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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Microbiol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Microbiology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Microbiol.</abbrev-journal-title>
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<issn pub-type="epub">1664-302X</issn>
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<publisher-name>Frontiers Media S.A.</publisher-name>
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<article-id pub-id-type="doi">10.3389/fmicb.2026.1734219</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>Effects of letrozole supplementation on growth performance, blood indexes, ruminal fermentation parameters, and microbiome composition of <italic>hu</italic> lambs</article-title>
</title-group>
<contrib-group>
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<name><surname>Yang</surname> <given-names>Lukuan</given-names></name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="author-notes" rid="fn002"><sup>&#x2020;</sup></xref>
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<contrib contrib-type="author" equal-contrib="yes">
<name><surname>Li</surname> <given-names>Tingting</given-names></name>
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<name><surname>Zhang</surname> <given-names>Yaqian</given-names></name>
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<name><surname>Ainiwaer</surname> <given-names>Munire</given-names></name>
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<name><surname>Wang</surname> <given-names>Shanshan</given-names></name>
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<name><surname>Liu</surname> <given-names>Zhiqiang</given-names></name>
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<aff id="aff1"><label>1</label><institution>Xinjiang Herbivore Nutrition Laboratory for Meat and Milk, College of Animal Science and Technology, Xinjiang Agricultural University, Urumqi</institution>, <city>Xinjiang</city>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Xinjiang Shangpin Meiyang Technology Co., Ltd., Changji</institution>, <city>Xinjiang</city>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>&#x002A;</label>Correspondence: Kailun Yang, <email xlink:href="mailto:yangkailun2002@aliyun.com">yangkailun2002@aliyun.com</email></corresp>
<corresp id="c002">Caidie Wang, <email xlink:href="mailto:caidie5338352@163.com">caidie5338352@163.com</email></corresp>
<fn fn-type="equal" id="fn002"><label>&#x2020;</label><p>These authors share first authorship</p></fn>
</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>17</volume>
<elocation-id>1734219</elocation-id>
<history>
<date date-type="received">
<day>28</day>
<month>10</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>21</day>
<month>01</month>
<year>2026</year>
</date>
<date date-type="accepted">
<day>29</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2026 Yang, Li, Liu, Zhang, Ainiwaer, Wang, Liu, Yang and Wang.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Yang, Li, Liu, Zhang, Ainiwaer, Wang, Liu, Yang and Wang</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>
<p>This study aimed to explore the effects of dietary letrozole (LE) supplementation on growth performance, rumen microbiota, fermentation profiles, and blood metabolites in <italic>Hu</italic> lambs, providing insights into its potential for enhancing animal production. Twenty-eight male <italic>Hu</italic> lambs (20.21 kg &#x00B1; 0.56 kg, 70 days old) were randomly assigned to four groups, with seven replicates per group: a control group (CON), and three test groups (T1, T2, T3). Lambs in the CON group were fed a basal diet, while T1, T2, and T3 groups received 0.05, 0.1, and 0.2 mg/kg BW of LE, respectively, in addition to the basal diet. The experiment lasted for 46 days. The findings were as follows: (1) There were no significant differences among groups in Initial Body Weight (IBW), Final Body Weight (FBW), Average Daily Feed Intake (ADFI), Average Daily Gain (ADG), and feed conversion ratio throughout the entire trial (<italic>P</italic> &#x003E; 0.05). (2) Compared with the CON group, plasma testosterone (T) concentrations in Groups T2 and T3 were significantly elevated at 0 h post-supplementation (<italic>P</italic> &#x003C; 0.05). Compared with the control group, nitric oxide (NO) levels in Groups T1 and T2 were significantly reduced 4 h after LE supplementation (<italic>P</italic> &#x003C; 0.05). (3)Nitric oxide (NO) levels in experimental