Effects of dietary rumen-protected choline supplementation to periparturient dairy cattle on inflammation, metabolism, and performance during an intramammary lipopolysaccharide challenge

Recent studies have suggested that dietary rumen-protected choline (RPC) supplementation can modulate immune function, attenuate inflammation, and improve performance in periparturient dairy cattle; however, this has yet to be evaluated during a mastitis challenge. Therefore, the objective of this study was to examine the effects of supplementation and dose of RPC on metabolism, inflammation, and performance during an intramammary lipopolysaccharide (LPS) challenge. Parous Holstein cows (parity, mean ± SD, 1.9 ± 1.1 at enrollment) were blocked by calving month and randomly assigned within block to receive either 45 g/d of RPC (20.4 g/d of choline ions; CHOL45, n = 18), 30 g/d of RPC (13.6 g/d of choline ions; CHOL30, n = 21), or no RPC (CON, n = 19) as a top-dress starting 24 d before expected calving until 21 d postpartum. Cows were alternately assigned within treatment group to either receive an intramammary LPS challenge (200 μg in each rear quarter; Escherichia coli O111:B4) or not at 17 DIM. Before the challenge, CHOL45 and CHOL30 cows produced 3.4 and 3.8 (±1.2 SED) kg/d more milk than CON, respectively. Dietary RPC supplementation did not mitigate the milk loss associated with the intramammary LPS challenge; however, CHOL45 and CHOL30 cows produced 3.1 and 3.5 (±1.4 SED) kg/d more milk than CON, respectively in the carryover period (22 to 84 DIM). Dietary RPC supplementation enhanced plasma β-hydroxybutyrate (BHB) concentrations before the LPS challenge, and increased plasma nonesterified fatty acids (NEFA) and acetylcarnitine concentrations during the LPS challenge, potentially reflecting greater adipose tissue mobilization, fatty acid transport and oxidation. Aside from trimethylamine N -oxide and sarcosine, which were increased in CHOL45-LPS as compared with CON-LPS, most other choline metabolite concentrations in plasma were unaffected by treat-ment, likely because more choline was being secreted in milk. Plasma lactic acid concentrations were decreased in CHOL45-LPS and CHOL30-LPS as compared with CON-LPS, suggesting a reduction in glycolysis or an enhancement in the flux through the lactic acid cycle to support gluconeogenesis. Plasma concentrations of fumaric acid, a byproduct of AA catabolism and the urea cycle, were increased in both choline groups as compared with CON-LPS during the LPS challenge. Cows in the CHOL45 group had greater plasma anti-oxidant potential before the LPS challenge and reduced plasma methionine sulfoxide concentrations during the LPS challenge compared with CON-LPS, suggesting an improvement in oxidant status. Nevertheless, concentrations of inflammatory markers such as haptoglobin and tumor necrosis factor α (TNFα) were not affected by treatment. Taken together, our data suggest that the effects of dietary RPC supplementation on milk yield could be mediated through metabolic pathways and are unlikely to be related to the resolution of inflammation in periparturient dairy cattle. Lastly, dose responses to dietary RPC supplementation were not found for various economically important outcomes including milk yield, limiting the justification for feeding a greater dietary RPC dose in industry.


INTRODUCTION
Despite widespread adoption of control programs, mastitis continues to be a prevalent disease in the dairy industry.The proportion of clinical mastitis is greatest during early lactation (Olde Riekerink et al., 2008).While there are numerous reasons behind this, it is broadly accepted that immune dysfunction and subsequently chronic inflammatory responses play key roles in the enhanced susceptibility to disease following calving (Bradford and Swartz, 2020).As such, investigations into strategies to improve resistance against mastitis pathogens are still needed in dairy cattle.
Most peripartum cows experience negative energy balance due to reductions in feed intake occurring alongside increased energy demand required for lactation.As a result, dairy cattle mobilize fat reserves to supplement dietary energy supply; however, not all fatty acids are completely oxidized, resulting in the production of ketones.These metabolic adaptations to lactation are known risk factors for infectious diseases (Dohoo and Martin, 1984;Oltenacu and Ekesbo, 1994;Raboisson et al., 2014) as well as mastitis severity (Kremer et al., 1993;Swartz et al., 2021).Moreover, negative energy balance induces oxidative stress, or the imbalance of free radicals and antioxidant defenses, which exacerbates inflammation (Sordillo and Aitken, 2009;Sordillo et al., 2009).Indeed, in more recent years, it has become evident that the reduction in feed intake occurring around the time of calving is likely the result of chronic, low-grade inflammation (Bradford et al., 2015).As such, an interdisciplinary approach incorporating nutrition and immunology has gained interest to help improve metabolic adaptations to lactation in periparturient dairy cattle and subsequently reduce the incidence of infectious diseases in the postpartum period (Ingvartsen and Moyes, 2013).To provide one example of this, dietary supplementation of rumen-protected methionine during the periparturient period improved neutrophil function (Zhou et al., 2016a;Batistel et al., 2018), attenuated inflammation in an ex vivo whole blood challenge with LPS (Vailati-Riboni et al., 2017) and enhanced milk production (Zhou et al., 2016b).
Choline is a trimethylated molecule (trimethyl-βhydroxyethylammonium) that plays a central role in numerous biological functions.Because choline is a methyl donor, one of the biological functions it can influence is DNA methylation and as a result it can affect gene transcription (Caudill, 2010).Additionally, choline plays a role in regulation of lipid metabolism and hepatic export of very low-density lipoproteins.In some studies, dietary rumen-protected choline (RPC) supplementation reduced fat accumulation in the liver in feed-restricted dry cows (Cooke et al., 2007;Zenobi et al., 2018b) and reduced plasma NEFA concentrations in periparturient dairy cattle (Pinotti et al., 2003;Sun et al., 2016a), but these effects are not consistent across all studies (Bollatti et al., 2020b).Dietary RPC supplementation also increased vitamin E concentrations and enhanced antioxidant defenses in periparturient dairy cows (Pinotti et al., 2003;Sun et al., 2016a).Using an ex vivo whole blood challenge with LPS, dietary RPC supplementation to healthy periparturient dairy cattle reduced transcript abundance of numerous proinflammatory cytokines from peripheral blood leukocytes (Zenobi et al., 2020).Similarly, using in vitro methods, increasing dose of choline altered numerous bovine immune responses including decreased TNFα secretion from monocytes challenged with LPS and reduced production of reactive oxygen species from neutrophils (Garcia et al., 2018).As a likely result of these effects, numerous studies have found that dietary RPC supplementation enhanced milk yield during the postpartum period (meta-analysis, Arshad et al., 2020).
While some of the dietary RPC effects on periparturient dairy cattle are described, the effects of dietary RPC supplementation during an intramammary challenge have yet to be investigated.Therefore, the objective of this study was to evaluate the effects of dietary RPC supplementation and dose to peripartum dairy cattle on metabolism, oxidant status, inflammation, and performance during an intramammary LPS challenge.We hypothesized that dietary RPC supplementation would reduce lipid mobilization, reduce oxidative stress and inflammation, and enhance milk yield during an intramammary LPS challenge in periparturient dairy cattle.

