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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Anim. Sci.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Animal Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Anim. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2673-6225</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fanim.2026.1763503</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>Evaluating plasma oxidative measures in beef calves supplemented with methionine and challenged with lipopolysaccharide</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name><surname>Barker</surname><given-names>Samantha N.</given-names></name>
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<name><surname>Jackson</surname><given-names>Treylr C.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Richeson</surname><given-names>John T.</given-names></name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
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<contrib contrib-type="author">
<name><surname>Carroll</surname><given-names>Jeffery A.</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<contrib contrib-type="author">
<name><surname>Burdick Sanchez</surname><given-names>Nicole C.</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<contrib contrib-type="author">
<name><surname>Broadway</surname><given-names>Paul R.</given-names></name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
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<contrib contrib-type="author">
<name><surname>Ducharme</surname><given-names>Gary</given-names></name>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
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<contrib contrib-type="author">
<name><surname>Kerth</surname><given-names>Christopher R.</given-names></name>
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<contrib contrib-type="author">
<name><surname>Hernandez</surname><given-names>Manuel Sebastian</given-names></name>
<xref ref-type="aff" rid="aff6"><sup>6</sup></xref>
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<contrib contrib-type="author" corresp="yes">
<name><surname>Legako</surname><given-names>Jerrad F.</given-names></name>
<xref ref-type="aff" rid="aff5"><sup>5</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>*</sup></xref>
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<aff id="aff1"><label>1</label><institution>Department of Animal Sciences, Tarleton State University</institution>, <city>Stephenville</city>, <state>TX</state>,&#xa0;<country country="us">United States</country></aff>
<aff id="aff2"><label>2</label><institution>Department of Agricultural Sciences, West Texas A&amp;M University</institution>, <city>Canyon</city>, <state>TX</state>,&#xa0;<country country="us">United States</country></aff>
<aff id="aff3"><label>3</label><institution>USDA-ARS, Livestock Issues Research Unit</institution>, <city>Lubbock</city>, <state>TX</state>,&#xa0;<country country="us">United States</country></aff>
<aff id="aff4"><label>4</label><institution>PROJ-X, Inc.</institution>, <city>Cumming</city>, <state>GA</state>,&#xa0;<country country="us">United States</country></aff>
<aff id="aff5"><label>5</label><institution>Department of Animal Science, Texas A&amp;M University, College</institution>, <city>Station</city>, <state>TX</state>,&#xa0;<country country="us">United States</country></aff>
<aff id="aff6"><label>6</label><institution>Department of Animal and Food Science, Texas Tech University</institution>, <city>Lubbock</city>, <state>TX</state>,&#xa0;<country country="us">United States</country></aff>
<author-notes>
<corresp id="c001"><label>*</label>Correspondence: Jerrad F. Legako, <email xlink:href="mailto:jerrad.legako@ag.tamu.edu">jerrad.legako@ag.tamu.edu</email></corresp>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-26">
<day>26</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>7</volume>
<elocation-id>1763503</elocation-id>
<history>
<date date-type="received">
<day>08</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>16</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="rev-recd">
<day>15</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2026 Barker, Jackson, Richeson, Carroll, Burdick Sanchez, Broadway, Ducharme, Kerth, Hernandez and Legako.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Barker, Jackson, Richeson, Carroll, Burdick Sanchez, Broadway, Ducharme, Kerth, Hernandez and Legako</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-26">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Introduction</title>
<p>The present study evaluated oxidative stress indicators in plasma of beef calves supplemented with a rumen-protected methionine (L0 = receiving ration top-dressed with a ground corn carrier, L1 = receiving ration top-dressed with 10.0 g of rumen-protected methionine supplement in a ground corn carrier, L2 = receiving ration top-dressed with 20.0 g of rumen-protected methionine supplement in a ground corn carrier) and administered lipopolysaccharide (LPS). An additional objective evaluated the effect of LPS on plasma metabolites.</p>
</sec>
<sec>
<title>Methods</title>
<p>Following an initial feeding period (40 d), steers (n = 32; 379 kg &#xb1; 30.7) were intravenously administered LPS (0.25 &#x3bc;g/kg BW). Blood was collected via jugular catheter at -2, 0, 2, 4, 6, 8, 10, 12, 18, 24, 36, and 48 h relative to LPS administration (0 h). Plasma was analyzed for amino acid (AA) concentrations, ferric-reducing antioxidant power (FRAP), thiobarbituric reactive substances (TBARS), and reactive oxygen species (ROS). Metabolomic analysis occurred for control cattle at -2, 2, and 8 h.</p>
</sec>
<sec>
<title>Results and discussion</title>
<p>Plasma AA asparginine and methionine were increased with supplementation (<italic>P</italic> &lt; 0.01). The greatest FRAP values were observed at -2, 0, 2, 36, and 48 h (<italic>P</italic> &lt; 0.001). At 6 and 8 h, FRAP decreased to their lowest values (<italic>P</italic> &lt; 0.001). Amount of TBARS increased at 2 h but declined at 4h (<italic>P</italic> &lt; 0.001). A treatment &#xd7; time interaction occurred for ROS (<italic>P</italic> &lt; 0.001). At 2 h, ROS was greatest in L0 cattle, least in L2, and intermediate in L1 but declined at 4 h in all treatments (<italic>P</italic> &lt; 0.001). Values peaked at 6 h for L1 and L2 cattle, followed by a decline at 8 h (<italic>P</italic> &lt; 0.001). Values for L0 cattle were similar from 4 to 6 h (<italic>P</italic> = 0.371) but increased at 8 h (<italic>P</italic> &lt; 0.001). Finally, L0 plasma metabolites present at -2 h segregated from those present at 2 and 8 h (<italic>P</italic> &lt; 0.05). Differences were primarily driven by taurocholic acid, LysoPE, butyric acid, acitretin, and tauromuricholic acid. These data demonstrate that LPS may alter oxidative stress indicators and plasma metabolites. However, methionine supplementation may mitigate oxidative stress.</p>
</sec>
</abstract>
<kwd-group>
<kwd>lipopolysaccharide</kwd>
<kwd>metabolomics</kwd>
<kwd>methionine</kwd>
<kwd>oxidative stress</kwd>
<kwd>receiving period</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. This study was funded by Adisseo USA Inc.</funding-statement>
</funding-group>
<counts>
<fig-count count="5"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="79"/>
<page-count count="12"/>
<word-count count="7156"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Animal Physiology and Management</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>The receiving period is a stressful event in the life of beef cattle, where cattle are subjected to transportation, comingling, potential pathogen exposure, and decreased feed intake (<xref ref-type="bibr" rid="B23">Duff and Galyean, 2007</xref>). Combined, these stressors ultimately contribute to decreased immune defenses, leaving cattle vulnerable to illnesses such as Bovine Respiratory Disease (BRD; <xref ref-type="bibr" rid="B55">Rice et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B69">Taylor et&#xa0;al., 2010</xref>). Continuous activation of the immune response creates a substantial stress scenario <italic>in vivo</italic>, further contributing over time to the suppression of cellular immunity (<xref ref-type="bibr" rid="B46">Nui et&#xa0;al., 2022</xref>). As the body attempts to remedy illness through activation of the immune response, oxidative bursts, as a product of phagocytosis by immune cells, result in a rapid increase of reactive oxygen species (ROS) which disrupt a key balance between endogenous antioxidants and pro-oxidants (<xref ref-type="bibr" rid="B29">Gorski et&#xa0;al., 2012</xref>).</p>