groups exhibited a secondary change 4 h after supplementation (<italic>P</italic> &#x003C; 0.05). There were no significant differences in plasma Total Antioxidant Capacity (T-AOC), Catalase (CAT), Superoxide Dismutase (SOD), Glutathione Peroxidase (GSH-Px), or Malondialdehyde (MDA) levels between 0 h pre-supplementation and 4 h post-supplementation across all experimental groups (<italic>P</italic> &#x003E; 0.05). At 0 h before and 4 h after supplementation, Total Protein (TP), Albumin (ALB), and Globulin (GLB) levels in all experimental groups showed no significant differences compared to the CON group (<italic>P</italic> &#x003E; 0.05). (4) Ammonia nitrogen (NH<sub>3</sub>-N) levels were extremely significantly higher in all test groups compared to the CON group (<italic>P</italic> &#x003C; 0.05). Propionic acid and isovaleric acid concentrations in Group T3 were significantly higher than in the CON group (<italic>P</italic> &#x003C; 0.01), while the ethyl-to-propyl ratio was significantly lower (<italic>P</italic> &#x003C; 0.01). (5) At the phylum level, LE-treated groups showed a higher relative abundance of <italic>Firmicutes</italic> than the CON group (21.04%), with increases proportional to the LE dose: Group T3 (37.88%), Group T2 (32.74%), and Group T1 (30.66%). At the family level, the relative abundance of <italic>Prevotellaceae</italic> was significantly lower in all test groups compared to the CON group (<italic>P</italic> &#x003C; 0.05), while <italic>Lachnospiraceae</italic> abundance was significantly higher in the test groups (<italic>P</italic> &#x003C; 0.01). Under the experimental conditions, supplemental feeding of LE did not significantly affect the overall growth performance of lambs. but it did increase plasma testosterone concentration, elevated the relative abundance of Firmicutes in the rumen, reduced the relative abundance of Bacteroidetes, and altered the rumen fermentation pattern. This shift occurred by decreasing the acetate-to-propionate ratio, increasing isovaleric acid concentration, and promoting a propionic acid fermentation pattern, thereby improving feed utilization. Among all groups, the optimal supplemental feeding rate was determined to be 0.2 mg/kg BW.</p>
</abstract>
<kwd-group>
<kwd>growth performance</kwd>
<kwd>lamb</kwd>
<kwd>letrozole</kwd>
<kwd>plasma hormone</kwd>
<kwd>rumen fermentation</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was received for this work and/or its publication. We acknowledged the support of the 2025 years Tianchi Talent Introduction Program-Young Doctor (L).</funding-statement>
</funding-group>
<counts>
<fig-count count="13"/>
<table-count count="7"/>
<equation-count count="3"/>
<ref-count count="45"/>
<page-count count="17"/>
<word-count count="8381"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Microorganisms in Vertebrate Digestive Systems</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec id="S1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Reproductive hormones, as a key component of the endocrine system, are critical for physiological processes such as skeletal development, muscle growth, and fat metabolism in young livestock (<xref ref-type="bibr" rid="B42">Yuting et al., 2011</xref>). Androgens have been shown to accelerate protein synthesis, promote muscle growth, and regulate glucose and lipid metabolism, thereby improving growth performance (<xref ref-type="bibr" rid="B33">Schiffer et al., 2017</xref>). In contrast, estrogen plays a pivotal role in skeletal maturation, epiphyseal closure, and the cessation of linear growth (<xref ref-type="bibr" rid="B20">Li, 2024</xref>). Letrozole (LE), a third-generation aromatase inhibitor, works by specifically binding to the aromatase enzyme, thereby suppressing the conversion of androgens to estrogens and increasing androgen levels within the organism. A study by <xref ref-type="bibr" rid="B30">Rezaei et al. (2020)</xref> demonstrated that administering LE at a dosage of 0.25 mg/kg significantly increased serum testosterone (T) levels in goats, which correlated with enhanced average daily gain (ADG) and carcass weight. Furthermore, the microbiota has been shown to play significant roles in the reproductive endocrine system by interacting with hormones such as estrogen, androgen, and insulin, while also influencing the ruminal microbial structure and metabolic function (<xref ref-type="bibr" rid="B31">Rosales-Nieto et al., 2021</xref>; <xref ref-type="bibr" rid="B37">Tian, 2022</xref>). In ruminants, steroid hormones reach the rumen either through transmural diffusion across the ruminal wall or via saliva (<xref ref-type="bibr" rid="B11">Han, 2010</xref>), and these hormones subsequently modulate ruminal metabolic activity (<xref ref-type="bibr" rid="B21">Li et al., 2022</xref>).</p>