MATERIALS AND METHODS
Experimental procedures were conducted from January through August 2021 at the Michigan State University Dairy Cattle Teaching and Research Center in East Lansing, MI in accordance with the protocol (PROTO202000184) approved by the Michigan State University Institutional Animal Care and Use Committee.

Experimental Design and Treatments
Experimental procedures related to treatments, study enrollment, and the close-up dry cow diet have been reported elsewhere (Swartz et al., 2022).Close-up dry Holstein parous cows (i.e., cows that had completed at least one lactation before the study; parity, mean ± SD, 1.9 ± 1.1 at study enrollment; n = 67) were blocked by expected calving month and randomly assigned within block to receive one of 3 treatments.Dietary treatments were top-dressing of 45 g/d of RPC (20.4 g/d of choline ions; CHOL45, n = 23), 30 g/d of RPC (13.6 g/d of choline ions; CHOL30, n = 22), or no RPC (CON, n = 22) starting approximately 24 ± 3 d before expected calving until 21 d postpartum.The RPC supplement (Balchem Corporation) used in this study is not currently commercially available.This RPC supplement contained a choline chloride core and a lipid coating with a ruminal protection level of 74.9%, determined Swartz et al.: CHOLINE EFFECTS ON LIPOPOLYSACCHARIDE CHALLENGE using a ruminal in situ procedure over a 12-h time frame.Research staff mixed the RPC supplement with ground corn and the supplement was top-dressed for a total weight of 150 g/d.Control cows received 150 g/d of ground corn.Sample size estimation was based on the number of animals for determining treatment effects between LPS-challenged cows (PROC POWER, SAS 9.4, SAS Inst.Inc.).Using SCS as our primary outcome, a power analysis was conducted using α = 0.05, β = 0.80, SD of 1 unit, and a 1-and 1.5-unit difference between CON-LPS and CHOL30-LPS and between CON-LPS and CHOL45-LPS, respectively; based on this analysis, 10 LPS-challenged cows were needed per treatment group.
Cows with nonfunctional mammary quarters were excluded from study enrollment.Moreover, cows with clinical postpartum diseases after enrollment were excluded from the trial due to animal welfare concerns related to compounding disease issues with the LPS challenge (excluded cows: CHOL45, n = 5; CHOL30, n = 1; CON, n = 3).Within each treatment group, cows were alternately assigned to receive either an intramammary LPS challenge at 17 d postpartum or to be left unchallenged.As such, final sample sizes were as follows: CHOL45, n = 9; CHOL45-LPS, n = 9; CHOL30, n = 11; CHOL30-LPS, n = 10; CON, n = 10; CON-LPS, n = 9.All cows were vaccinated 3 times against Escherichia coli mastitis (Enviracor J-5, Zoetis Animal Health, Parsippany, NJ).These vaccinations were administered at dry-off, 5 wk prepartum, and 10 d postpartum.Genomic evaluations were conducted on all cows using a medium density chip (Clarifide Plus, Zoetis Animal Health).

Diets and Housing
Ingredients and chemical composition of the close-up and lactating diets are provided in Supplemental Table S1 (https: / / doi .org/ 10 .6084/m9 .figshare.22593457.v1;Swartz, 2023).The diets were formulated using AMTS software (Groton, NY) to meet nutrient recommendations for a 620-kg cow consuming 12.7 kg DM/d for the close-up diet, and a 642-kg cow consuming 16.1 kg DM/d, producing 36.3kg milk/d (3.7% fat; 3.0% protein) for the lactating diet.Supplemental rumenprotected methionine was included in close-up and lactating diets during the transition period to evaluate choline effects in the context of a diet that was enriched with methionine.Feed samples of the close-up and lactating TMR were taken weekly, composited by month, and were evaluated using NIR spectroscopy (Cumberland Valley Analytical Services).
Close-up dry cows were housed in freestalls with rubber mattresses that were bedded with sawdust.Cows were fed once daily in the morning (1030 h).Just before the delivery of the TMR, headlocks were set to restrain close-up dry cows such that as the feed was being dispensed from the mixer, cows would be caught in the headlocks.Once all cows were restrained, dietary treatments were provided.Approximately 45 min later, the TMR was inspected to ensure that the supplement had been consumed by each cow.All cows consumed at least some of their daily supplement; however, there were a few instances where a cow did not consume the entire supplement.If this happened, the remaining supplement was removed from the feed bunk to ensure that other cows did not consume it.Dry cows were then released from the headlocks.After calving, cows were housed in tie stalls with rubber mattresses that were bedded with sawdust.The lactating TMR was provided once daily in the morning (1000 h) and dietary treatments were top-dressed following feeding.Tie stalls were fitted with feed gates such that during milking times the feed gates would be closed to ensure that cows only had access to their individual diets.For the first 21 d postpartum, as-fed feed intake was recorded daily by weighing refusals and subtracting it from feed offered and adjusted by the DM content of the diet to determine daily DMI.During the LPS challenge (d 17 through 21), we assessed DMI as a percentage of the d 16 baseline to determine if treatment affected the reduction in feed intake associated with the LPS challenge.
Because inflammatory responses to LPS might be dependent on the weight of the cow, body weights were recorded on d 14 postpartum (3 d before the LPS challenge) using a digital scale.Body condition score (1 to 5 scale) was recorded by a single observer on d −24, −17, −10, 0, 7, 14, and 21 relative to calving.

Milk Weights and Milk Sampling
Cows were milked 3 times daily (0630, 1430, and 2230 h) in a double-7 herringbone parlor.Milk yield was recorded at each milking and summed by day for the first 84 d of lactation.During the LPS challenge (d 17 through 21), we assessed milk yield as a percentage of the d 16 baseline to determine if treatment affected the amount of milk loss associated with the LPS challenge.After the supplementation period ended (at 21 d postpartum), daily milk weights were averaged by week for wk 4 through 12 of lactation.Composite milk samples (~50 mL) were collected at calving (d 0) and once weekly for the first 3 wk postpartum in a sealed tube with a preservative (bronopol) and stored at 4°C for milk component (milk fat and protein) and SCC analyses (Bentley FTM/FCS, Bentley Instruments Inc.) conducted by the Michigan Dairy Herd Improve-ment Association (Central Star DHI).Energy-corrected milk (ECM) yield was calculated using the formula: ECM = (0.327 × milk kg) + (12.95 × fat kg) + (7.65 × protein kg).Somatic cell score was calculated using the formula from Ali and Shook (1980), SCS = log 2 (SCC/100,000) + 3.