<p>Methionine is an essential but often considered a limiting amino acid in the diet of cattle due to rumen degradation and/or composition of feedstuffs (Richardson and Hatfield, 1978; <xref ref-type="bibr" rid="B73">Waterman et&#xa0;al., 2012</xref>). However, when accessibility is achieved, methionine has been shown to not only improve and regulate some metabolic processes but also mitigate oxidative stress through the activation of vital endogenous antioxidants, like glutathione (<xref ref-type="bibr" rid="B39">Lopes et&#xa0;al., 2019</xref>). Using ruminally-protected methionine, research has indicated benefits to the intestinal environment, improved milk production, and increased immune benefits in all ages as an inflammation modulator (<xref ref-type="bibr" rid="B1">Abdelmegeid et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B5">Barker et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B45">Motta et&#xa0;al., 2025</xref>). Nonetheless, the benefits of a ruminally-protected methionine supplement have not been evaluated thoroughly in beef cattle, specifically during the receiving period.</p>
<p>Oxidative stress occurs in the body with an imbalance between pro-oxidants and antioxidants, which favors pro-oxidants. Severe oxidative stress has been demonstrated to reduce feed efficiency, increase protein degradation, and further contribute to a reduction in meat quality (<xref ref-type="bibr" rid="B9">Bottje et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B57">Russell et&#xa0;al., 2016</xref>). Additionally, metabolomic analysis has risen in popularity in recent years as a way to understand metabolic differences and to classify, metabolic changes as potential biomarkers, which may further be used to define oxidative stress. Therefore, the primary objective of this study was to determine the oxidative status in the plasma of receiving beef calves following lipopolysaccharide administration to individual calves supplemented with a methionine analogue and to explore the novelty of metabolomics analyses in beef cattle. A second objective sought to explore the plasma metabolites expressed in response to LPS administration.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Animal management and treatment</title>
<p>All procedures were approved by the West Texas A&amp;M University Institutional Animal Care and Use Committee (Protocol Number: 2021.03.001) and the Livestock Issues Research Unit (IACUC Protocol # 2119S). On d -1, cattle entering the West Texas A&amp;M University Research Feedlot were processed following procedures described by <xref ref-type="bibr" rid="B5">Barker et&#xa0;al. (2024)</xref>. In brief, weaned beef steers (n = 65; 287.1 &#xb1; 45.7 kg) were processed, weighed, and received a growth implant, visual, and electronic ID tag, as well as vaccinations in accordance with West Texas A&amp;M University health protocol. Steers were stratified by initial BW and allocated randomly into pens (6 pens; 10 steers/pen; 2 pen/treatment), and further randomly assigned to 1 of 3 treatments: (1) standard receiving ration top-dressed with a ground corn carrier (L0; n = 21), (2) standard receiving ration top-dressed with 10.0 g of rumen-protected methionine supplement (MetaSmart, Adisseo USA Inc., Alpharetta, GA; L1; n = 22) per head per day in a ground corn carrier, or (3) standard receiving ration top-dressed with 20.0 g of rumen-protected methionine supplement (MetaSmart, Adisseo USA Inc., Alpharetta, GA; L2; n = 22) per head per day in a ground corn carrier. Methionine supplements were top-dressed with a ground corn carrier, whereas the L1 treatment group received 2.2 g/steer/d of methionine, while the L2 group received 4.4 g/steer/d of methionine. Cattle were allowed <italic>ad libitum</italic> access to feed and water. Supplementation treatment doses were selected based on recommendations from the manufacturer. Unconsumed feed was collected and weighed to determine a daily DMI from dry matter samples. Feed and watering procedures are further described in <xref ref-type="bibr" rid="B5">Barker et&#xa0;al. (2024)</xref>. Feeding and management practices conducted from d -1 to d 40 were designed to simulate the receiving period commonly experienced by transitioning cattle (<xref ref-type="bibr" rid="B34">Johnson, 2022</xref>).</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Lipopolysaccharide administration</title>
<p>Parameters of LPS administration and sample collections were conducted following the methods described in depth by <xref ref-type="bibr" rid="B5">Barker et&#xa0;al. (2024)</xref>. On d 35, a subset of calves (n = 32; L0 = 10, L1 = 11, L2 = 11) were selected based on temperament according to pen score (<xref ref-type="bibr" rid="B30">Hammond et&#xa0;al., 1996</xref>) in order to select for the most intermediate calves (i.e., removing extremely calm and temperamental steers). Further, calves selected for immune stimulation using LPS administration were similar in BW, had not been treated previously for illness, and were visually healthy. On d 40, the selected steers were transported to the Livestock Issues Research Unit&#x2019;s Bovine Immunology Research and Development Complex, USDA (approximately 165 km). Upon arrival, cattle were placed in covered, outdoor holding pens separated by treatment, with access to water and previously assigned feed rations.</p>
<p>On d 41, cattle were weighed and restrained via halter in a squeeze chute to allow for fitting of indwelling rectal temperature (RT) recording devices (<xref ref-type="bibr" rid="B54">Reuter et&#xa0;al., 2010</xref>) that measure RT continuously at 5-min intervals, and indwelling jugular vein catheters (<xref ref-type="bibr" rid="B54">Reuter et&#xa0;al., 2010</xref>). Steers were then moved into individual stalls (2.5 m &#xd7; 6 m) in an enclosed barn where they remained for the duration of the LPS administration and sample collection period. Cattle were fed once daily their respective treatments and allowed access to feed until 1 h prior to collection of the first blood sample, with <italic>ad libitum</italic> access to water throughout the study. On d 42, cattle were administered LPS intravenously (0.25 &#xb5;g/kg BW LPS from <italic>E. coli</italic> O111:B4; Sigma Aldrich, St. Louis, MO, USA) at 0 h. Whole blood samples (n = 4) were collected at 2 h intervals from -2 to 12 h and every 12 h from 18 to 48 h relative to LPS administration at 0 h. Whole blood samples were collected in evacuated blood collection tubes containing lithium-heparin for plasma isolation and were immediately centrifuged at 1250 &#xd7; g for 20 min at 4 &#xb0;C. Isolated plasma was allocated to microcentrifuge tubes and stored at -80 &#xb0;C until subsequent analysis. Data on the analysis of the acute phase response to LPS administration has been reported by <xref ref-type="bibr" rid="B5">Barker et&#xa0;al. (2024)</xref>.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Plasma amino acid analysis</title>
<p>Plasma amino acids were evaluated on collected plasma samples following the methods described by <xref ref-type="bibr" rid="B31">Hoppmann and Arriola Apelo (2024)</xref>. In brief, plasma proteins were precipitated on acetonitrile, with precipitates transferred to glass vials. Supernatants were further buffered with sodium borate and derivatized with 9-fluorenylmethoxycarbonyl chloride. The resulting analytes were isolated by solid-phase extraction and further separated by reverse-phase liquid chromatography. Quality control samples were prepared alongside samples to ensure peak areas were with the acceptable range for each amino acid in plasma.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Ferric reducing antioxidant power analysis</title>
<p>The ferric-reducing antioxidant power (FRAP) was evaluated on collected plasma samples using a quantitative assay kit (OxiSelect, Cell BioLabs Inc., San Diego, CA). An iron standard was used for comparison for quantifying concentrations of ferrous iron within unknown samples. Plasma samples were thawed and evaluated for ferric-reducing antioxidant power according to direct FRAP procedures described by <xref ref-type="bibr" rid="B7">Benzie and Strain (1996)</xref>. Standards and samples were evaluated in duplicate on 96-well plates and measured via spectrophotometer at 540 nm. Intra-assay CV was accepted at &#x2264; 5%.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Thiobarbituric reactive substances analysis</title>