<p>Currently, research on the mechanism by which LE regulates growth performance in ruminants has primarily focused on endocrine pathways, while its effects on rumen microbial communities and metabolic products remain unclear. Therefore, this study used <italic>Hu</italic> sheep as the experimental subjects. By supplementing diets with varying levels of LE, we investigated its effects on growth performance, serum hormone levels, rumen fermentation parameters, rumen microbial community structure, and metabolomic characteristics. The aim was to elucidate the rumen microbial mechanisms through which LE regulates growth in Hu sheep, thereby providing a theoretical basis for the rational application of LE in ruminant production.</p>
</sec>
<sec id="S2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="S2.SS1">
<label>2.1</label>
<title>Design and management of experiment</title>
<p>The trial was conducted at Xinjiang Shangpin Meiyang Technology Co., Ltd. (87.136291&#x00B0;E, 44.359568&#x00B0;N) from September to October 2023, lasting for 46 days. Twenty-eight 70-day-old male <italic>Hu</italic> lambs, with an average body weight of 20.21 &#x00B1; 0.56 kg and in good health, were randomly assigned to four groups (<italic>n</italic> = 7): CON Group (basal diet), Group T1 (basal diet + 0.05 mg/kg BW<sup>&#x2013;1</sup> LE), Group T2 (basal diet + 0.1 mg/kg BW LE), and Group T3 (basal diet + 0.2 mg/kg BW LE). LE was dissolved in 1% carboxymethyl cellulose (CMC) and administered daily at 09:00 a.m. The basal diet was provided via a TMR feeding truck at 09:00 and 17:30 daily. The proportion and detailed composition of TMR are shown in <xref ref-type="table" rid="T1">Table 1</xref>. All lambs had a libitum access to both feed and water.</p>
<table-wrap position="float" id="T1">
<label>TABLE 1</label>
<caption><p>Composition and nutritional level of basic diet (%).</p></caption>
<table cellspacing="5" cellpadding="5" frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="center">Items</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Contents</th>
<th valign="top" align="center"/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">Ingredient</td>
<td/>
<td valign="top" align="center">Nutrient level</td>
<td/>
</tr>
<tr>
<td valign="top" align="center">Corn</td>
<td valign="top" align="center">30.00</td>
<td valign="top" align="center">ME/(MJ&#x22C5;kg<sup>&#x2013;1</sup>)<xref ref-type="table-fn" rid="t1fns2"><sup>&#x2781;</sup></xref></td>
<td valign="top" align="center">9.45</td>
</tr>
<tr>
<td valign="top" align="center">Whole plant corn silage</td>
<td valign="top" align="center">24.00</td>
<td valign="top" align="center">DM</td>
<td valign="top" align="center">94.15</td>
</tr>
<tr>
<td valign="top" align="center">Alfalfa</td>
<td valign="top" align="center">20.00</td>
<td valign="top" align="center">CP</td>
<td valign="top" align="center">12.25</td>
</tr>
<tr>
<td valign="top" align="center">Corn germ meal</td>
<td valign="top" align="center">16.00</td>
<td valign="top" align="center">EE</td>
<td valign="top" align="center">4.26</td>
</tr>
<tr>
<td valign="top" align="center">Corn bran</td>
<td valign="top" align="center">8.00</td>
<td valign="top" align="center">Ash</td>
<td valign="top" align="center">8.66</td>
</tr>
<tr>
<td valign="top" align="center">Premix<xref ref-type="table-fn" rid="t1fns1">&#x2780;</xref></td>
<td valign="top" align="center">2.00</td>
<td valign="top" align="center">NDF</td>
<td valign="top" align="center">26.67</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="3">Total</td>
<td valign="top" align="center" rowspan="3">100.00</td>
<td valign="top" align="center">ADF</td>
<td valign="top" align="center">18.76</td>
</tr>
<tr>
<td valign="top" align="center">Ca</td>
<td valign="top" align="center">0.54</td>
</tr>
<tr>
<td valign="top" align="center">P</td>
<td valign="top" align="center">0.35</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="t1fns1"><p>&#x2780; Premix provides the following per kg: Vitamin A 12,100 IU; Vitamin D2 1,150 IU; Vitamin E 130 IU; Cu 18 mg; Zn 65 mg; Mn 50 mg; Fe 65 mg; I 0.8 mg; Co 0.7 mg; Se 0.8 mg.</p></fn>
<fn id="t1fns2"><p>&#x2781; Metabolizable energy was a calculated value, whereas nutrient levels were analytically determined values.</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S2.SS2">