Intramammary Challenge
Cows that were assigned to receive an intramammary LPS challenge were infused with 200 μg of LPS (E. coli O111:B4, Millipore Sigma, St. Louis, MO) in 10 mL of sterile PBS into each rear quarter (total of 400 μg of LPS per challenged cow).Approximately 1 h following the morning milking at 17 d postpartum (0730 h), teats were sprayed with a 0.4% chlorhexidine aerosol (Fight bac, Deep Valley Farm) and wiped with a paper towel.Teat ends were then scrubbed with cotton balls soaked in 70% ethanol.The challenge dose (10 mL in each quarter) was administered in the left and right rear quarters via a teat cannula (Jorgensen Laboratories Inc.) and a 20-mL syringe.The infusion was dispensed through the teat canal and massaged upward to aid in the dispersion of the LPS into the mammary gland.Afterward, teats were sprayed with a 0.4% chlorhexidine aerosol.
In LPS-challenged cows, a mammary biopsy was conducted on the left rear quarter at 8 h postchallenge and on the right rear quarter at 48 h postchallenge (data to be reported in a companion paper).Individual quarter foremilk samples were collected during the LPS challenge to quantify SCC from the right rear quarter at 0 (just before challenge), 4, 8, 24, and 48 h (just before biopsy) relative to challenge.The right rear quarter was selected for milk sampling to avoid any influence that the 8 h mammary biopsy may have had on SCC in milk from the left rear quarter.Milk samples were diluted 1:10 in Ca 2+ and Mg 2+ free PBS before being sent to the laboratory.Foremilk SCC was calculated using the dilution factor and transformed to SCS using the aforementioned equation.Finally, vaginal temperature was recorded hourly for the first 48 h following challenge using a data logger (DST micro-T, Star Oddi) attached to a blank CIDR (provided in kind by Zoetis Inc.).

Plasma Analyses
Blood samples (~10 mL into K 2 -EDTA tubes) were collected from the tail vessels just before treatment application (−24 d, covariate), −17, −10 (before their expected calving), 0 (day of calving), 7, 14, and 21 d relative to calving.On d 1, 3, and 7 postpartum, an additional 10-mL blood sample was collected using lithium heparinized tubes for quantifying total calcium.In LPS-challenged cows, 5 additional blood samples were collected (K 2 -EDTA tubes) starting just before challenge (0 h), and 4, 8, 24, and 48 h following challenge.Blood samples were chilled using ice packs, centrifuged at 2,000 × g for 15 min at 4°C to separate plasma, and then the plasma was aliquoted into 2 mL Eppendorf tubes and stored at −80°C.
Haptoglobin, reactive oxygen and nitrogen species (RONS), antioxidant potential (AOP), nonesterified fatty acids (NEFA), BHB, and glucose were measured in plasma samples collected on d −24, −17, −10, 0, 7, 14, and 21 relative to calving.Moreover, all aforementioned parameters plus TNFα were measured in the plasma samples collected around the LPS challenge (0, 4, 8, 24, and 48 h).Assays used to determine oxidant status (RONS and AOP) were conducted within 2 mo of sample collection.The concentrations of RONS were measured using an in vitro ROS/RNS assay kit (Cell Biolabs Inc.).Free radicals convert a nonfluorescent dichlorodihydrofluorescein probe to the fluorescent 2',7'-dichlorodihydrofluorescein and the RONS concentration in the samples is quantified against a hydrogen peroxide standard curve.Antioxidant potential was standardized to the reduction capacity of Trolox, a synthetic vitamin E analog, using 2,2′-azinobis-3-ethylbenzothiazoline-6-sulfonic acid as a radical cation, as previously described (Re et al., 1999).The oxidative stress index (OSi) was calculated by dividing RONS by AOP.Nonesterified fatty acids (NEFA-HR, Fujifilm Wako Chemicals), BHB (Pointe Scientific), and glucose (Fujifilm Wako Chemicals) concentrations were determined using enzymatic colorimetric procedures; for plasma samples collected during the LPS challenge (0, 4, 8, 24, and 48 h), BHB and glucose concentrations were quantified using targeted metabolomics (methods provided in the following section).Haptoglobin (Life Diagnostics) and TNFα (Farney et al., 2011) concentrations were quantified using bovine-specific ELISA.Finally, total calcium was quantified in lithium heparinized plasma samples using a colorimetric assay (Arsenazo III, Pointe Scientific).

Metabolomics Analyses
If the concentration of a metabolite was below the limit of detection (LOD), an imputed value (one-fifth of the least positive value for each metabolite) was used.Metabolites with more than 50% missing values were deemed as not detectable and statistical analyses were not conducted (Supplemental Table S2; https: / / doi .org/ 10 .6084/m9 .figshare.22593457.v1;Swartz, 2023).Because of the complexity of the statistical models, metabolites were analyzed individually using the GLIMMIX procedure (SAS 9.4) rather than using metabolomics software, which was unable to accommodate our experimental design.The model included the fixed effects of treatment, time, and the 2-way interaction, along with the random effects of block and cow.Parity (2 vs. 3+) and BCS recorded just before applying treatment (−24 d) were tested as covariates in all models.Backward elimination was used to remove nonsignificant terms until all variables in the model had a P ≤ 0.05 except for treatment and time, which were forced into the model.Outliers were removed if the absolute value of the Studentized residual was greater than 4. If an outcome variable was nonnormally distributed, a natural logarithmic (ln) transformation was used.No interactions between treatment and time were significant for any of the metabolites.Because of the large number of hypotheses tested, the likelihood of type 1 error is high.To limit type 1 error, the Benjamini-Hochberg procedure was used to determine the false discovery rate (FDR; PROC MULTTEST, SAS 9.4).When treatment FDR ≤0.10, treatment least squares means were separated using the PDIFF statement with a Tukey adjustment.Significance was declared at P ≤ 0.05.