<p>Thiobarbituric reactive substances (TBARS) were evaluated on collected plasma samples using a quantitative assay kit (OxiSelect, Cell BioLabs, Inc., San Diego, CA). A malondialdehyde (MDA) equivalent standard was used for comparison for quantifying concentrations of MDA and levels of oxidation within unknown samples. Plasma samples were thawed and evaluated for reactive substances according to direct TBARS procedures described in the kit protocol. Standards and samples were evaluated in duplicate on 96-well plates and measured via spectrophotometer at 532 nm. Intra-assay CV was accepted at &#x2264; 10%.</p>
</sec>
<sec id="s2_6">
<label>2.6</label>
<title>Reactive oxygen species analysis</title>
<p>Reactive oxygen species (ROS) includes a variety of compounds which may lead to the oxidation of biological samples. This analysis evaluated hydrogen peroxide concentrations in collected plasma samples using a quantitative fluorometric assay kit (OxiSelect, Cell BioLabs, Inc., San Diego, CA). A hydrogen peroxide standard was used for comparison in quantifying concentrations of 2mM hydrogen peroxide solution as the primary ROS within unknown samples. Collected plasma samples were thawed and evaluated for hydrogen peroxide concentrations according to direct procedures described by the assay kit protocol. Samples were evaluated fluorometrically in quadruples and free radical content was determined by comparison to a 2&#x2019;, 7&#x2019;- dichlorodihydrofluorescein (DCF) and hydrogen peroxide standard curves. Samples were read on 96-well plates via a standard fluorescence plate reader at 480 nm excitation/530 nm emission. Intra-assay CV were accepted at &#x2264; 5%.</p>
</sec>
<sec id="s2_7">
<label>2.7</label>
<title>Metabolomics</title>
<p>Samples were selected for metabolomic analysis from control (L0) calves at -2, 2, and 8 h relative to LPS administration based on oxidative stress markers determined using results from FRAP, TBARS, and ROS assays. Plasma was extracted with methanol following the procedure of <xref ref-type="bibr" rid="B72">Want et&#xa0;al. (2006)</xref>. Briefly, 400 &#xb5;L of plasma was extracted with 800 &#xb5;L of methanol, centrifuged for 10 min at 14000 &#xd7; g, decanted into a new centrifuge tube and dried under a stream of nitrogen gas. The pellet was resuspended with 400 &#xb5;L of a solution containing 95 parts HPLC water and 5 parts acetonitrile.</p>
<p>Reverse-phase liquid chromatography-electrospray ionization-high resolution mass spectrometry (quadrupole time-of-flight; model 6545 HPLC-qTOF, Agilent Technologies, Santa Clara, CA) was used to separate and detect metabolites (50 to 1,400 <italic>m/z</italic>) with blanks (subtracted from the samples) and QC samples (treatment quality control consisting of a pooled treatment sample). The mobile phase consisted of 95:5:0.1 parts HPLC water:acetonitrile:formic acid for solution A and 100:0.1 parts acetonitrile:formic acid for solution B. The sample (10 &#xb5;L) was injected with a flow of 250 &#xb5;L/min in positive ion mode through an Agilent Poroshell 120 EC-C18 3.0 x 100 mm, 2.7 &#xb5;m column. The mobile phase was run as solution B 5% for 2 minutes, 90% for 62 minutes, and 5% for 3 minutes with the balance of each consisting of solution A. The mass spectrometer was run in Auto MS/MS, positive ion mode with fixed collision energies of 10, 20, and 40 mV. After completion, all features were integrated using MassHunter Qualitative Analysis. Metabolites were log<sub>10</sub>-transformed and analyzed using MassHunter Qualitative Workflow, Profinder, and Mass Profiler Professional software (v. B.08, Agilent Technologies, Santa Clara, CA). Compound groups were filtered using the following criterion: absolute peak height of 1200, retention time window of 0.2 min, and molecular feature extraction score of greater than 80.</p>
</sec>
<sec id="s2_8">
<label>2.8</label>
<title>Statistical analyses</title>
<p>Plasma amino acid concentrations were analyzed using the MIXED procedure of SAS (Version 9.4, SAS Institute, Cary, NC) specific for repeated measures. Fixed effects were treatment, time, and their interaction and steer was the experimental unit. The covariance structure that resulted in the smallest Akaike Information Criterion (AIC) and Schwartz Bayesian criteria were selected for each analysis. Significant effects were determined at <italic>&#x3b1;</italic> = 0.05, with tendencies established at <italic>&#x3b1;</italic> &gt; 0.05, but &lt; 0.10. When significant, fixed effects were separated using the PDIFF option in SAS. Data are presented as the LSM &#xb1; SEM.</p>
<p>Data accumulated for FRAP, TBARS, and ROS assays were averaged for each sample and analyzed as repeated measures using the GLIMMIX procedure of SAS. Methionine feeding treatment and time served as main effects. As cattle were housed and managed individually throughout the LPS administration phase of this study, individual animal served as the experimental unit as reported previously (<xref ref-type="bibr" rid="B5">Barker et&#xa0;al., 2024</xref>). The covariance structure showing the lowest AIC was used. Probability values (<italic>P</italic>-values) less than or equal to <italic>&#x3b1;</italic> = 0.05 were considered significant. The Kenward-Rogers adjustment was used to estimate denominator degrees of freedom.</p>
<p>Mass spectral features from metabolomic analysis were annotated using MS-DIAL. Total ion count intensities were median normalized, log<sub>10</sub> transformed, and analyzed using MetaboAnalyst v.5. Partial least squares-discriminant analysis (PLS-DA), agglomerative clustering (AHC), and an analysis of variance (ANOVA) with a false discovery rate (FDR) adjusted <italic>P</italic>&#xa0;&lt; 0.05 were conducted. Of the 245 annotated metabolites, 155 differed between time points. Partial Least Squares- Discriminant Analysis (PLS-DA) and variable importance in projection (VIP) plot were used to visualize treatments and identify compounds driving discrimination between groups. Hierarchical clustering using the Ward method was used to determine metabolite differences present following LPS administration in cattle. Pathway analyses were also conducted via KEGG <italic>Bos Taurus</italic> pathway library.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Plasma amino acid analysis</title>
<p>All amino acids changed over time (<italic>P</italic> &lt; 0.01) in response to LPS administration (<xref ref-type="table" rid="T1"><bold>Table&#xa0;1</bold></xref>). There was no treatment (<italic>P</italic> &#x2265; 0.11) nor treatment &#xd7; time interaction (<italic>P</italic> &#x2265; 0.15) for alanine, aspartic acid, glutamine, glutamic acid, glycine, histidine, isoleucine, leucine, proline, tryptophan, tyrosine and valine. There was a tendency (<italic>P</italic> = 0.06) for a treatment effect on arginine, such that the L2 treatment had greater arginine concentrations than L0 (<italic>P</italic> = 0.02), and L2 calves tended (<italic>P</italic> = 0.09) to have greater arginine concentrations than L1 calves. However, there was no treatment &#xd7; time interaction (<italic>P</italic> = 0.15) for arginine concentrations. There was a treatment effect (<italic>P</italic> &lt; 0.01) for concentrations of asparagine, such that L1 and L2 calves had greater concentrations than L0 calves (<italic>P</italic> &#x2264; 0.01), while concentrations from L1 and L2 calves did not differ (<italic>P</italic> = 0.11). There was not treatment &#xd7; time interaction for asparagine (<italic>P</italic> = 0.16). There was no treatment effect for lysine (<italic>P</italic> = 0.21); however, there was a tendency (<italic>P</italic> = 0.10) for a treatment &#xd7; time interaction. Specifically, L0 calves had greater lysine concentrations than L1 calves at 36 h post-LPS (<italic>P</italic> = 0.02), while L2 calves had greater lysine concentrations than L1 calves from 24 to 48 h post-LPS (<italic>P</italic> &#x2264; 0.02). There was a treatment &#xd7; time interaction (<italic>P</italic> = 0.04) for methionine concentrations. Specifically, L1 calves had greater methionine concentrations than L0 calves at 0 and 10 h post-LPS (<italic>P</italic> &#x2264; 0.03), while L2 calves had greater methionine concentrations than L0 calves at 10, 12, 24 and 48 h post-LPS (<italic>P</italic> &#x2264; 0.02). Additionally, L2 calves had greater