<label>2.2</label>
<title>Sample collection</title>
<sec id="S2.SS2.SSS1">
<label>2.2.1</label>
<title>Collection of growth performance indicators</title>
<p>The lambs&#x2019; body weight was measured after fasting on days 0, 15, 30, and 45, and <italic>AverageDailyGain</italic>(ADG) was calculated. From days 31 to 37, daily feed intake and leftovers were recorded to determine the Average Daily Feed Intake (ADFI) and feed conversion ratio (FCR) for each group.</p>
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</sec>
<sec id="S2.SS2.SSS2">
<label>2.2.2</label>
<title>Collection of blood biochemical parameters</title>
<p>On the 25th day of the experiment, 5 healthy lambs with similar body weight were selected from each group. Blood samples were collected from the jugular vein using heparin sodium anticoagulant tubes at 0 h before and 4 h after supplementary feeding. The samples were centrifuged at 3,500 rpm for 15 min, and the plasma was transferred into 1.5 mL cryovials and stored at -20&#x00B0;C for subsequent analysis.</p>
</sec>
<sec id="S2.SS2.SSS3">
<label>2.2.3</label>
<title>Collection of ruminal fluid parameters</title>
<p>On day 46, five healthy lambs of similar body weight were selected from each group. Approximately 2 h post-supplementation, around 100 mL of ruminal fluid was collected from each lamb using a vacuum extraction device. To avoid contamination from saliva, the first 50 mL was discarded. The pH of the remaining ruminal fluid was immediately measured using a portable pH meter, and the fluid was then filtered through four layers of medical gauze, aliquoted, and stored at -80&#x00B0;C.</p>
</sec>
</sec>
<sec id="S2.SS3">
<label>2.3</label>
<title>Sample analysis</title>
<sec id="S2.SS3.SSS1">
<label>2.3.1</label>
<title>Plasma biochemical parameter assay</title>
<p>The plasma levels of T, E<sub>2</sub>, GH, and insulin were measured using the enzyme-linked immunosorbent assay (ELISA). The levels of T-AOC, CAT, SOD, GSH-Px, MDA, and NO concentration were determined using colorimetric methods. All these tests were commissioned to Beijing Huaying Biotechnology Co., Ltd. The Hua Wei Delong DR-200BS microplate reader was used (the instrument was purchased from Wuxi Hua Wei Delong Instrument Co., Ltd.). The analysis of plasma total protein (TP), albumin (ALB), and globulin (GLB) was outsourced to the Third People&#x2019;s Hospital of Xinjiang.</p>
</sec>
<sec id="S2.SS3.SSS2">
<label>2.3.2</label>
<title>Rumen fluid parameter analysis</title>
<sec id="S2.SS3.SSS2.Px1">
<label>2.3.2.1</label>
<title>NH<sub>3</sub>-H quantification</title>
<p>The NH<sub>3</sub>-N concentration was determined using the phenol-hypochlorite method (indophenol blue method), as detailed in <xref ref-type="bibr" rid="B14">Jin (2024)</xref>. The analysis was performed using a TECAN Infinite M200 full-wavelength microplate reader (purchased from Tecan Group, Switzerland).</p>
</sec>
<sec id="S2.SS3.SSS2.Px2">
<label>2.3.2.2</label>
<title>VFA concentration assay</title>
<p>Volatile fatty acid (VFA) concentrations were determined according to the method described by <xref ref-type="bibr" rid="B40">Xu (2013)</xref> using a Shimadzu GC-2010 gas chromatograph, with 4-methylpentanoic acid serving as the internal standard.</p>
</sec>
<sec id="S2.SS3.SSS2.Px3">
<label>2.3.2.3 16</label>
<title>S rRNA gene amplicon sequencing of rumen bacteria</title>
<p>The 16S rRNA sequencing of rumen was commissioned to Beijing Novogene Biotech Co., Ltd. The V3-V4 hypervariable region of the bacterial 16S rRNA gene was amplified by PCR using universal bacterial primers (314F: 5&#x2019;-CCTAYGGGRBGCASCAG-3&#x2019; and 806R: 5&#x2019;-GGACTACNNGGGTATCTAAT-3&#x2019;). Polymerase Chain Reaction (PCR) products were electrophoresed on a 2% agarose gel, purified with magnetic beads, and the target bands were extracted for sequencing library construction. Genome sequencing was performed on the Illumina Novaseq platform, and the resulting data were analyzed using QIIME2 software.</p>
</sec>
</sec>
</sec>
<sec id="S2.SS4">
<label>2.4</label>
<title>Data statistics and analysis</title>