Statistical Analyses
Linear mixed models were conducted using the GLIMMIX procedure (SAS 9.4).Data recorded before the LPS challenge were analyzed in a separate model from data recorded during the LPS challenge.Similarly, carryover milk yield responses after the dietary choline supplementation period ended were analyzed in a separate model (i.e., wk 4 through 12 of lactation).
For milk yield, ECM yield, milk component yields, composite SCS, DMI, and plasma analytes collected before the LPS challenge, the model included the fixed effects of treatment, time (repeated measure), and 2-way interactions, along with the random effects of block and cow.The genetic traits (genomic PTA for milk [PTAM], fat [PTAF], protein [PTAP], and the PTA for SCS) were tested as a covariate in their respective models.For ECM yield, PTAM was tested.Furthermore, plasma analytes (haptoglobin, RONS, AOP, OSi, NEFA, BHB, and glucose) recorded just before applying treatment (−24 d) were tested as covariates in their respective models.Parity (2 vs. 3+) and BCS recorded before applying treatment (−24 d) was tested for every outcome.Finally, the interaction of the covariates with treatment were tested.
For milk yield (both from 17 to 21 DIM as well as carryover responses measured wk 4 to 12 of lactation), ECM yield, milk component yields, composite SCS, DMI, and plasma analytes recorded after the LPS challenge, the model included the fixed effects of treatment, LPS (challenged vs. unchallenged), time (when applicable), and 2-and 3-way interactions, along with the random effects of block and cow.The genetic traits (genomic PTAM, PTAF, PTAP, and the PTA for SCS) were tested as a covariate in their respective models.For ECM yield, PTAM was tested.Furthermore, plasma analytes (haptoglobin, RONS, AOP, OSi, NEFA, BHB, and glucose) recorded just before applying treatment (−24 d) were tested as covariates in their respective models.Parity (2 vs. 3+) and BCS recorded before applying treatment (−24 d) were tested for every outcome.Finally, the interaction of the covariates with treatment were tested.
For plasma analytes and SCS from quarter-level milk samples collected only from LPS-challenged cows (0, 4, 8, 24, and 48 h relative to challenge), the model included the fixed effects of treatment, time, and the 2-way interaction, along with the random effects of block and cow.Parity (2 vs. 3+) and BCS recorded just before applying treatment (−24 d) were tested as covariates in all models.Plasma analytes (haptoglobin, RONS, AOP, OSi, NEFA, BHB, and glucose) recorded just before treatment (−24 d) were tested as covariates in their respective models.For SCS, the PTA for SCS was tested along with the interaction with treatment.
Backward elimination was used to remove nonsignificant terms until all variables in the model had a P ≤ 0.05 or were part of a significant interaction term except for treatment, LPS (when applicable), and time (when applicable), which were forced into the model.For repeated measures analyses, the first order autoregressive error structure was used, unless sampling time points were uneven, in which case spatial power was used instead.Treatment least squares means were separated using the SLICEDIFF or PDIFF statement with a Tukey adjustment.In all models, residuals were evaluated for normality and outliers (PROC UNIVARI-ATE).Outliers were removed if the Studentized residual was greater than the absolute value of 4. If an outcome variable was nonnormally distributed, a natural logarithmic (ln) transformation was used.Significance was declared at P ≤ 0.05.

Milk, Milk Component, and ECM Yields After the LPS Challenge
Treatment LSM, SEM, and probability levels are provided in Table 2 for milk, milk fat, milk protein, and ECM yields after the LPS challenge.Data are illustrated in Supplemental Figures S1 and S2.From 17 to 21 d (after LPS challenge), treatment did not affect milk yield (P = 0.08).When assessing LPS effects over time (interaction, P < 0.0001), LPS-challenged cows produced less milk than unchallenged cows with a 19.1 (±1.7 SED) kg difference on d 17 that gradually diminished to a 4.8 (±1.7 SED) kg difference by d 21 (all P ≤ 0.01).Treatment did not affect milk yield expressed as a percentage of the d 16 baseline following the LPS challenge (P = 0.44; Table 2).Challenged cows deviated from the d 16 baseline more than unchallenged cows starting on d 17 and remained significantly different through d 21 (all P ≤ 0.01).
Following the LPS challenge, neither treatment (P = 0.72) nor LPS (P = 0.19) affected milk protein yield at 3 wk postpartum (Table 2).Treatment did not affect milk fat yield following the LPS challenge (P = 0.18); nevertheless, LPS-challenged cows produced 0.25 (±0.098SED) kg/d less milk fat than unchallenged cows at 3 wk postpartum (P = 0.01; Table 2).For ECM yield at 3 wk postpartum, treatment interacted Within a row, treatment means with different superscripts differ (P ≤ 0.05). 1 Milk yield and DMI were recorded daily.For milk components and composite SCS, milk samples were collected once weekly starting at calving.Body condition score was recorded on d −17, −10, 0, 7, and 14 before the LPS challenge.Interactions between treatment and time were not significant.Trmt = treatment. 2For milk fat yield, there was a significant interaction (P = 0.02) between treatment and the genetic parameter for milk fat yield (PTAF; Figure 1A).When the cow's genomic PTAF was ≤9 kg (≤50th percentile), CHOL45 cows produced greater milk fat yields than CON (all P ≤ 0.02).When the cow's genomic PTAF was ≤4.5 kg (≤30th percentile), CHOL30 cows produced more milk fat than CON (all P ≤ 0.03).Treatment interacted with the genomic PTA for ECM yield at 3 wk postpartum (interaction, P = 0.04; B).When the cow's genomic PTAM was ≤2 kg (≤20th percentile), CHOL45 cows produced more ECM yield than CON (all P ≤ 0.03).Values are LSM ± SE.Trmt = treatment; PTAF = predicted transmitting ability for milk fat yield; PTAM = predicted transmitting ability for milk yield.

Composite Somatic Cell Score
Treatment did not affect composite SCS before the LPS challenge (P = 0.42; Table 1) nor following the LPS challenge at 3 wk postpartum (P = 0.16; Table 2).Cows that were challenged with LPS had a greater composite SCS at 3 wk postpartum than unchallenged cows (P < 0.0001).Data are illustrated in Supplemental Figure S2F.
Postpartum DMI was not affected by treatment before the LPS challenge (P = 0.80; Table 1).After the LPS challenge, treatment did not affect DMI (P = 1.00;Table 2).When assessing LPS effects over time (interaction, P < 0.0001), LPS-challenged cows consumed less DM than unchallenged cows on d 17 through d 20 (all P ≤ 0.03).To determine if treatment affected the reduction in DMI associated with the LPS challenge, we assessed DMI as a percentage of the d 16 baseline (before challenge).Although treatment interacted with LPS (P = 0.04), none of the pairwise comparisons between treatment groups were significantly different (all P ≥ 0.16).Furthermore, the change from baseline indicating a reduction in DMI due to LPS challenge was Within a row, treatment means with different superscripts differ (P ≤ 0.05). 1 Cows were alternatively assigned within treatment group to receive an intramammary LPS challenge (200 μg in each rear quarter; 400 μg in total per challenged cow) on d 17 or to be left unchallenged.Milk yield and DMI were recorded daily.Carryover milk yield was recorded daily and averaged by week for wk 4 through 12 of lactation.A single milk sample was collected for component and composite SCS analyses for wk 3. Similarly, BCS was recorded on d 21 following the LPS challenge.Trmt = treatment. 2For ECM, there was a significant interaction (P = 0.04) between treatment and the genetic parameter for milk yield (PTAM; Figure 1B). 3For DMI expressed as a percentage of the d 16 baseline, there was a significant treatment by LPS interaction (P = 0.04); however, none of the pairwise comparisons between treatment groups were significantly different (all P ≥ 0.16).
apparent within every treatment group (CHOL45-LPS vs. CHOL45, P < 0.0001; CHOL30-LPS vs. CHOL30, P = 0.04; CON-LPS vs. CON, P = 0.03).Moreover, the change from baseline was detected in LPS-challenged cows as compared with unchallenged cows (LPS by time interaction, P < 0.0001) starting from d 17 and carrying through d 20 (all P ≤ 0.03); however, this change from baseline was no longer statistically significant between LPS-challenged and unchallenged cows on d 21 (P = 0.20).Dry matter intake data are illustrated in Supplemental Figure S3B-C.