methionine concentrations than L1 calves from 24 to 48 h post-LPS (<italic>P</italic> &#x2264; 0.04). Methionine concentrations were greater (treatment effect: P &lt; 0.01) in L2 than L1 and L0 calves (<italic>P</italic> &#x2264; 0.03), while concentrations did not differ between L0 and L1 calves (<italic>P</italic> = 0.21). There was no treatment effect on concentrations of phenylalanine (<italic>P</italic> = 0.16); however, there was a tendency for a treatment &#xd7; time interaction (<italic>P</italic> = 0.09). Specifically, phenylalanine concentrations were greater in L1 versus L0 calves from 8 to 10 h post-LPS (<italic>P</italic> &#x2264; 0.05) and were greater in L2 versus L0 calves from 10 to 12 h post-LPS (<italic>P</italic> &#x2264; 0.01). There was a treatment effect for serine concentrations (<italic>P</italic> = 0.02), such that concentrations were greater in L1 and L2 calves compared to L0 calves (<italic>P</italic> &#x2264; 0.04), while concentrations did not differ between L1 and L2 calves (<italic>P</italic> = 0.50). Further, there was a tendency for a treatment &#xd7; time interaction (<italic>P</italic>&#xa0;= 0.06) for serine concentrations, such that serine concentrations were greater in L1 than L2 calves at 0, 2, 6, 8, 10, 12 and 18 h post-LPS (<italic>P</italic> &#x2264; 0.04), were greater in L2 calves than L0 calves at 8 and 10 h post-LPS (<italic>P</italic> &#x2264; 0.05), and were greater in L1 than L2 calves at 0 h (<italic>P</italic> = 0.03). There was a tendency (<italic>P</italic> = 0.08) for a treatment effect on concentrations of threonine, where L1 and L2 calves had greater threonine concentrations than L0 calves (<italic>P</italic> = 0.05), while L1 and L2 calves did not differ (<italic>P</italic> = 0.95). Additionally, there was a tendency for a treatment &#xd7; time interaction (<italic>P</italic> = 0.10) for threonine concentrations, where concentrations were greater in L1 and L2 versus L0 calves at 8, 10, and 12 h post-LPS (<italic>P</italic> &#x2264; 0.05).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Summary of the effect of methionine supplementation on amino acid concentrations in plasma of cattle administered lipopolysaccharide (LPS; 0.25 &#xb5;g/kg BW).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left"/>
<th valign="middle" colspan="3" align="center">Treatment<sup>1</sup></th>
<th valign="middle" align="center"/>
<th valign="middle" colspan="3" align="center"><italic>P</italic>-value</th>
</tr>
<tr>
<th valign="middle" align="left">Amino acid, &#xb5;M</th>
<th valign="middle" align="center">L0</th>
<th valign="middle" align="center">L1</th>
<th valign="middle" align="center">L2</th>
<th valign="middle" align="center">SEM</th>
<th valign="middle" align="center">Treatment</th>
<th valign="middle" align="center">Time<sup>2</sup></th>
<th valign="middle" align="center">Interaction</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">Alanine</td>
<td valign="middle" align="left">187.37</td>
<td valign="middle" align="left">181.91</td>
<td valign="middle" align="left">190.24</td>
<td valign="middle" align="left">7.531</td>
<td valign="middle" align="left">0.71</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.19</td>
</tr>
<tr>
<td valign="middle" align="left">Arginine</td>
<td valign="middle" align="left">71.20</td>
<td valign="middle" align="left">74.10</td>
<td valign="middle" align="left">81.07</td>
<td valign="middle" align="left">2.971</td>
<td valign="middle" align="left">0.06</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.15</td>
</tr>
<tr>
<td valign="middle" align="left">Asparagine</td>
<td valign="middle" align="left">20.46<sup>b</sup></td>
<td valign="middle" align="left">23.61<sup>a</sup></td>
<td valign="middle" align="left">25.54<sup>a</sup></td>
<td valign="middle" align="left">0.858</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.16</td>
</tr>
<tr>
<td valign="middle" align="left">Aspartic Acid</td>
<td valign="middle" align="left">3.64</td>
<td valign="middle" align="left">3.62</td>
<td valign="middle" align="left">6.84</td>
<td valign="middle" align="left">0.222</td>
<td valign="middle" align="left">0.71</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">1.00</td>
</tr>
<tr>
<td valign="middle" align="left">Glutamine</td>
<td valign="middle" align="left">255.75</td>
<td valign="middle" align="left">266.33</td>
<td valign="middle" align="left">265.15</td>
<td valign="middle" align="left">6.909</td>
<td valign="middle" align="left">0.49</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.19</td>
</tr>
<tr>
<td valign="middle" align="left">Glutamic Acid</td>
<td valign="middle" align="left">58.89</td>
<td valign="middle" align="left">60.65</td>
<td valign="middle" align="left">59.39</td>
<td valign="middle" align="left">2.820</td>
<td valign="middle" align="left">0.90</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.98</td>
</tr>
<tr>
<td valign="middle" align="left">Glycine</td>
<td valign="middle" align="left">202.63</td>
<td valign="middle" align="left">231.23</td>
<td valign="middle" align="left">225.46</td>
<td valign="middle" align="left">9.887</td>
<td valign="middle" align="left">0.11</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.68</td>
</tr>
<tr>
<td valign="middle" align="left">Histidine</td>
<td valign="middle" align="left">52.49</td>
<td valign="middle" align="left">50.97</td>
<td valign="middle" align="left">55.08</td>
<td valign="middle" align="left">1.484</td>
<td valign="middle" align="left">0.14</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.34</td>
</tr>
<tr>
<td valign="middle" align="left">Isoleucine</td>
<td valign="middle" align="left">80.50</td>
<td valign="middle" align="left">84.32</td>
<td valign="middle" align="left">87.73</td>
<td valign="middle" align="left">4.078</td>
<td valign="middle" align="left">0.45</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.30</td>
</tr>
<tr>
<td valign="middle" align="left">Leucine</td>
<td valign="middle" align="left">131.78</td>
<td valign="middle" align="left">1239.07</td>
<td valign="middle" align="left">146.39</td>
<td valign="middle" align="left">6.260</td>
<td valign="middle" align="left">0.26</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.51</td>
</tr>
<tr>
<td valign="middle" align="left">Lysine</td>
<td valign="middle" align="left">79.30</td>
<td valign="middle" align="left">74.12</td>
<td valign="middle" align="left">84.49</td>
<td valign="middle" align="left">4.236</td>
<td valign="middle" align="left">0.21</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.10</td>
</tr>
<tr>
<td valign="middle" align="left">Methionine</td>
<td valign="middle" align="left">16.81<sup>b</sup></td>
<td valign="middle" align="left">17.96<sup>b</sup></td>
<td valign="middle" align="left">20.00<sup>a</sup></td>
<td valign="middle" align="left">0.648</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.04</td>
</tr>
<tr>
<td valign="middle" align="left">Phenylalanine</td>
<td valign="middle" align="left">56.92</td>
<td valign="middle" align="left">60.56</td>
<td valign="middle" align="left">61.79</td>
<td valign="middle" align="left">1.860</td>
<td valign="middle" align="left">0.16</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.09</td>
</tr>
<tr>
<td valign="middle" align="left">Proline</td>
<td valign="middle" align="left">49.05</td>
<td valign="middle" align="left">52.17</td>
<td valign="middle" align="left">52.76</td>
<td valign="middle" align="left">1.484</td>
<td valign="middle" align="left">0.17</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.35</td>
</tr>
<tr>
<td valign="middle" align="left">Serine</td>
<td valign="middle" align="left">53.13<sup>b</sup></td>
<td valign="middle" align="left">64.97<sup>a</sup></td>
<td valign="middle" align="left">62.17<sup>a</sup></td>
<td valign="middle" align="left">3.047</td>
<td valign="middle" align="left">0.02</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.06</td>
</tr>
<tr>
<td valign="middle" align="left">Threonine</td>
<td valign="middle" align="left">45.41</td>
<td valign="middle" align="left">52.91</td>
<td valign="middle" align="left">53.13</td>
<td valign="middle" align="left">2.711</td>
<td valign="middle" align="left">0.08</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.10</td>
</tr>
<tr>
<td valign="middle" align="left">Tryptophan</td>
<td valign="middle" align="left">36.96</td>
<td valign="middle" align="left">38.13</td>
<td valign="middle" align="left">39.76</td>
<td valign="middle" align="left">1.828</td>