<p>Data organization was initially performed in Microsoft Excel 2021. Statistical analyses were conducted separately: zootechnical and biochemical data were analyzed using one-way ANOVA followed by Duncan&#x2019;s <italic>post-hoc</italic> test in SPSS 25.0, with significance levels set at <italic>P</italic> &#x003C; 0.05 and <italic>P</italic> &#x003C; 0.01 (<xref ref-type="bibr" rid="B17">Krzywinski and Altman, 2014</xref>). Microbial data, including alpha diversity indices and relative taxonomic abundances at the phylum, family, and genus levels, were analyzed via the Kruskal-Wallis test on the NovoMagic platform, which was also used for data visualization (<xref ref-type="bibr" rid="B16">Kruskal and Wallis, 2012</xref>).</p>
</sec>
</sec>
<sec id="S3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="S3.SS1">
<label>3.1</label>
<title>Sequencing quality control</title>
<p>The dilution curve construction is based on the relationship between the progressively increasing sequencing data volume and the corresponding &#x03B1;-diversity index values, as shown in <xref ref-type="fig" rid="F1">Figure 1</xref>. As the sequencing data volume increases, the dilution curves for each sample group gradually plateau, indicating that the sequencing depth is sufficient to capture the major taxa within the microbial communities. This provides a comprehensive reflection of the microbial diversity and enables further analysis.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption><p>Rarefaction curve of samples.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g001.tif">
<alt-text content-type="machine-generated">Line graph depicting observed OTUs as a function of sequence number for four groups: CON, T1, T2, and T3. Observed OTUs increase rapidly at first, then plateau, with T3 showing the highest values and CON the lowest. Each group is represented by a distinct marker and color, and axes are clearly labeled.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS2">
<label>3.2</label>
<title>Microbial species composition</title>
<p>A total of 8,289 operational taxonomic units (OTUs) were identified across all samples in this study (<xref ref-type="fig" rid="F2">Figure 2</xref>). Of these, 1,078 OTUs (13.00% of the total) were shared across all four groups. The numbers of unique OTUs in the CON, T1, T2, and T3 groups were 1,107 (13.36%), 975 (11.76%), 1,093 (13.19%), and 1,606 (19.38%), respectively.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption><p>Effects of LE supplementation on rumen OTUs.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g002.tif">
<alt-text content-type="machine-generated">Venn diagram with four overlapping colored sets labeled CON, T1, T2, and T3, each containing various numbers representing shared and unique elements among the groups, illustrating their intersections and differences.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS3">
<label>3.3</label>
<title>Alpha diversity analysis</title>
<p>The Chao1 index in T3 was significantly higher than that in the CON and T1 groups (<italic>P</italic> &#x003C; 0.05). No significant differences were observed in the Observed_otus, Shannon, or Simpson indices among the groups (<italic>P</italic> &#x003E; 0.05). These results indicate that LE supplementation increased the richness of the rumen microbial community. Furthermore, the Goods coverage of all samples exceeded 99%, confirming that the sequencing depth was adequate to capture the majority of OTUs and reliably represent the microbial composition of the rumen fluid (<xref ref-type="table" rid="T2">Table 2</xref>).</p>
<table-wrap position="float" id="T2">
<label>TABLE 2</label>
<caption><p>Effects of LE supplementation on alpha diversity index of rumen microbial community (<italic>n</italic> = 5).</p></caption>
<table cellspacing="5" cellpadding="5" frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="center">Items</th>
<th valign="top" align="center" colspan="4">Groups</th>
<th valign="top" align="center"><italic>P</italic>-value</th>
</tr>
<tr>
<th valign="top" align="center"/>
<th valign="top" align="center">CON</th>
<th valign="top" align="center">T1</th>
<th valign="top" align="center">T2</th>
<th valign="top" align="center">T3</th>
<th valign="top" align="center"/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">Chao1</td>
<td valign="top" align="center">1130.09<sup>b</sup>&#x00B1; 238.27</td>
<td valign="top" align="center">1126.08<sup>b</sup>&#x00B1; 169.91</td>
<td valign="top" align="center">1319.83<sup>ab</sup>&#x00B1; 109.65</td>
<td valign="top" align="center">1481.62<sup>a</sup>&#x00B1; 192.75</td>
<td valign="top" align="center">0.02</td>
</tr>
<tr>
<td valign="top" align="center">Goods_coverage</td>
<td valign="top" align="center">99.94 &#x00B1; 0.02</td>
<td valign="top" align="center">99.94 &#x00B1; 0.01</td>
<td valign="top" align="center">99.95 &#x00B1; 0.01</td>