Plasma Analyses Measured on d 21 in Challenged and Unchallenged Cows
Treatment LSM, SEM, and probability levels are provided in Table 4 for plasma analytes measured on d 21.Data are illustrated in Supplemental Figure S4.Treatment did not affect plasma haptoglobin concentrations on d 21 (P = 0.82); however, challenged cows had greater plasma haptoglobin concentrations than unchallenged cows (P < 0.0001).There was a significant treatment by LPS interaction on d 21 for plasma NEFA concentrations (interaction, P = 0.05).Cows in the CHOL45-LPS group had Data presented using a natural logarithmic transformation. 3 For plasma AOP, there were 2 significant interactions.Treatment interacted with time (interaction, P = 0.03; Figure 2A).Treatment also interacted with the −24 d AOP covariate (interaction, P = 0.03; Figure 2B).greater plasma NEFA concentrations than CON-LPS cows (P = 0.01); however, no other pairwise comparison between treatment groups was significantly different (all P ≥ 0.27).Moreover, LPS effects within treatment groups were not significantly different (CHOL45-LPS vs. CHOL45, P = 0.09; CHOL30-LPS vs. CHOL30, P = 0.35; CON-LPS vs. CON, P = 0.12).Neither treatment (P = 0.79) nor LPS (P = 0.40) affected BHB concentrations on d 21.Similarly, treatment (P = 0.46) and LPS (P = 0.34) did not affect plasma glucose concentrations on d 21 (P = 0.46).The concentrations of plasma RONS were similar between treatment groups after the LPS challenge (P = 0.26) and the LPS challenge did not affect plasma RONS concentrations (P = 0.34).Neither treatment (P = 0.35) nor LPS (P = 0.06) affected plasma AOP concentrations on d 21.As such, the OSi was similar between treatment groups (P = 0.88), and similar between LPS-challenged and unchallenged cows (P = 0.43).Within a row, treatment means with different superscripts differ (P ≤ 0.05). 1 An intramammary LPS challenge (200 μg in each rear quarter; 400 μg in total per challenged cow) was conducted on d 17.Vaginal temperature was recorded hourly for the first 48 h postchallenge.Milk and blood samples were collected at 0 (just before the challenge), 4, 8, 24, and 48 h relative to the LPS challenge.Interactions between treatment and time were not significant for any outcome.Trmt = treatment. 2Treatment interacted with the genetic parameter for SCS (PTA SCS; interaction, P < 0.01; Figure 3).

Vaginal Temperature and Quarter-Level SCS During the LPS Challenge
Treatment LSM, SEM, and probability levels are provided in Table 5 for vaginal temperature and quarter-level SCS measured during the LPS challenge.Data are illustrated in Supplemental Figure S5 (https: / / doi .org/ 10 .6084/m9 .figshare.22593457.v1;Swartz, 2023).In every treatment group, cows had robust and rapid febrile responses, with mean peak vaginal temperature occurring at 5 h postchallenge.Vaginal temperature was affected by treatment (P < 0.01), where CHOL45-LPS cows had 0.32°C (±0.10 SED) greater body temperatures than CON-LPS (P < 0.01).No difference was found between CHOL45-LPS and CHOL30-LPS (P = 0.06) or between CHOL30-LPS and CON-LPS (P = 0.64).Quarter-level SCS rapidly climbed from 0 to 8 h, then plateaued until 24 h and subsequently began to decline at 48 h following the LPS challenge.Treatment interacted with the genomic PTA for SCS (interaction, P < 0.01; Figure 3).When the genomic PTA for SCS was ≤2.93 (≤70th percentile), CHOL45-LPS cows had a lesser SCS than CON-LPS (P ≤ 0.05).When the genomic PTA for SCS was ≥2.87 (≥50th percentile), CHOL30-LPS cows had a lesser SCS than CON-LPS (P ≤ 0.02).When the genomic PTA for SCS was ≤2.8 (≤30th percentile), CHOL45-LPS cows had a lesser SCS than CHOL30-LPS (P ≤ 0.05).In general, the differences between treatment groups were relatively small, approximately 0.5 to 1 SCS difference between RPC supplemented cows and CON cows with inferior SCS genetics.Finally, the genomic PTA for SCS was positively associated with challenged quarter SCS responses (P = 0.01).

Plasma Analyses During the LPS Challenge
Treatment LSM, SEM, and probability levels are provided in Table 5 for plasma analytes measured during the LPS challenge (0, 4, 8, 24, and 48 h relative to challenge).Data are illustrated in Supplemental Figure S6 (https: / / doi .org/ 10 .6084/m9 .figshare.22593457.v1;Swartz, 2023).During the LPS challenge, treatment did not affect plasma concentrations of haptoglobin (P = 0.15), TNFα (P = 0.36), RONS (P = 0.13), and AOP (P = 0.90).Treatment did not affect the OSi (P = 0.57) during the LPS challenge.Finally, plasma NEFA concentrations were affected by treatment during the LPS challenge (P < 0.001).Cows in the CHOL45-LPS and CHOL30-LPS groups had approximately 100 ) on quarter-level SCS (milk samples from the right rear quarter) in cows receiving an intramammary LPS challenge.The intramammary LPS challenge (200 μg in each rear quarter; 400 μg in total per challenged cow) was conducted on d 17.Milk samples were collected at 0 (just before the challenge), 4, 8, 24, and 48 h relative to the LPS challenge.Treatment interacted with the genetic parameter for SCS (PTA SCS; interaction, P < 0.01).When the genomic PTA for SCS was ≤2.93, CHOL45-LPS cows had a lesser SCS than CON-LPS (all P ≤ 0.05).When the genomic PTA for SCS was ≥2.87, CHOL30-LPS cows had a lesser SCS than CON-LPS (all P ≤ 0.02).When the genomic PTA for SCS was ≤2.8, CHOL45-LPS cows had a lesser SCS than CHOL30-LPS (all P ≤ 0.05).Values are LSM ± SE.Trmt = treatment.μmol/L greater plasma NEFA concentrations than CON-LPS (both P < 0.001); no difference was found between CHOL45-LPS and CHOL30-LPS (P = 0.90).

Plasma AA During the LPS Challenge
The concentrations of tryptophan were affected by treatment (FDR = 0.10).Plasma tryptophan concentrations were lesser in CHOL45-LPS (P = 0.01) as compared with CON-LPS, although no difference was found between CHOL30-LPS and CON-LPS (P = 0.08).
carnitine concentrations were greater in CHOL30-LPS cows as compared with CON-LPS (P < 0.01); however, no difference was found between CHOL45-LPS and CON-LPS (P = 0.40).