<td valign="middle" align="left">0.54</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.18</td>
</tr>
<tr>
<td valign="middle" align="left">Tyrosine</td>
<td valign="middle" align="left">85.26</td>
<td valign="middle" align="left">88.58</td>
<td valign="middle" align="left">85.82</td>
<td valign="middle" align="left">3.941</td>
<td valign="middle" align="left">0.81</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.83</td>
</tr>
<tr>
<td valign="middle" align="left">Valine</td>
<td valign="middle" align="left">215.04</td>
<td valign="middle" align="left">205.28</td>
<td valign="middle" align="left">210.55</td>
<td valign="middle" align="left">11.001</td>
<td valign="middle" align="left">0.81</td>
<td valign="middle" align="left">&lt;0.01</td>
<td valign="middle" align="left">0.34</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p><sup>1</sup> Methionine treatment types varied by supplementation level, where L0 = 0 g methionine/hd/d, L1 = 10 g methionine/hd/d, and L2 = 20 g methionine/hd/d.</p></fn>
<fn>
<p><sup>2</sup>Blood collections occurred for all animals at -2, 0, 2, 4, 6, 8, 10, 12, 18, 24, 36, and 48 h in reference to LPS application immediately following blood collection at 0 h.</p></fn>
<fn>
<p><sup>a-b</sup>Means lacking common superscripts differ (<italic>P</italic> &lt; 0.05).</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Ferric-reducing antioxidant power analysis</title>
<p>No interaction was present between methionine treatment and time from LPS administration (<italic>P</italic> = 0.16) on concentrations of Fe<sup>2+</sup>. However, there was a main effect of time on concentrations of Fe<sup>2+</sup> (<italic>P</italic> &lt; 0.001; <xref ref-type="fig" rid="f1"><bold>Figure&#xa0;1</bold></xref>). Initial antioxidant capacity did not differ among -2 h, 0 h, and 2 h relative to the LPS administration at 0 h (<italic>P</italic> &#x2265; 0.27). Antioxidant capacity decreased 4 h post-LPS, with the lowest antioxidant capacity observed at 8 h (<italic>P</italic> &lt; 0.001). While the data showed a slight increase in Fe<sup>2+</sup> concentrations at 10 and 12 h post-LPS (<italic>P</italic> = 0.05), antioxidant capacity did not return to initial values until 48 h post-LPS (<italic>P</italic> = 0.91).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Ferric Reducing Antioxidant Power (FRAP) concentrations (&#x3bc;M Fe<sup>2+</sup>) in beef calf plasma across time (<italic>P</italic> &lt; 0.001) in a lipopolysaccharide (LPS; 0.25 &#xb5;g/kg BW) challenge. Pooled averages from cattle receiving three levels of Methionine treatment (0, 10, or 20 g methionine/hd/d). *LS means with common symbol differ from initial concentrations at &#x2013;2 and 0 h (<italic>P</italic> &lt; 0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fanim-07-1763503-g001.tif">
<alt-text content-type="machine-generated">Line graph showing concentrations of Fe&#xb2;&#x207a; in micromolar (&#xb5;M) from -2 to 48 hours after LPS challenge. Initial concentration increases to approximately 280 &#xb5;M, then decreases to about 200 &#xb5;M by 18 hours, and rises again to approximately 280 &#xb5;M at 48 hours. Error bars and asterisks highlight significant differences at various points.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Thiobarbituric reactive substances analysis</title>
<p>No interaction was present between methionine treatment and time on MDA concentration (<italic>P</italic> = 0.345). Still, there was a main effect of time on MDA concentrations (<italic>P</italic> &lt; 0.001; <xref ref-type="fig" rid="f2"><bold>Figure&#xa0;2</bold></xref>). Concentrations of MDA did not differ from -2 to 0 h prior to LPS administration (<italic>P</italic> = 0.29). However, 2 h post-LPS, MDA concentrations increased drastically, reaching peak concentrations (<italic>P</italic> &lt; 0.001). Following 2 h post-LPS, MDA concentration declined, was similar to initial values at 4 h (<italic>P</italic> &#x2264; 0.99), but continued to decline below initial values from 6 h to 36 h (<italic>P</italic> &#x2264; 0.05). Concentrations increased again at 48 h post-LPS and were similar to initial values (<italic>P</italic> = 0.18).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Malondialdehyde (MDA) concentrations in beef calf plasma across time (<italic>P</italic> &lt; 0.001) in a lipopolysaccharide (LPS; 0.25 &#xb5;g/kg BW) challenge. Pooled averages from cattle receiving three levels of Methionine treatment (0, 10, or 20 g methionine/hd/d). *LS means with common symbol differ from initial concentrations at &#x2013;2 and 0 h (<italic>P</italic> &lt; 0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fanim-07-1763503-g002.tif">
<alt-text content-type="machine-generated">Line graph showing the concentration of MDA in micromoles per liter over time in hours from LPS challenge. The concentration peaks at about 40 micromoles at 2 hours, then decreases, reaching a low around 10 micromoles at 24 hours, followed by a slight increase to 15 micromoles at 48 hours. Error bars represent variability, and asterisks indicate significance.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Reactive oxygen species analysis</title>
<p>An interaction between time and methionine treatment occurred for ROS in plasma samples (<italic>P</italic> &lt; 0.001; <xref ref-type="fig" rid="f3"><bold>Figure&#xa0;3</bold></xref>). All treatments were similar in hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) concentration at -2 and 0 h before LPS administration (<italic>P</italic> = 1.00). An increase in H<sub>2</sub>O<sub>2</sub> occurred 2 h post-LPS, with the greatest concentration of H<sub>2</sub>O<sub>2</sub> occurring in L0 cattle, the least in L2, and intermediate concentrations in L1 (<italic>P</italic> &lt; 0.001). At 4 h post-LPS, concentrations for all treatments were similar to initial values (<italic>P</italic> = 1.00) but concentrations increased again at 6 h post-LPS for L1 and L2 samples (<italic>P</italic> &lt; 0.001). At 8 h, concentrations of H<sub>2</sub>O<sub>2</sub> for L1 and L2 cattle decreased to initial values (<italic>P</italic> = 1.00). However, L0 cattle showed a delay in response, increasing in H<sub>2</sub>O<sub>2</sub> concentrations 8 h post-LPS (<italic>P</italic> &lt; 0.001) before declining again at 10 h. All treatments returned to initial values at 10 h post-LPS and did not increase again for the remainder of the study (<italic>P</italic> = 1.00).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>The interaction (<italic>P</italic> &lt; 0.001) of methionine treatment level and time from lipopolysaccharide (LPS; 0.25 &#xb5;g/kg BW) administration on reactive oxygen species (ROS) concentrations (&#x3bc;M Hydrogen Peroxide) in plasma. Methionine treatment types varied by level, where L0 = 0 g methionine/hd/d, L1 = 10 g methionine/hd/d, and L2 = 20 g methionine/hd/d. (a&#x2013;c) Means lacking common superscripts differ (<italic>P</italic> &lt; 0.05).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fanim-07-1763503-g003.tif">
<alt-text content-type="machine-generated">Line graph showing hydrogen peroxide concentration in micromolar over time, measured in hours after LPS challenge. Lines L0, L1, and L2 are represented by dashed with circles, solid with squares, and solid with triangles, respectively. Peaks occur at 2, 8, and 18 hours, with notable differences in concentration indicated by letters a, b, and c.</alt-text>
</graphic></fig>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Metabolomics</title>
<p>Hierarchal clustering was used to determine differences across time points -2, 2, and 8 h of the study (<xref ref-type="fig" rid="f4"><bold>Figure&#xa0;4</bold></xref>). Metabolites measured across these time points were most similar at 2 and 8 h post-LPS and created a clear cluster, with a clear separation from -2 h, which created its own individual cluster. A PLS-DA was used to draw clearer distinctions between time points, where PC1 explained 47.5% of the variation in the model (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5a</bold></xref>). Metabolites present at -2 h distinctly segregated themselves from those present at 2 and 8 h. Across PC2, only small differences occurred between 2 and 8 h. A VIP plot was used to determine the driving factors for the differences between time points (<xref ref-type="fig" rid="f5"><bold>Figure&#xa0;5</bold></xref>). Differences were driven primarily by 5 metabolites: taurocholic acid, LysoPE (18:3; Lysophosphatidylethanolamine), butyric acid, acitretin, and tauromuricholic acid. Pathway analyses further identified arginine biosynthesis, beta-alanine metabolism, arginine and proline metabolism, and histidine metabolism as the metabolic pathways likely driving differences in the data (FDR <italic>P</italic> &lt; 0.05).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Hierarchal clustering of detected metabolite differences present in plasma analyzed from cattle without supplementation (0 g methionine/hd/d) at -2, 2, and 8 h of lipopolysaccharide (LPS; 0.25 &#xb5;g/kg BW) challenge.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fanim-07-1763503-g004.tif">
