main effect of LpH, but not by kp or the interaction (P > 0.10) (Table 1). Protozoa counts in the present study are lower than the range reported in vivo (∼1 × 106;
Investigating unsaturated fat, monensin, or bromoethanesulfonate in continuous cultures retaining ruminal protozoa. I. Fermentation, biohydrogenation, and microbial protein synthesis.
), so part of the reason for the lower counts is a result of lower DM (substrate) concentration. Additionally, generation times of protozoa in excess of 20 or 40 h for Hkp or Lkp, respectively, are indicative of protozoal sequestration on the bottom of fermentors to avoid outflow because we expected generation times to align with kp (
). The shorter generation time with LpH could reflect a differentially greater inhibition of the sedimenting protozoa, especially those of the family Isotrichidae; however, another explanation seems more likely. All generation times in our study are still above the minima summarized for various entodiniomorphid protozoa (
); thus, recovery after the nadir pH of 5.8 might have prevented a shift in populations resulting from the different kp. We detected a relatively low number of cells in all treatments and a prevalence of primarily small (<50 µm length) Entodinium spp. (data not shown); therefore, only total cell counts (not differentiated by genera) were recorded. Considering that members of genus Entodinium are more resistant to inhibition by low pH (
), the decrease (P = 0.03) in mean protozoal counts in fermentors by LpH in the present study combined with no difference in outflow of protozoal cells into the effluent might reflect a greater proportion of smaller protozoa that have a shorter (P = 0.06) generation time.
Table 1Counts of protozoa populations within fermentors, calculated effluent flow, and generation time for continuous cultures treated with control or low pH and either low or high solids passage rate (kp)
Apparent NSC digestibility was high (average = 88.4%), but we found no effect of treatments or interaction (P > 0.10), and NSC digestibility is consistently high in continuous culture fermentation systems (
). High NSC digestibility likely resulted from pelleted diets that sink to the bottom of the fermentor, increasing digestion time before fermentation buoyancy floats particles to potential outflow; however, pelleting is necessary to ensure correct diet delivery and prevent excessive overflow.
Apparent OM digestibility was not affected by kp or the interaction of pH × kp (P > 0.10), yet the main effect of LpH tended (P = 0.07) to have greater OM digestibility compared with the main effect mean for CpH (Table 2). Despite the lack of treatment effects on NSC digestibility, LpH unexpectedly increased apparent OM digestibility without affecting the more pH-sensitive metric, NDF digestibility (
) because we established a minimum pH of 5.8 to protect protozoa.
Table 2Nutrient digestibilities and N effluent flows in continuous cultures that were treated with either control or low pH and either low or high solids passage rate (kp)
Digestibility of NDF did not differ by treatments (P > 0.10), which is surprising given a previously dramatic effect of increased kp on NDF digestibility in our laboratory (
). That study and most published literature had a much faster stirring rate, which would increase overflow of particles by disrupting digesta at the bottom of the fermentors, but also almost completely eliminates protozoa (
, who noted that treatment of 4 h at suboptimal pH (<6.3) decreased NDF digestibility. The effect of low pH (<6.0) on cellulolytic bacteria probably is related to growth inhibition rather than activity of cellulase per se (
), and therefore daily CH4 production need not change. Based on the VFA and CH4 concentration patterns reported in the present study (Table 3), we suggest that microorganisms inhibited during the first 4 to 8 h postfeeding by LpH were able to compensate in the last 16 h to overcome differences in digestibility, VFA, and CH4 that occurred in the earlier hours. Future methane mitigation strategies must consider not only the capability of microbes to adapt to treatments, but also to compensate for short-term changes.
Table 3Effluent flow, VFA and methane production, and dihydrogen (H2) emission into headspace or aqueous (aq) concentration for continuous cultures that were treated with either control or low pH and either low or high solids passage rate (kp)
Concentration of NH3-N in daily effluent (average = 17.5 mg/dL) was not affected by treatment or interaction (P > 0.10) (Table 2). However, LpH increased (P < 0.01) total N flow and tended (P = 0.08) to increase bacterial N flow per kilogram of OM degraded, with no effect of kp or the interaction of pH × kp (P > 0.10). Bacterial N flow was not affected by pH or the interaction of pH × kp (P > 0.10), but the main effect mean of Hkp trended (P = 0.09) toward an increase compared with the main effect mean of Lkp (Table 2). This is congruent with the hypothesis of
, that increased kp would increase microbial growth rate in response, and is supported by previous reviews that predicted increased kp should improve the efficiency of microbial protein synthesis (
). The main effect of Hkp tended (P < 0.10) to increase grams of bacterial N per kilogram of OM, NSC, or NDF degraded compared with the main effect mean of Lkp (Table 2).