DISCUSSION
The objectives of our study were to determine the effects of dietary RPC supplementation and dose to periparturient dairy cattle on metabolism, oxidant status, inflammation, and performance during an intramammary LPS challenge.In general, we found that dietary RPC supplementation increased milk yield and altered the concentrations of numerous metabolites but did not attenuate inflammation.As such, our data suggest that the effects of dietary RPC on milk yield may be mediated through metabolic pathways and are unlikely to be related to resolution of inflammation during an intramammary LPS challenge.Moreover, dose responses to dietary RPC supplementation were not found for many of the outcomes including milk yield.Therefore, the justification for feeding a greater dietary RPC dose than what is typically fed in industry (12.9 g/d of choline ions) is limited.

Effects of Dietary RPC Supplementation on Milk and Milk Component Yields
Cows in the CHOL45 and CHOL30 groups produced 3.4 and 3.8 kg/d more milk, respectively, than CON cows for the first 16 d of lactation.These results are generally in agreement with a meta-analysis which found that dietary RPC supplementation increased milk yield in postpartum dairy cows by approximately 2 kg/d (Arshad et al., 2020).During the LPS challenge, treatment effects were not observed, and milk loss associated with the LPS challenge was similar between treatment groups.Nevertheless, a carryover effect was observed where cows supplemented with CHOL45 and CHOL30 produced approximately 3.1 and 3.5 kg/d more milk than CON cows, respectively, for wk 4 through 12 of lactation, even though the dietary RPC supplementation period ended at 21 d postpartum.These results are similar to those found by Bollatti et al. (2020a) where dietary RPC supplementation during the periparturient period enhanced ECM yields by 2.4 kg/d for wk 4 through 15 of lactation.
Although no treatment effects were found on milk protein yields, CHOL45 and CHOL30 cows produced greater milk fat yields than CON during the first 2 wk of lactation, but this effect was only found in cows with inferior genetics for milk fat yield (PTAF).Similarly, CHOL45 and CHOL30 cows produced greater ECM yields than CON during the first 2 wk of lactation.At 21 d postpartum, milk fat yield was not affected by treatment; however, CHOL45 and CHOL30 cows produced greater ECM yields than CON if the cows had inferior genetics for milk yield (PTAM).Generally, these data concur with numerous studies that have found the dietary RPC supplementation increased milk fat yield 1 An intramammary LPS challenge (200 μg in each rear quarter; 400 μg in total per challenged cow) was conducted on d 17 after calving.Blood samples were collected at 0 (just before the challenge), 4, 8, 24, and 48 h relative to the LPS challenge.False discovery rate (FDR) was calculated using the Benjamini-Hochberg method.Interactions between treatment and time were not significant for any metabolite.Trmt = treatment.
2 Data presented using a natural logarithmic transformation.
and ECM yield (meta-analysis, Arshad et al., 2020).Nevertheless, we are unaware of any dairy cattle studies that assessed the interactions between genetic potential and dietary RPC supplementation.In humans, there is a greater appreciation for the interactions between choline and genetic polymorphisms related to health and disease (Zeisel, 2011;Smallwood et al., 2016).Potentially, an increased supply of methyl donors altered DNA methylation affecting gene transcription related to milk fat synthesis in the mammary gland.

Effects of Dietary RPC Supplementation on Adipose Tissue Mobilization
From −17 to 14 d relative to calving, treatment did not affect plasma NEFA concentrations; however, during the LPS challenge, CHOL45-LPS and CHOL30-LPS cows had greater plasma NEFA concentrations than CON-LPS, and CHOL45-LPS had greater NEFA concentrations than CON-LPS on d 21.These data broadly imply that cows supplemented with RPC had greater adipose tissue mobilization than CON cows.In support of this, postpartum DMI were similar between treatment groups when energy demands were greater due to greater milk yields produced by cows supplemented with dietary RPC.Nevertheless, a limitation to our study is that prepartum DMI were not measured.While no difference in plasma NEFA concentrations were found during the first 2 wk of lactation (before the LPS challenge), we would note that cows supplemented with dietary RPC produced greater milk fat yields.This may have masked treatment effects on plasma NEFA concentrations, as the mammary gland can use circulating NEFA for milk fat synthesis (Glascock and Welch, 1974).Unlike the present study, the majority of past studies have found that dietary RPC supplementation had no effect on NEFA concentrations (Zhou et al., 2016b;Zenobi et al., 2018a;Bollatti et al., 2020b), although Sun et al. (2016a) reported a decline in NEFA concentrations during the postpartum period.Moreover, a meta-analysis found dietary RPC supplementation reduced postpartum NEFA concentrations (Arshad et al., 2020); however, the magnitude of the difference was small.

Effects of Dietary RPC Supplementation on Energy Metabolism
Carnitines are quaternary ammonium compounds that support energy metabolism by transporting long-chain fatty acids into the mitochondria for oxidation.Dietary RPC supplementation increased plasma acetylcarnitine and decreased propionylcarnitine concentrations in both CHOL45-LPS and CHOL30-LPS as compared with CON-LPS cows.As mentioned previously, plasma NEFA concentration was greater in cows supplemented with dietary RPC during the LPS challenge in the present study.As such, our data are in agreement with Humer et al. (2016) that found a positive association between acetylcarnitine and serum NEFA concentrations, and a negative association between propionylcarnitine and serum NEFA in early-lactation dairy cattle.The inverse relationship between these 2 carnitines (greater acetylcarnitine and lesser propionylcarnitine concentrations) have also been found in humans with type 2 diabetes (Adams et al., 2009).Supplementation of L-carnitine to feed-restricted cows is beneficial for liver function in dairy cattle as it reduced total lipid accumulation in the liver and enhanced ex vivo fatty acid oxidation (Carlson et al., 2006).Potentially, the increase in acetylcarnitine in the present study may provide an additional mechanism behind the effects found in past studies showing that dietary RPC supplementation reduced fat accumulation in the liver in feed-restricted dairy cattle (Cooke et al., 2007;Zenobi et al., 2018b).Assuming that plasma concentrations of carnitines are reflective of liver concentrations, an increase in plasma acetylcarnitine concentrations in cows supplemented with dietary RPC may suggest an increase in the supply of acetyl-CoA used to acetylate free carnitine.The increase in supply of acetyl-CoA would likely be due to enhanced fatty acid oxidation.In support of this notion, cows in the CHOL45 and CHOL30 groups had greater plasma BHB concentrations than CON from −17 to 14 d relative to calving.
Alterations in hepatic lipid metabolism can have direct and indirect effects on glucose metabolism.Glucose is metabolized to pyruvate during glycolysis.Under normoxic conditions, pyruvate is oxidized to acetyl-CoA and then fully oxidized to carbon dioxide and water in the tricarboxylic acid (TCA) cycle to generate NADH; however, under hypoxic conditions, pyruvate is fermented to lactic acid.In the liver, lactic acid can be used a substrate to regenerate glucose by gluconeogenesis.Dietary RPC supplementation reduced plasma lactic acid concentrations during the LPS challenge, suggesting either a reduction in glycolysis or greater flux through the lactic acid cycle to support gluconeogenesis.