<td valign="top" align="center">99.93 &#x00B1; 0.02</td>
<td valign="top" align="center">0.51</td>
</tr>
<tr>
<td valign="top" align="center">Observed_otus</td>
<td valign="top" align="center">1118.00 &#x00B1; 239.09</td>
<td valign="top" align="center">1116.60 &#x00B1; 168.86</td>
<td valign="top" align="center">1311.80 &#x00B1; 107.38</td>
<td valign="top" align="center">1473.40 &#x00B1; 191.61</td>
<td valign="top" align="center">0.01</td>
</tr>
<tr>
<td valign="top" align="center">Shannon</td>
<td valign="top" align="center">7.12 &#x00B1; 0.74</td>
<td valign="top" align="center">7.52 &#x00B1; 0.54</td>
<td valign="top" align="center">8.19 &#x00B1; 0.52</td>
<td valign="top" align="center">8.28 &#x00B1; 0.59</td>
<td valign="top" align="center">0.02</td>
</tr>
<tr>
<td valign="top" align="center">Simpson</td>
<td valign="top" align="center">0.96 &#x00B1; 0.02</td>
<td valign="top" align="center">0.98 &#x00B1; 0.01</td>
<td valign="top" align="center">0.98 &#x00B1; 0.02</td>
<td valign="top" align="center">0.99 &#x00B1; 0.01</td>
<td valign="top" align="center">0.12</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Within a row, data points with no superscript letters or the same letter indicate no significant difference (<italic>P</italic> &#x003E; 0.05). Different lowercase letters indicate a significant difference (<italic>P</italic> &#x003C; 0.05), and different uppercase letters indicate a highly significant difference (<italic>P</italic> &#x003C; 0.01).</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS4">
<label>3.4</label>
<title>PLS-DA analysis</title>
<p>The PLS-DA score plot, a tool commonly used to visually assess a model&#x2019;s classification performance. The greater the separation between the two sample groups within the plot, the more pronounced the classification effect. The first principal component accounts for 6.31% of the variance, while the second principal component explains 4.59%. The CON group and Group T1 exhibit less distinct separation, which may be attributed to their smaller node sizes (<xref ref-type="fig" rid="F3">Figure 3</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption><p>PLS-DA score plot.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g003.tif">
<alt-text content-type="machine-generated">Scatter plot showing partial least squares discriminant analysis (PLS-DA) with four groups labeled as C, T1, T2, and T3, each represented by distinct colors and confidence ellipses. Axes denote explained variances of 6.31% and 4.59%.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS5">
<label>3.5</label>
<title>The effect of LE on rumen fermentation parameters in <italic>hu</italic> lambs</title>
<p>There is no significant differences in ruminal pH were observed among the groups (<italic>P</italic> &#x003E; 0.05). However, the NH<sub>3</sub>-N concentration was significantly higher in the treatment groups compared to the CON group (<italic>P</italic> &#x003C; 0.05). Specifically, groups T2 and T3 exhibited a highly significant increase in NH<sub>3</sub>-N concentration compared to group T1 (<italic>P</italic> &#x003C; 0.01), with a linear increase in NH<sub>3</sub>-N levels corresponding to the escalating doses of LE. The concentrations of propionate and isovalerate in group T3 were significantly higher than those in the CON group and group T1 (<italic>P</italic> &#x003C; 0.01), no significant difference compared with Group T2 (<italic>P</italic> &#x003E; 0.05). Additionally, the isovalerate concentration demonstrated both linear and quadratic effects as the dose of LE supplementation increased. The acetate-to-propionate ratio was significantly lower in group T3 compared to the CON group (<italic>P</italic> &#x003C; 0.01), with a linear decrease in Acetate-to-Propionate Ratio observed as LE supplementation increased. As shown in <xref ref-type="table" rid="T3">Table 3</xref>.</p>
<table-wrap position="float" id="T3">
<label>TABLE 3</label>
<caption><p>The effect of feeding LE on rumen fermentation parameters of <italic>Hu</italic> lambs (<italic>n</italic> = 5).</p></caption>
<table cellspacing="5" cellpadding="5" frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="center">Items</th>
<th valign="top" align="center" colspan="4">Groups</th>
<th valign="top" align="center"><italic>SEM</italic></th>
<th valign="top" align="center" colspan="3"><italic>P</italic>-value</th>
</tr>
<tr>
<th valign="top" align="center"/>
<th valign="top" align="center">CON</th>
<th valign="top" align="center">T1</th>
<th valign="top" align="center">T2</th>