The main effect of LpH increased (P = 0.03) NAN flow and NAN flow as a percentage of N intake, with no effects (P > 0.10) of kp or the interaction of pH × kp. Because of the removal of protozoa before 15N analysis, nonammonia, nonmicrobial N is termed nonammonia, nonbacterial N (NANBN) in the present study. The main effect of LpH increased (P < 0.01) NANBN flow and NANBN flow as a percentage of N intake, and the main effect of Hkp also increased (P = 0.04) NANBN flow and flow as a percentage of N intake. We found no interaction of pH × kp (P > 0.10). The main effect of LpH shifted N flow in the current experiment, increasing both NAN and NANBN flows when calculated directly or as percentages of N intake. The increase in NANBN flow by LpH in the present study is similar to that reported previously by
Unfortunately, protozoal N could not be measured because small contaminating particles could not be removed by separation of the protozoal fraction based on centrifugation or filtration. Using the estimate of 5.46 × 10−10 g of N/cell (
), protozoal N can be estimated at approximately 1.3% of total microbial N, but this estimate depends on cell size and potential for treatment differences. Fermentation activity inside small particles in continuous culture is not rapid enough for typical flocculation to separate protozoa; without flocculation, small feed particles that are contaminated with adherent bacterial N are similar in size and density to protozoal cells and are not removed during harvesting of protozoa (
Examining the effects of adding fat, ionophores, essential oils, and Megasphaera elsdinii on ruminal fermentation with methods in vitro and in vivo. The Ohio State University,
Columbus2013
Examining the effects of adding fat, ionophores, essential oils, and Megasphaera elsdinii on ruminal fermentation with methods in vitro and in vivo. The Ohio State University,
Columbus2013
, which used sonication and boiling to destroy protozoa and subtracted lysed protozoal N from a control sample containing both protozoal N and contaminating feed N, was also insufficient to determine N with acceptably low error.
VFA
We noted no interactions (P > 0.10) of pH × kp for total VFA production or molar percentage of individual VFA (Table 3). Total concentration of VFA measured in daily effluent was not affected by pH or kp, nor was net production of VFA (calculated by effluent VFA concentration × effluent outflow per day). However, the molar percentage of acetate was decreased (P < 0.01) by lowering pH and decreased (P < 0.01) by increasing kp. The lower acetate was mirrored by a higher (P < 0.05) propionate molar percentage for main effects means of both LpH and Hkp when compared with main effect means for CpH and Lkp, respectively. We observed no treatment effects (P > 0.10) on isobutyrate or butyrate. The main effect of LpH increased (P < 0.05) both isovalerate and valerate, with no effect of Hkp (P > 0.10, Table 3). The acetate-to-propionate ratio was decreased by both the main effect of LpH and Hkp (P < 0.01). Increased isovalerate might be a result of decreased iso long-chain fatty acid synthesis into bacterial membranes with decreasing pH (
). This effect cannot be verified because, under our GLC conditions, isovalerate coelutes with 2-methylbutyrate (the primer for anteiso long-chain fatty acids); isovalerate production should not have increased from leucine deamination because LpH also increased NANBN (an index of undegraded dietary protein; Table 2).
When time had a main effect difference or an interaction with treatment, the VFA were presented over time (Figure 1). Hourly measurements indicated that VFA total concentration was increased by LpH (P < 0.05) for 1 to 4 h postfeeding (Figure 1A). Although we noted a pH × time interaction (P < 0.05) for molar percentage of acetate (Figure 1B), acetate was consistently decreased by the main effects of LpH (P < 0.01) at every time point compared with CpH, reflecting the main effect differences (Table 3). For molar percentage of propionate, we observed interactions with time for both the pH (P = 0.09) and the kp (P = 0.02) treatments (Figure 1C). Respective differences for both main effects (P < 0.01) were in the first 8 h after feeding. Butyrate molar percentage (Figure 1D) had a main effect of time (P < 0.01) and an interaction of pH × time (P < 0.01). The main effect of LpH was lower (P < 0.05) from 3 to 8 h postfeeding compared with the main effect of CpH, again confirming most of the responses before 8 h.