<alt-text content-type="machine-generated">Heatmap illustrating data with values ranging from negative one point nine to two point two, color-coded from blue to red. The heatmap is organized by class and time, with classes indicated by different colors and times represented by purple, teal, and orange bars for two hours and eight hours. The y-axis lists various compounds. The x-axis shows numbered samples from one to sixty-two.</alt-text>
</graphic></fig>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p><bold>(a)</bold> Partial least squares- Discriminant analysis of metabolites present in plasma analyzed from cattle without supplementation (0 g methionine/hd/d) at -2, 2, and 8 h of lipopolysaccharide (LPS; 0.25 &#xb5;g/kg BW) challenge. Component 1 explains 47.5% of the variation in the model. <bold>(b)</bold> Variable importance in projection (VIP) plot scores of metabolite groups driving difference between time points at -2, 2, and 8 h of the challenge.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fanim-07-1763503-g005.tif">
<alt-text content-type="machine-generated">a. Scatter plot displaying data with three clusters at different times: -2 hours (red), 2 hours (green), and 8 hours (blue). Axis labels are Component 1 and Component 2.  b. Bar chart ranking various compounds by VIP scores, showing a color gradient from high (red) to low (blue) across the -2 hours, 2 hours, and 8 hours time points.</alt-text>
</graphic></fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>The role of the antioxidant defense system is to scavenge free radicals and destroy oxidants. However, a deficiency, or absolute depletion, of these defenses can contribute to oxidative stress (<xref ref-type="bibr" rid="B7">Benzie and Strain, 1996</xref>). The FRAP assay works by analyzing the ability of an antioxidant to donate hydrogen to an oxidant (<xref ref-type="bibr" rid="B32">Huang et&#xa0;al., 2005</xref>). In this case, it can be speculated that the decline in Fe <sup>2+</sup> beginning 2 h post-LPS administration is due to the sacrificial action of antioxidants working in the calf. As free radicals begin to increase in the body due to immune activation, the system is flooded with prooxidants. The antioxidants must then work to control propagation by donating hydrogen atoms and stopping the chain reaction (<xref ref-type="bibr" rid="B61">Sies, 1993</xref>).</p>
<p>The body is naturally equipped with endogenous antioxidants to fight off and scavenge for ROS. These natural antioxidants include glutathione, superoxide dismutase, glucose 6-phosphate dehydrogenase (G6PD), or other metal-binding proteins and vitamins (<xref ref-type="bibr" rid="B25">Ellah, 2010</xref>). Many of these systems work in a redox fashion, supplying each other with the means to successfully maintain ROS invasion by donation of hydrogen atoms or &#x201c;attacking&#x201d; free radicals. While a decline in antioxidant capacity, or ferric-reducing ability as in this study, may be seen as a negative result at first glance, it may be demonstrating the ability of this system to decrease ROS production following an acute phase response. While antioxidant capacity was slow to return to initial values, it did increase over time following LPS administration, displaying the body&#x2019;s natural defense system and return to homeostasis. <xref ref-type="bibr" rid="B77">Yi et&#xa0;al. (2025)</xref> observed increased endogenous antioxidant concentrations in serum, such as superoxide dismutase, glutathione, and catalase, following supplementation of guanidinoacetic acid and methionine. Similar results were seen in liver tissues with increased superoxide dismutase, glutathione, and catalase concentrations following supplementation. While the animals in Yi et&#xa0;al. were not exposed to any immune challenges, methionine may increase the body&#x2019;s ability to produce its own protection.</p>
<p>In general, TBARS serve as an adequate marker of lipid oxidation. However, when analyzed in plasma, TBARS serves as an indicator of oxidative stress and damage, rather than just oxidized lipids (<xref ref-type="bibr" rid="B3">Armstrong and Browne, 1994</xref>). In times of stress, whether psychological or physiological (i.e., illness, disease, parturition, etc.), the body is depleted of its natural antioxidants, leaving reactive metabolites and lipid oxidative products, such as MDA, to increase rapidly. When compared to the results of the FRAP assay, the inverse relationship is indicative of an imbalance between pro- and antioxidants, favoring pro-oxidants. This further suggests that the opportunity for oxidative stress was greatest early in the response to LPS, but restoration of antioxidant systems, as indicated by FRAP values, allowed a return to homeostasis for TBARS values. However, it is important to recognize that reactive metabolites, contributing to the production of MDA as a secondary lipid oxidation product, may also be generated by phagocytosis (Myolonas and Kouretas, 1999). While initial assumptions may suggest severe oxidative stress 2 h post-LPS administration, a portion of the MDA produced may be a necessary response to neutralizing the LPS present following administration.</p>
<p><xref ref-type="bibr" rid="B42">Miao et&#xa0;al. (2021)</xref> determined that birds kept in high-stocking-density housing had reduced activity of glutathione peroxidase and increased concentrations of MDA compared to those at normal stocking density. However, the study further recognized that with the addition of methionine, signs of oxidative stress were reduced as GSH/GSSG ratios increased. Further still, evaluation of methionine and oxidative stress in normal and intrauterine growth restricted (IUGR) piglets showed reduced MDA and cellular apoptosis with methionine supplementation (<xref ref-type="bibr" rid="B66">Su et&#xa0;al., 2017</xref>). An additional study evaluating broilers and stocking density found that methionine supplementation was similar to vitamin E, selenium, and astaxanthin as antioxidant sources in broiler diets, as it decreased MDA concentrations in muscle tissues, attenuating lipid oxidation (<xref ref-type="bibr" rid="B40">Magnuson et&#xa0;al., 2020</xref>).</p>
<p>While the current study did not find differences based on methionine supplementation on lipid oxidation products in plasma, it is worth noting that dietary supplementation of amino acids, like methionine, have been observed to suppress the side effects of lipid oxidation products like MDA (<xref ref-type="bibr" rid="B67">Sun et&#xa0;al., 2016</xref>). Methionine, and other sulfur-contain amino acids like cysteine, are capable of scavenging for free radicals, making them ideal possibilities in feeding regimens to reduce oxidative stress (<xref ref-type="bibr" rid="B4">Atmaca, 2004</xref>; <xref ref-type="bibr" rid="B19">Chen et&#xa0;al., 2013</xref>). Methionine can be converted into cysteine, which then serves as a precursor for the powerful antioxidant, glutathione (<xref ref-type="bibr" rid="B44">Miller, 2003</xref>). Further, MDA concentrations were reduced in both serum and liver samples of animals supplemented with a guanidinoacetic acid and methionine mix (<xref ref-type="bibr" rid="B77">Yi et&#xa0;al., 2025</xref>). Therefore, methionine supplementation may be of value when formulating a transition diet for receiving calves.</p>