Effects of Dietary RPC Supplementation on AA Metabolism
Plasma concentrations of tryptophan during the LPS challenge were reduced in CHOL45-LPS cows as compared with CON-LPS.Dietary RPC supplementation did not affect milk protein yields in the present study, suggesting that the effect of treatment on plasma tryp- tophan concentrations was not related to milk protein synthesis.Tryptophan is a gluconeogenic and ketogenic AA.Therefore, this AA may have been catabolized to support glucose and ketone production, the latter of which was increased in plasma from dietary RPC supplemented cows before the LPS challenge.
Plasma concentrations of fumaric acid were greater in both CHOL45-LPS and CHOL30-LPS as compared with CON-LPS.Fumaric acid is generated as a final product of the urea cycle and as a product of AA catabolism.Moreover, fumaric acid is an intermediate of the TCA cycle, linking gluconeogenesis with ureagenesis (Mayes et al., 2003).Greater plasma fumaric acid concentrations in cows supplemented with dietary RPC may have implications on ureagenesis and gluconeogenesis, although this requires further investigation.

Effects of Dietary RPC Supplementation on Choline Metabolism
Choline can be metabolized either through the cytidine diphosphate choline pathway or the phosphatidylethanolamine N-methyltransferase pathway.Lipidsoluble choline metabolites include PC and SM, which are structural components of cell membranes, and phospholipases can partially hydrolyze PC to yield the metabolite LPC (Zeisel and Blusztajn, 1994).Watersoluble choline metabolites include betaine, which was measured in the present study, as well as acetylcholine, phosphocholine, and glycerophosphocholine (Zeisel and Blusztajn, 1994), which were not measured in the present study.Dietary RPC supplementation did not alter the concentrations of plasma choline, betaine, total LPC, total SM, total PC, or total choline molecules (sum of choline, total LPC, total SM, and total PC) during the LPS challenge.While this may seem surprising, it is noteworthy that dietary RPC supplementation substantially enhanced milk yields (3.4 to 3.8 kg/d depending on the dose) before the LPS challenge.Indeed, in our companion paper (Swartz et al., 2022), both CHOL45 and CHOL30 cows had greater yields of choline, betaine, and total choline molecules in colostrum than CON cows, but no effects were found on the concentrations of these choline metabolites.France et al. (2022) found that the dose of RPC increased plasma choline and betaine concentrations in mid-lactation cows; however, that study administered a single bolus of RPC and did not assess daily dietary RPC supplementation during the periparturient period as in the present study.Because of this, France et al. (2022) did not evaluate the effects of RPC supplementation on plasma choline metabolite concentrations in periparturient cows where RPC supplementation increases milk yield, as is often the case.As such, we speculate that the effects of dietary RPC supplementation on the plasma concentrations of choline metabolites did not differ between treatment groups in the present study because greater amounts of choline metabolites were being secreted in milk.
Dietary RPC supplementation altered plasma concentrations of a few acyl-specific isomers of LPC during the LPS challenge.Lysophosphatidylcholine is produced via partial hydrolysis of PC via phospholipase A 2 (Law et al., 2019).Moreover, phospholipase A 2 is a critical enzyme in the inflammatory pathway to liberate arachidonic acid, a precursor to numerous prostaglandins and leukotrienes.Conversely, LPC can be broken down via lysophospholipases (Law et al., 2019).Total LPC concentrations were not affected by treatment.As a result, it seems unlikely that dietary RPC supplementation affected activity of phospholipase A 2 or the degradation of LPC via lysophopholipases.It also seems unlikely that the altered concentrations of these acyl-specific isomers of LPC are related to plasma choline concentrations as we were unable to identify any treatment effects on the concentrations of any choline containing metabolites.As such, the mechanisms underlying the effects of dietary RPC on acyl-specific isomers of LPC is unknown and requires further investigation.
In addition to the lipid-soluble metabolites, choline also serves as a methyl donor in the one-carbon metabolic pathway.Choline can be oxidized to betaine, which contains 3 methyl groups.Betaine can be further demethylated to dimethylglycine and eventually sarcosine (also known as monomethylglycine).Additionally, glycine can be methylated via glycine N-methyltransferase to resynthesize sarcosine (Mudd et al., 2007).Sarcosine concentrations were increased in CHOL45-LPS cows as compared with either CHOL30-LPS or CON-LPS.In general, these data suggest that feeding larger doses of RPC, such as the dose used in the CHOL45 group (20.4 g/d of choline ions), enhanced the supply of methyl donors sufficiently enough to increase the utilization of choline as a methyl donor.Nevertheless, ruminants have evolved to limit the need for nonessential methylation reactions reducing sarcosine synthesis; this adaptation is likely due to the destruction of methyl donors by rumen microbes limiting their supply to the animal (Xue and Snoswell, 1986;Snoswell and Xue, 1987).As such, an increase in sarcosine concentrations could be an indicator that the supply of methyl donors exceeded requirements.

Effects of Dietary RPC Supplementation on Oxidant Status
Cows in the CHOL45 group had improved AOP as compared with either CON or CHOL30 groups at various time points throughout the periparturient period, although no treatment effects on AOP were found during the LPS challenge.Past studies have also found dietary RPC supplementation enhanced antioxidant defenses and increased vitamin E concentrations (Pinotti et al., 2003;Sun et al., 2016a).Methionine sulfoxide, the oxidized form of the AA methionine and a marker for oxidative stress, was reduced in CHOL45-LPS cows as compared with CON-LPS, despite a lack of treatment effects on methionine concentrations.The sulfur residues on methionine can be used to scavenge free radicals.This reaction is reversible, as methionine sulfoxide can be reduced to methionine via methionine sulfoxide reductase (Weissbach et al., 2005).Elevated ratios of methionine sulfoxide: methionine have been associated with oxidative stress and disease in humans (Suzuki et al., 2016).Reductions in methionine sulfoxide with no effect on methionine concentrations suggest that CHOL45-LPS cows had improved oxidant status.Furthermore, our data suggest that a larger dose of dietary RPC, such as the dose used in the CHOL45 group (20.4 g/d of choline ions vs. 13.6 g/d of choline ions for CHOL30), may be needed to enhance antioxidant defenses in periparturient dairy cattle, although 15 g/d of choline ions was sufficient to do so in a past study (Sun et al., 2016a).