Figure 1Total concentration or molar percentages of VFA over time postfeeding for continuous cultures that had treatments of either control (CpH) or low (LpH) pH and either low (Lkp) or high (Hkp) solids passage rate (kp). We found no pH × kp × time interactions (P > 0.10), but interactions of pH and kp are noted when P ≤ 0.10. The main effects and interactions of treatments were tested at each time point and are reported when they were P ≤ 0.10. (A) Total VFA concentration had the main effect of time (P < 0.01). Total VFA tended (P = 0.07) to be increased for the main effect of LpH at 0 h and was increased (P ≤ 0.05) from 1 to 4 h postfeeding compared with the main effect of CpH. High kp tended (P = 0.07) to decrease total VFA at 4 h postfeeding. Pooled standard error was 2.75 mM. (B) Acetate molar percentage had a pH × time interaction (P = 0.02). The main effect of LpH decreased (P ≤ 0.05) acetate molar percentage for all time points compared with the main effect of CpH. Pooled standard error was 1.22 mol/100 mol. (C) Molar percentage of propionate had main effects of time (P = 0.02), and we found interactions for pH × time (P = 0.09) and kp × time (P = 0.02). The main effect of LpH was greater (P < 0.01) from 1 to 8 h postfeeding compared with the main effect of CpH. The main effect of Hkp was greater (P < 0.01) from 0 to 8 h postfeeding compared with Lkp. Pooled standard error was 1.14 mol/100 mol. (D) Molar percentage of butyrate had a main effect of time (P < 0.01) and an interaction of pH × time (P < 0.01). The main effect of LpH was lower (P < 0.05) from 3 to 8 h postfeeding compared with the main effect of CpH. Pooled standard error was 0.499 mol/100 mol.
); however, their low pH treatment was much lower than the diurnal average of the present study. Most importantly, the effect of pH has changed fermentation conditions independent of changes in diet (
), but these studies have previously been performed using immediate changes to the fermentor pH rather than the gradual shift in pH implemented in the present study. In the present study, acetate-to-propionate ratio was decreased by LpH and also by Hkp. This shifted ratio was observed throughout the first 8 h postfeeding, indicating potential for microbial adaptation as the root cause rather than an increase in concentration of H2(aq) (
), in contrast to the present study. However, values in that study represent unusually high acetate-to-propionate ratio for a continuous culture experiment, perhaps because of its constant feeding. The response of total VFA concentration and acetate-to-propionate ratio possibly is not linear across a wider variation in kp, as in other previous work in single-flow fermentors (
). Despite the shift in acetate-to-propionate ratio in the present study, we found no change in total VFA production; thus, more carbon and hydrogen were incorporated into VFA as acetate production decreased and propionate production increased.
The ideal ratio of acetate-to-propionate ratio for milk production or ruminal fermentative efficiency is not known (
). We must be careful not to interpret shifts in acetate-to-propionate ratio as indicative of greater or lesser fermentative efficiency, but only as a descriptive variable for the VFA pathway balance in the culture measured. After our study was conducted, a theoretical publication provided evidence that VFA may not be shifted by thermodynamic control under normal rumen conditions (
). Further, VFA absorption in vivo complicates potential thermodynamic feedback that was not accounted for in the current experiment.