<th valign="top" align="center">T3</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Anova</th>
<th valign="top" align="center">Linear</th>
<th valign="top" align="center">Quadratic</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">pH</td>
<td valign="top" align="center">6.72</td>
<td valign="top" align="center">6.80</td>
<td valign="top" align="center">6.74</td>
<td valign="top" align="center">6.85</td>
<td valign="top" align="center">0.03</td>
<td valign="top" align="center">0.28</td>
<td valign="top" align="center">0.15</td>
<td valign="top" align="center">0.85</td>
</tr>
<tr>
<td valign="top" align="center">NH3-N /(mg/dL)</td>
<td valign="top" align="center">11.70<sup>Bc</sup></td>
<td valign="top" align="center">16.60<sup>Bb</sup></td>
<td valign="top" align="center">24.00<sup>Aa</sup></td>
<td valign="top" align="center">23.25<sup>Aa</sup></td>
<td valign="top" align="center">1.37</td>
<td valign="top" align="center">&#x003C; 0.01</td>
<td valign="top" align="center">&#x003C; 0.01</td>
<td valign="top" align="center">0.10</td>
</tr>
<tr>
<td valign="top" align="center">Acetate/(mmol/L)</td>
<td valign="top" align="center">48.66</td>
<td valign="top" align="center">52.04</td>
<td valign="top" align="center">53.87</td>
<td valign="top" align="center">57.21</td>
<td valign="top" align="center">2.25</td>
<td valign="top" align="center">0.63</td>
<td valign="top" align="center">0.21</td>
<td valign="top" align="center">1.00</td>
</tr>
<tr>
<td valign="top" align="center">Propionate/(mmol/L)</td>
<td valign="top" align="center">14.45<sup>Bb</sup></td>
<td valign="top" align="center">14.55<sup>Bb</sup></td>
<td valign="top" align="center">18.27<sup>ABab</sup></td>
<td valign="top" align="center">22.83<sup>Aa</sup></td>
<td valign="top" align="center">1.10</td>
<td valign="top" align="center">&#x003C; 0.01</td>
<td valign="top" align="center">&#x003C; 0.01</td>
<td valign="top" align="center">0.21</td>
</tr>
<tr>
<td valign="top" align="center">Butyrate/(mmol/L)</td>
<td valign="top" align="center">10.93</td>
<td valign="top" align="center">10.07</td>
<td valign="top" align="center">10.22</td>
<td valign="top" align="center">10.59</td>
<td valign="top" align="center">0.43</td>
<td valign="top" align="center">0.91</td>
<td valign="top" align="center">0.84</td>
<td valign="top" align="center">0.51</td>
</tr>
<tr>
<td valign="top" align="center">Isobutyrate/(mmol/L)</td>
<td valign="top" align="center">1.28</td>
<td valign="top" align="center">1.35</td>
<td valign="top" align="center">1.28</td>
<td valign="top" align="center">1.67</td>
<td valign="top" align="center">0.07</td>
<td valign="top" align="center">0.19</td>
<td valign="top" align="center">0.10</td>
<td valign="top" align="center">0.28</td>
</tr>
<tr>
<td valign="top" align="center">Valerate/(mmol/L)</td>
<td valign="top" align="center">1.04</td>
<td valign="top" align="center">0.95</td>
<td valign="top" align="center">1.15</td>
<td valign="top" align="center">1.19</td>
<td valign="top" align="center">0.04</td>
<td valign="top" align="center">0.16</td>
<td valign="top" align="center">0.09</td>
<td valign="top" align="center">0.39</td>
</tr>
<tr>
<td valign="top" align="center">Isovalerate/(mmol/L)</td>
<td valign="top" align="center">1.51<sup>Bb</sup></td>
<td valign="top" align="center">1.42<sup>Bb</sup></td>
<td valign="top" align="center">1.74<sup>ABb</sup></td>
<td valign="top" align="center">2.35<sup>Aa</sup></td>
<td valign="top" align="center">0.11</td>
<td valign="top" align="center">&#x003C; 0.01</td>
<td valign="top" align="center">&#x003C; 0.01</td>
<td valign="top" align="center">0.03</td>
</tr>
<tr>
<td valign="top" align="center">Total VFAs)/(mmol/L)</td>
<td valign="top" align="center">77.87</td>
<td valign="top" align="center">80.38</td>
<td valign="top" align="center">86.54</td>
<td valign="top" align="center">95.85</td>
<td valign="top" align="center">3.47</td>
<td valign="top" align="center">0.28</td>
<td valign="top" align="center">0.06</td>
<td valign="top" align="center">0.62</td>
</tr>
<tr>
<td valign="top" align="center">Acetate-to-Propionate Ratio</td>
<td valign="top" align="center">3.41<sup>ABa</sup></td>
<td valign="top" align="center">3.53<sup>Aa</sup></td>
<td valign="top" align="center">2.94<sup>ABab</sup></td>
<td valign="top" align="center">2.59<sup>Bb</sup></td>
<td valign="top" align="center">0.12</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">&#x003C; 0.01</td>