Effects of Dietary RPC Supplementation on Inflammatory Markers
Supplementation of dietary RPC during the periparturient period and the intramammary LPS challenge had minimal effects on inflammatory markers.For instance, concentrations of haptoglobin, an acute phase protein and a nonspecific inflammatory marker (Ceciliani et al., 2012), were not different between treatment groups at any time point.Moreover, concentrations of plasma TNFα did not differ between treatment groups during the LPS challenge.While we did find a small decrease in SCS in the milk during the LPS challenge in cows supplemented with RPC as compared with CON-LPS that had inferior SCS genetics, this reduction was too small to mitigate the milk loss associated with the challenge.
Plasma concentrations of asymmetric dimethylarginine were lesser in both CHOL45-LPS and CHOL30-LPS as compared with CON-LPS.Asymmetric dimethylarginine is a methylated analog of l-arginine, and is an endogenous inhibitor of nitric oxide synthase (Leone et al., 1992).Although asymmetric dimethylarginine has been associated with cardiovascular disease in humans (Tain and Hsu, 2017), relatively little is known about this metabolite in dairy cattle.Ghaffari et al. (2019) found serum concentrations of asymmetric di-methylarginine declined during the postpartum period in dairy cattle, although the implications of this are unknown.In the present study, plasma asymmetric dimethylarginine concentrations declined during the first 8 h following the LPS challenge, potentially reflecting a physiological response to enhance nitric oxide synthesis as a part of immune activation.
Cows in the CHOL45-LPS group had greater vaginal temperatures during the intramammary LPS challenge than CON-LPS cows.Coinciding with this, CHOL45-LPS cows also had greater concentrations of TMAO than CON-LPS.Trimethylamine N-oxide is derived from microbial metabolism of choline to trimethylamine in the gut (rumen or intestine depending on the degree of ruminal protection), which is then oxidized by flavin-containing monooxygenases in the liver (Wang et al., 2011).Elevated concentrations of TMAO have been associated with numerous diseases in humans, although the direct effects remain unclear (Ufnal et al., 2015).In our companion paper (Swartz et al., 2022), we found similar results where colostrum from both CHOL45 and CHOL30 cows had greater concentrations of TMAO than CON.Moreover, a recent study found that a dietary bolus of RPC increased plasma TMAO concentrations in both mid-and late lactation cows (France et al., 2022).Using either in vitro methods or mouse models, TMAO has been found to exert a proinflammatory effect (Sun et al., 2016b;Boini et al., 2017).Specifically, TMAO activates the NLRP3 inflammasome, resulting in cleavage of caspase-1, and as a result, the maturation and secretion of proinflammatory cytokines such as interleukin-1β (Sun et al., 2016b;Boini et al., 2017).Interleukin-1β (IL-1β) is pyrogenic (Goff et al., 1992), which may explain the elevated vaginal temperature found in CHOL45-LPS cows as those cows also had greater plasma TMAO concentrations.Numerous attempts were made in the present study to measure plasma IL-1β concentrations; unfortunately, none of the ELISA kits performed adequately when conducting a validation.As such, the mechanism behind the increased vaginal temperature in CHOL45-LPS cows remains unclear.It should be noted that an intravenous infusion of TMAO had no effect on liver health or milk production in early-lactation dairy cows (Myers et al., 2021); however, that study did not evaluate the effect of TMAO during a LPS challenge.Potentially, the effect of TMAO on the inflammatory response is only evident in infectious disease scenarios.

Noteworthy Intramammary LPS Effects
Many of the effects of an intramammary LPS challenge are well-known, particularly those related to inducing inflammation, reducing milk production, and decreasing feed intake.Our data set provides some additional interesting LPS effects that we highlight below.
Cows challenged with LPS produced substantially less milk during the challenge, as expected.But more interestingly, LPS-challenged cows also produced 2.2 kg/d less milk than unchallenged cows during the carryover period (wk 4 through 12 of lactation).This is likely the result of apoptosis occurring in the mammary epithelium, although other effects such as altered metabolic processes and epigenetic effects cannot be ruled out.Nonetheless, these data underscore the importance of preventing mastitis especially during early lactation, as one of the largest contributors to the cost of clinical mastitis is the loss of future milk yield (Rollin et al., 2015).
Plasma concentrations of many choline metabolites including choline, betaine, total PC, total LPC, and total choline declined during the first 8 h following the LPS challenge.The LPC data agree with Humer et al. (2018), who found LPC concentrations declined 24 h following an intramammary LPS challenge in Simmental cattle.There is scant evidence in the scientific literature on why an LPS challenge might reduce concentrations of choline metabolites in dairy cattle.In a mouse model, choline uptake and metabolism was vital for activation and IL-1β secretion from macrophages (Sanchez-Lopez et al., 2019).Potentially, choline metabolism plays a role in immune function, but future studies are needed to provide additional clarity.
In addition to choline metabolism, the LPS challenge altered the concentrations of numerous metabolites related to energy metabolism.Plasma concentrations of both lactic and pyruvic acid increased during the first 8 h following the LPS challenge while concentrations of citric acid decreased, suggesting an enhancement in glycolytic flux and a reduction in oxidative phosphorylation (TCA cycle flux) potentially due to immune activation (Ganeshan and Chawla, 2014).
Concentrations of acetylcarnitine (C2) declined during the first 8 h following the LPS challenge.Moreover, plasma BHB concentrations declined during the first 8 h of the LPS challenge.These data suggest that the LPS challenge reduced fatty acid oxidation in the liver of dairy cows, in agreement with Minuti et al. (2015).While this could be due to impaired liver function, we would note that plasma NEFA concentrations also declined at 8 h following the LPS challenge, similar to the results of Pires et al. (2019), which would reduce the supply of NEFA to the liver.
Similar to plasma NEFA, concentrations of all proteogenic AA, along with methylhistidine, a marker for muscle catabolism (Plaizier et al., 2000), declined at 8 h following the LPS challenge as compared with pre-challenge levels.These AA results are similar to the results found in lambs (Hoskin et al., 2016), steers (Waggoner et al., 2009), and Simmental cattle (Humer et al., 2018) challenged with LPS.Endotoxin challenges are known to induce insulin release, although insulin resistance in peripheral tissues can occur simultaneously (Kvidera et al., 2017;Horst et al., 2019).Taken together, we speculate that insulin signaling impaired adipose and muscle tissue catabolism during the acute phase response of the LPS challenge in the present study.

CONCLUSIONS
Dietary RPC supplementation increased milk and milk fat yield, enhanced adipose mobilization, and altered plasma concentrations of numerous metabolites involved in energy and AA metabolism.Dietary RPC supplementation did not enhance plasma concentrations of most choline metabolites, which is likely due to greater secretion of choline metabolites in milk.Apart from a small decrease in SCS particularly in cows with inferior genetics (PTA SCS), dietary RPC supplementation did not attenuate inflammation during the LPS challenge.As such, our data suggest that the effects of dietary RPC on milk yield are likely mediated through metabolic pathways and are unlikely related to inflammation in periparturient dairy cattle.Finally, dose responses to dietary RPC supplementation were not found for many of the outcomes including milk yield.Therefore, the justification for feeding a greater dietary RPC dose than what is typically fed in industry is limited.
Swartz et al.: CHOLINE EFFECTS ON LIPOPOLYSACCHARIDE CHALLENGE Swartz et al.: CHOLINE EFFECTS ON LIPOPOLYSACCHARIDE CHALLENGE