<p>While still considered a ROS, hydrogen peroxide has less reactivity compared to other reactive species (<xref ref-type="bibr" rid="B35">Konno et&#xa0;al., 2021</xref>). Nonetheless, it has an extreme ability to pass through cell membranes, having greater potential for reacting with other compounds, such as iron and hemoglobin (<xref ref-type="bibr" rid="B41">Maurya, 2014</xref>). When white blood cells destroy pathogens in the body, they do so through oxidants such as nitric oxide, superoxide, and hydrogen peroxide (<xref ref-type="bibr" rid="B41">Maurya, 2014</xref>). Commonly referred to as the main contributors to oxidation, ROS play an important role in immune health and help the body fight toxins and disease (<xref ref-type="bibr" rid="B41">Maurya, 2014</xref>; <xref ref-type="bibr" rid="B6">Bassoy et&#xa0;al., 2021</xref>). This process explains the spike in ROS concentration following LPS administration and the return to basal concentrations following recovery. Production of ROS has been recognized as a result of normal cellular metabolism, arising from mitochondrial respiration, phagocytosis in an immune response, or Fenton Reactions. Furthermore, ROS are produced in a controlled manner for numerous physiological processes in the body, such as signaling of growth factors and cytokines, or even activating apoptosis (<xref ref-type="bibr" rid="B11">Brambilla et&#xa0;al., 2008</xref>). Nonetheless, when produced in excess, oxidative stress may occur, resulting in enzyme impairment, DNA damage, or lipid peroxidation (<xref ref-type="bibr" rid="B25">Ellah, 2010</xref>).</p>
<p>Methionine has often been considered a limiting amino acid in dairy cows, specifically when it comes to milk protein production, and may be added to the diet. In general, plant-based feeds are limited in methionine, and sufficient microbial breakdown of proteins in the rumen further add to the limitations of methionine without supplementation (<xref ref-type="bibr" rid="B10">Brake et&#xa0;al., 2013</xref>; <xref ref-type="bibr" rid="B39">Lopes et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B21">Costa et&#xa0;al., 2025</xref>). Rumen-protected methionine has been demonstrated to reduce oxidative stress in dairy cows during the transition period (<xref ref-type="bibr" rid="B76">Wu et&#xa0;al., 2013</xref>), as well as increase immune response capabilities. Further, methionine acts as a precursor for vital endogenous antioxidants, such as glutathione (<xref ref-type="bibr" rid="B14">Brosnan and Brosnan, 2006</xref>). In times of stress, disease, or other scenarios where insufficient redox reactions and antioxidant function occur, methionine may be vital to the diet. In the current study, calves receiving methionine appeared to show a milder reaction to LPS, based on ROS production alone. Additionally, calves receiving methionine had a second peak in ROS production sooner than control calves, suggesting a quicker recovery and increased immune response capability, as described by <xref ref-type="bibr" rid="B76">Wu et&#xa0;al. (2013)</xref>. As the receiving period for beef calves often results in significant immune challenges, as well as physical and psychological distress, rumen-protected methionine may provide an immunity boost, which protects against the production of ROS <italic>in vivo</italic>.</p>
<p>As metabolomic analyses have risen in popularity in recent years, and the database of metabolites continues to grow every day, control samples were selected in the current study in order to identify potential markers of inflammation that may be driving differences in response to LPS during the most crucial time points (as observed in the oxidative stress parameters measured). The time points selected were based on all other oxidative stress assays within the current study. Taurocholic acid was the primary driver of differences between pre- and post-LPS samples. Taurocholic acid is a bile salt composed of taurine (synthesized from methionine) and either primary or secondary bile acids (<xref ref-type="bibr" rid="B26">Elliot and Hyde, 1971</xref>; <xref ref-type="bibr" rid="B8">Blaschka et&#xa0;al., 2020</xref>). Bile acids are synthesized in the liver using cholesterol (<xref ref-type="bibr" rid="B56">Russel, 2003</xref>). As the functional component of bile, bile acids aid in the emulsification of nutritional components (<xref ref-type="bibr" rid="B56">Russel, 2003</xref>). While beneficial to digestion, high concentrations may be considered cytotoxic, although human studies show bile acids can be excreted in urine (<xref ref-type="bibr" rid="B8">Blaschka et&#xa0;al., 2020</xref>). Further, bile acids are responsible for cholesterol catabolism and approximately 50% of daily cholesterol turnover (<xref ref-type="bibr" rid="B33">Insull, 2006</xref>). In human and animal studies (<xref ref-type="bibr" rid="B70">Uchida et&#xa0;al., 1985</xref>; <xref ref-type="bibr" rid="B16">Brufau et&#xa0;al., 2010</xref>), bile acid concentrations have the potential to alter glucose homeostasis, where insulin and glucose play a role in modulation of bile acid synthesis (<xref ref-type="bibr" rid="B43">Michael et&#xa0;al., 2000</xref>; <xref ref-type="bibr" rid="B24">Duran-Sandoval et&#xa0;al., 2004</xref>). Bile acid synthesis may also help modulate glucose absorption in the intestine as deficient mice have exhibited delayed glucose absorption (<xref ref-type="bibr" rid="B71">Van Dijk et&#xa0;al., 2009</xref>).</p>
<p>Lysophospholipids (LPL) are derived from phospholipids by either enzyme or ROS induction (<xref ref-type="bibr" rid="B28">Fuchs et&#xa0;al., 2012</xref>). While the results of the current study appear to disagree, LPL tends to increase under inflammatory conditions (<xref ref-type="bibr" rid="B28">Fuchs et&#xa0;al., 2012</xref>). The formation of LPL result from cellular stress and phospholipid disturbances (<xref ref-type="bibr" rid="B48">Pena et&#xa0;al., 1997</xref>). Lysophospholipids are often produced and participate in the process of inflammation, including redness, swelling, heat, pain, and loss of function (<xref ref-type="bibr" rid="B60">Serhan et&#xa0;al., 2020</xref>). Interestingly, LysoPE (18:3) was greatest in cattle at -2 h and decreased from 2 and 8 h. This may suggest inflammation was greater prior to the challenge, and LPS application did not contribute to the presence of LysoPE (18:3), although difficult to determine completely based on the time points evaluated. Nonetheless, this increase in LysoPE may be as a result of the jugular catheter placed prior to the study. Lipophosphatidic acid (LPA) and other LPL have been evaluated as potential therapeutic targets, showing significant potential in modulating wound healing, specifically of endothelial cells (<xref ref-type="bibr" rid="B65">Sturm et&#xa0;al., 1999</xref>; <xref ref-type="bibr" rid="B37">Lee et&#xa0;al., 2000</xref>). Therefore, this increase may actually be specific and unrelated to the challenge itself. In human studies, reduced concentrations of LPL are associated with sepsis or poor outcomes following bacterial and viral infections (<xref ref-type="bibr" rid="B27">Frej et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B63">Song et&#xa0;al., 2020</xref>). Therefore, the current study contradicts published literature, although it would appear that the lack of LysoPE metabolites during the challenge may have been beneficial.</p>
<p>Butyric acid (BA) is a 4-carbon fatty acid influencing morphology, growth, and gene expression in mammals (<xref ref-type="bibr" rid="B52">Prasad, 1980</xref>). In a study evaluating the rumen conditions of cattle exposed to heat stress, isobutyric acid concentrations were increased (<xref ref-type="bibr" rid="B58">Sales et&#xa0;al., 2021</xref>). When supplemented in the diet, BA helps regulate performance and inflammation (<xref ref-type="bibr" rid="B74">Weber et&#xa0;al., 2014</xref>). <xref ref-type="bibr" rid="B74">Weber et&#xa0;al. (2014)</xref> further recognized that BA, when combined with humic acid, decreased serum cortisol by 62% in weanling pigs administered LPS. The aforementioned study also suggested the combination of BA and humic acid in the diet of pigs can mitigate oxidative stress. Butyric acid was most prevalent in samples at 2 h and intermediate in 8 h samples, suggesting a potential protective effect occurring during the response to LPS administration.</p>