Aqueous Hydrogen
Concentration of H2(aq) (average for all time points and treatments = 4.11 µM) had an interaction (pH × kp, P = 0.02) at 1 h postfeeding: CpH/Lkp was greatest, followed by CpH/Hkp and LpH/Hkp, and LpH/Lkp was lowest (Figure 2A). Over all time points, the main effect of LpH decreased (P < 0.01) H2(aq) by 4.33 µM compared with CpH. Although not the hypothesized result, the decreased acetate-to-propionate ratio (and therefore H2 production) might have limited accumulation of H2(aq) because methanogens readily consumed available substrate. Our hypothesized role of H2(aq) was unlikely to shift VFA production in the LpH treatments because concentration of H2(aq) was actually decreased by LpH (Figure 2A). The decrease in CH4 production by LpH might not have been mediated by H2(aq) via LpH in the present study because the concentration never shifted enough (>10 µM) to see the dramatic pathway shifts proposed by
Figure 2Emission of dihydrogen (H2) or aqueous (aq) concentration and emission (production) of methane (CH4) over time postfeeding for continuous cultures that had treatments of either control (CpH) or low (LpH) pH and either low (Lkp) or high (Hkp) solids passage rate (kp). We found no pH × kp × time interactions (P > 0.10), but interactions of pH and kp are noted when P ≤ 0.10. The main effects and interactions of treatments were tested at each time point and are reported when they were P ≤ 0.10. (A) For H2(aq), we found an interaction of pH × kp (P = 0.02) at 1 h postfeeding with CpH/Lkp being greatest, CpH/Hkp and LpH/Hkp being intermediate, and LpH/Lkp being least. We also noted a trend (P = 0.08) for LpH to be lower at 2 h than CpH. Pooled standard error was 3.68 μM. (B) For H2 emission, we found a main effect of time (P < 0.01) and a pH × time interaction (P < 0.01). The main effect of LpH was lower than CpH from 2 to 8 h (P < 0.05) and 9 h (P = 0.06) postfeeding. Pooled standard error was 13.8 μmol/h. (C) For CH4 production rate, we observed a main effect of time (P < 0.01). The main effect of LpH was lower (P < 0.05) from 5 to 9 h postfeeding compared with the main effect of CpH. The main effect of Hkp was lower (P < 0.05) from 3 to 9 h compared with the main effect of Lkp. Pooled standard error was 326 μmol/h.
and represents biological variation in addition to experimental error. Measurement of concentrations of H2(aq) in excess of equilibrium predictions accentuates the necessity of measuring H2(aq) rather than the simpler headspace H2 or calculations for H2(aq) derived from headspace H2 because of supersaturation (
). Although only different at 1 h postfeeding, the H2(aq) landscape probably is more dynamic than the current sampling points allowed us to measure. The production of H2 probably occurred more rapidly than it could be consumed by methanogens or other bacteria, which is supported by in vitro results from
Shifts in rumen fermentation and microbiota are associated with dissolved ruminal hydrogen concentrations in lactating dairy cows fed different types of carbohydrates.
). Headspace gas merely represents H2 escape; once escaped, H2 models predict a relatively low proportion of gaseous H2 returning to H2(aq) for contribution to methanogenesis within the rumen fluid culture unless methanogenesis has been interrupted by an inhibitor (
) and is expected in our slow-stirring fermentors especially during its peak production; during these times when H2 is accumulating in the headspace, we expect limited redissolving into liquid before it is vented by our gas collection system. Eructation and absorption of H2 into blood for expiration also would remove gaseous H2 in vivo.
Gas Production
We found no interactions (P > 0.10) of pH × kp for H2 production. Hydrogen escape into headspace gas was decreased (P < 0.05) by LpH for 2 to 8 h postfeeding, and we observed no effect of kp (P > 0.10, Figure 2B). This result is similar to the decrease in H2(aq) caused by LpH treatment. The rate of H2 escape into headspace probably was not decreased by lower culture pH; if this were true, H2(aq) measurements—from which H2 is equilibrated for a standard sample pH across all treatments—would have increased detected quantities of H2(aq). More likely, the lower H2(aq) in LpH could be due to H2 diversion away from escape resulting from reducing equivalent disposal into increasing chain length of fermentation end-products, such as valerate (as noted in Table 3), with more negative redox potential of bacteria if methanogenesis is disrupted (
Methane production rate was decreased by the main effect of LpH (P ≤ 0.05) for 5 to 9 h postfeeding and was also decreased by the main effect of Hkp (P ≤ 0.05) for 3 to 9 h post-feeding (Figure 2C). With trends (P ≤ 0.10) to decrease CH4 production rate for both LpH and Hkp at 10 h, CH4 production rates were not different (P > 0.10) from 11 to 24 h postfeeding. In the present study, methanogenesis did occur below pH 6.0, which is contrary to that previously reported after abrupt treatments (
). However, CH4 production rate was decreased by both LpH and Hkp during the time of most active fermentation postfeeding. In combination with observed shifts in the current study of VFA production toward a lower acetate-to-propionate ratio, decreased CH4 production rate would support the hypothesis by
, that increased H2(aq) shifts VFA production away from H2-producing pathways. This may be accomplished by redirecting pyruvate toward propionate or by disposal of reducing equivalents when acetyl coA is elongated to butyrate and valerate (
The role of thermodynamics in the control of ruminal fermentation.
in: Sejrsen K. Hvelplund T. Nielsen M.O. Pages 55–86 in Ruminant Physiology: Digestion, Metabolism and Impact of Nutrition on Gene Expression, Immunology and Stress. Wageningen Academic Publishers,
Wageningen, the Netherlands2006
). In support, valerate increased when LpH suppressed methanogenesis (Table 3); however, the H2 emission and H2(aq) themselves did not respond as hypothesized according to
The net result on a daily basis from minor hourly differences for CH4 production rates between treatments was no effect of LpH or interaction of pH × kp (P > 0.10) for daily CH4 production (Table 3); however, Hkp decreased daily CH4 production (P < 0.01) by 13.3 mmol/d. When considering millimoles of CH4 produced per gram of NDF degraded, we found no effect of treatment (P > 0.10, Table 3). Although the daily CH4 production was not significant for LpH, the shift in the present study in CH4 production rate and VFA ratio was accomplished without any change in the diet fed. Furthermore, the mitigation of CH4 by increased kp without decreases in NDF digestibility or changes in dietary composition support the hypothesis by
, whereby increased methanogen growth rate and requirement for substrate (H2) at an increased growth rate would increase H2(aq) concentration and decrease net methanogenesis by decreasing H2-producing VFA pathways.
CONCLUSIONS
We aimed to determine whether decreased pH or increased kp would increase H2(aq), shifting VFA pathways away from acetate production and decreasing net H2 production available for methanogenesis. Although we did not observe the hypothesized increase of H2(aq), CH4 production rate was decreased during early fermentation by both LpH and Hkp, in support of the hypothesis of
. However, the thermodynamic control by H2(aq) might be less influential in standard dietary conditions for dairy cattle. The decrease in CH4 produced with increased kp without a decline in NDF digestibility provides strong in vitro evidence that methanogenesis can be mitigated by changing conditions influencing archaeal growth rate. Responses in VFA production, primarily a decline in acetate-to-propionate ratio, were also observed independent of any dietary changes. Increasing kp also tended to increase grams of bacterial N per kilogram of NSC and NDF degraded. The microbial community appears to be dynamically adaptive, such that VFA production shifted in response to inhibition of methanogenesis inhibition, yet detection of biologically significant differences in H2(aq) eluded us due to limited time points measured and high variability in its measurement. Although challenging, H2(aq) can be measured experimentally and offers valuable information for future modeling of the relationship between VFA production and methanogenesis.
ACKNOWLEDGMENTS
Research was jointly supported by state and federal funds appropriated to the Ohio Agricultural Research and Development Center, The Ohio State University. Funds were provided by the USDA National Institute of Food and Agriculture award 2012-67015-19437. Manuscript number 15/17AS.
Investigating unsaturated fat, monensin, or bromoethanesulfonate in continuous cultures retaining ruminal protozoa. I. Fermentation, biohydrogenation, and microbial protein synthesis.
The role of thermodynamics in the control of ruminal fermentation.
in: Sejrsen K. Hvelplund T. Nielsen M.O. Pages 55–86 in Ruminant Physiology: Digestion, Metabolism and Impact of Nutrition on Gene Expression, Immunology and Stress. Wageningen Academic Publishers,
Wageningen, the Netherlands2006
Shifts in rumen fermentation and microbiota are associated with dissolved ruminal hydrogen concentrations in lactating dairy cows fed different types of carbohydrates.
Examining the effects of adding fat, ionophores, essential oils, and Megasphaera elsdinii on ruminal fermentation with methods in vitro and in vivo. The Ohio State University,
Columbus2013 (PhD thesis)
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