<p>Pathway analyses further highlight the body&#x2019;s defenses against oxidative stress. Prior studies have recognized the function of arginine (Arg) against oxidative stress (<xref ref-type="bibr" rid="B64">Southern and Baker, 1983</xref>; <xref ref-type="bibr" rid="B68">Suschek et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B38">Lin et&#xa0;al., 2008</xref>), while <xref ref-type="bibr" rid="B79">Zheng et&#xa0;al. (2017)</xref> recognized Arg synthesis decreased in piglets experiencing oxidative stress. Arginine itself has been recognized as an important amino acid in the protection and development of the small intestine of pigs, specifically by improving villus morphology in the jejunum (<xref ref-type="bibr" rid="B79">Zheng et&#xa0;al., 2017</xref>). Arginine also had a protective effect on intestinal integrity, via attenuation of LPS-induced inflammation and inhibition of tight-junction protein downregulation (<xref ref-type="bibr" rid="B36">Lan et&#xa0;al., 2020</xref>). The study further suggested that arginine on its own aids in enhancing disease resistance by inhibiting numerous other pathways related to immune stimulation and proinflammatory conditions. Data also suggests that arginine, as an essential amino acid, is beneficial for gastrointestinal, liver, and immune functions, as well as enhancing insulin sensitivity, amongst other functions (<xref ref-type="bibr" rid="B75">Wu et&#xa0;al., 2008</xref>). This pathway may be prevalent in the data of the current study because of the role of arginine in aiding the body in defense against immune stimulation, especially with LPS. Arginine appears to play an important role in health and immune defense.</p>
<p>Interestingly, Arg is synthesized from proline, as well as glutamine and glutamate, making the Arg and proline metabolism pathway another key element in the pathways driving differences in the current data set. Proline is a particularly fascinating amino acid, as it is the only proteogenic secondary amino acid, and is metabolized by a family of enzymes that respond to metabolic stress and signaling (<xref ref-type="bibr" rid="B49">Phang, 1985</xref>; <xref ref-type="bibr" rid="B51">Phang et&#xa0;al., 2008</xref>, <xref ref-type="bibr" rid="B50">2010</xref>). Proline may also be interconvertible with glutamate and Arg, where the conversion between Arg and proline is an important step in the urea cycle (<xref ref-type="bibr" rid="B2">Adams, 1970</xref>; <xref ref-type="bibr" rid="B50">Phang et&#xa0;al., 2010</xref>). In contrast to previous research, a new theory has emerged suggesting the proline metabolic pathway is mobilized under conditions of stress (<xref ref-type="bibr" rid="B50">Phang et&#xa0;al., 2010</xref>). It is further suggested that proline oxidase plays a vital role in cellular energy maintenance for survival, where glucose deprivation contributed to an inverse increase in proline oxidase (<xref ref-type="bibr" rid="B47">Pandhare et&#xa0;al., 2009</xref>). These data in the current study, as well as others, can be considered further, where arginine was the only amino acid affected by methionine supplementation when evaluating amino acid concentrations in plasma. On their own, methionine and arginine have strong capabilities in preventing oxidative stress through the production of glutathione and exerting anti-inflammatory properties, respectively (<xref ref-type="bibr" rid="B22">Dai et&#xa0;al., 2020</xref>).</p>
<p>In an <italic>in vitro</italic> study evaluating &#x3b2;-alanine (&#x3b2;A) metabolism, the non-essential amino acid increased cellular oxygen consumption, thus improving oxidative metabolism (<xref ref-type="bibr" rid="B59">Schnuck et&#xa0;al., 2016</xref>). In human applications, &#x3b2;A is often supplemented for athletes to prolong exercise duration (<xref ref-type="bibr" rid="B17">Carpentier et&#xa0;al., 2015</xref>). Further, supplementation of &#x3b2;A in the diets of weaned piglets has been shown to alleviate the inflammatory response generated during stress (<xref ref-type="bibr" rid="B20">Chen et&#xa0;al., 2022</xref>). Lactate, previously considered a waste product of metabolism, may also be used in endocrine signaling (<xref ref-type="bibr" rid="B12">Brooks, 1985</xref>; <xref ref-type="bibr" rid="B13">2009</xref>). Lactate and its associated H<sup>+</sup> ions tend to further inhibit glycolysis of immune cells and suppress glucose uptake and intracellular ATP levels in monocytes (<xref ref-type="bibr" rid="B18">Caslin et&#xa0;al., 2019</xref>). Therefore, this metabolic pathway may ease the potential damages elicited by the immune response during an endotoxin challenge.</p>
<p>Histidine is one of the body&#x2019;s essential amino acids and is a gluconeogenic amino acid (<xref ref-type="bibr" rid="B15">Brosnan and Brosnan, 2020</xref>). Histidine may be metabolized into histamine via decarboxylation (<xref ref-type="bibr" rid="B15">Brosnan and Brosnan, 2020</xref>). Research in rats recognized that increases in serum histidine contributed to increases in histamine synthesis, specifically in the brain (<xref ref-type="bibr" rid="B53">Prell et&#xa0;al., 1996</xref>). It was later determined that, in the brain, histamine derived from histidine controls various functions, including stress response (<xref ref-type="bibr" rid="B78">Yoshikawa et&#xa0;al., 2019</xref>). While it is also well-recognized that metal ions, like iron, promote the production of free radicals, histidine may help attenuate their effects (<xref ref-type="bibr" rid="B62">Smolik et&#xa0;al., 2010</xref>). Therefore, histidine metabolism may be another key effort in the body&#x2019;s attempts to manage not only immune stress, but also oxidative stress. The pathways present within the current study may aide in elucidating the events which occur to maintain immune responsiveness, prevent oxidative stress, and ultimately, return the body to homeostasis following LPS administration.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>In summary, these data suggest that oxidative stress indicators from an activated immune response may be mitigated with the addition of supplemental methionine, suggesting expedited recovery of stressed animals during the receiving period. While a complete elimination of oxidative stress markers from the body is not feasible, some within the current study, specifically ROS, show marked reductions in concentrations with supplementation. Further, while prior work on methionine supplementation showed no effect on lipid oxidation products or antioxidant reducing activity, the impact on ROS could be sufficient to slow the effect of immune dysfunction on other plasma indicators. Metabolomic data further demonstrate a clear distinction between pre- and post-LPS administration metabolites present <italic>in vivo</italic>, where protective measures may naturally be activated. Ultimately, these data demonstrate increased oxidative stress products <italic>in vivo</italic> following an immune challenge, as well as their subsequent recovery between 24 to 48 h. These data will be important in further predicting and understanding the potential damage to the growth and development of cattle during the receiving period.</p>
</sec>
</body>
<back>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.</p></sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>All procedures were approved by the West Texas A&amp;M University Institutional Animal Care and Use Committee (Protocol Number: 2021.03.001) and the Livestock Issues Research Unit (IACUC Protocol # 2119S). The study was conducted in accordance with the local legislation and institutional requirements.</p></sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>SB: Investigation, Visualization, Writing &#x2013; original draft. TJ:&#xa0;Investigation, Writing &#x2013; review &amp; editing. JR: Investigation, Methodology, Writing &#x2013; review &amp; editing. JC: Investigation, Methodology, Resources, Writing &#x2013; review &amp; editing. NB:&#xa0;Investigation, Methodology, Resources, Writing &#x2013; review &amp; editing. PB: Investigation, Methodology, Resources, Writing &#x2013; review &amp; editing. GD: Funding acquisition, Resources, Writing &#x2013; review &amp; editing. CK: Investigation, Resources, Writing &#x2013; review &amp; editing. MH: Data curation, Writing &#x2013; review &amp; editing. JL:&#xa0;Methodology, Resources, Writing &#x2013; review &amp; editing.</p></sec>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>Author GD was employed by the company PROJ-X, Inc. Coauthor GD serves as an independent consultant to Adisseo USA Inc.</p>
<p>The authors declared that this work received funding from Adisseo USA Inc. The funder had the following involvement in the study: Funding acquisition and decision to publish.</p></sec>
<sec id="s11" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declared that generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p></sec>
<sec id="s12" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p></sec>
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