<td valign="top" align="center">0.24</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Different lowercase letters on the same data point indicate significant differences (<italic>P</italic> &#x003C; 0.05), different uppercase letters indicate highly significant differences (<italic>P</italic> &#x003C; 0.01), and identical letters or no letters indicate no significant differences (<italic>P</italic> &#x003E; 0.05).</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS6">
<label>3.6</label>
<title>The effect of LE on the rumen microbial flora of <italic>hu</italic> lambs</title>
<sec id="S3.SS6.SSS1">
<label>3.6.1</label>
<title>Effect of LE supplementation on rumen microflora structure (phylum level) of <italic>hu</italic> lambs</title>
<p>The ruminal microbial community structure at the phylum level for <italic>Hu</italic> lambs supplemented with varying doses of LE. The top 10 phyla by relative abundance were identified as <italic>Bacteroidota</italic>, <italic>Firmicutes</italic>, <italic>Euryarchaeota</italic>, <italic>Proteobacteria</italic>, <italic>Spirochaetota</italic>, <italic>Patescibacteria</italic>, <italic>Synergistota</italic>, <italic>Cyanobacteria</italic>, <italic>Fibrobacterota</italic>, and <italic>Verrucomicrobiota</italic>. <italic>Bacteroidota</italic> and <italic>Firmicutes</italic> dominated the microbial composition across all treatment groups. The CON group exhibited the highest relative abundance of <italic>Bacteroidota</italic> (74.06%), followed by T1 (64.36%), T2 (60.57%), and T3 (53.45%). In contrast, the relative abundance of <italic>Firmicutes</italic> was higher in all treatment groups compared to the CON group (21.04%), with values of 30.66% in T1, 32.74% in T2, and 37.88% in T3 (<xref ref-type="fig" rid="F4">Figure 4</xref>).</p>
<fig id="F4" position="float">
<label>FIGURE 4</label>
<caption><p>Distribution of main rumen bacteria at phylum level.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g004.tif">
<alt-text content-type="machine-generated">Stacked bar chart showing the relative abundance of microbial phyla in four groups: CON, T1, T2, and T3. Bacteroidota and Firmicutes are the most abundant, with smaller proportions of Euryarchaeota, Proteobacteria, Spirochaetes, and other taxa. Each color in the legend corresponds to a specific group, with Bacteroidota in blue and Firmicutes in pink. The vertical axis represents relative abundance from zero to one hundred percent.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS6.SSS2">
<label>3.6.2</label>
<title>Effects of LE on the rumen microbial community structure (family level) in <italic>hu</italic> lambs</title>
<p>The effects of different levels of LE supplementation on the ruminal microbiota structure of <italic>Hu</italic> lambs at the family level. The top 10 most abundant families were <italic>Prevotellaceae</italic>, <italic>Selenomonadaceae</italic>, <italic>Rikenellaceae</italic>, <italic>F082</italic>, <italic>Lachnospiraceae</italic>, <italic>Acidaminococcaceae</italic>, <italic>Bacteroidales_RF16_group</italic>, <italic>Oscillospiraceae</italic>, <italic>Eubacterium_coprostanoligenes_group</italic>, and <italic>Methanobrevibacteraceae</italic>. Among these, <italic>Prevotellaceae</italic> was the dominant family in all groups. Its relative abundance was highest in the CON group (52.10%) compared to the treatment groups, with values of 38.49% in T1, 32.61% in T2, and 35.13% in T3. The relative abundance of <italic>Prevotellaceae</italic> was significantly lower in all treatment groups than in the CON group (<italic>P</italic> &#x003C; 0.05). In contrast, <italic>Lachnospiraceae</italic> abundance was significantly higher in all treatment groups (<italic>P</italic> &#x003C; 0.01), accounting for 2.80% (T1), 5.36% (T2), and 6.26% (T3), respectively. Furthermore, the T3 group exhibited a significantly higher abundance of <italic>Lachnospiraceae</italic> compared to the group T1, while the abundance of <italic>Bacteroidales_RF16_group</italic> in T3 was significantly lower than that in the CON group (<xref ref-type="fig" rid="F5">Figure 5</xref>).</p>
<fig id="F5" position="float">
<label>FIGURE 5</label>
<caption><p>Distribution of main rumen bacteria at family level.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g005.tif">
<alt-text content-type="machine-generated">Stacked bar chart illustrating the relative abundance of different bacterial genera across four sample groups labeled COX, T1, T2, and T3. Each genus is represented by a distinct color, with Prevotella and Selenomonas accounting for the largest proportions in all samples, while other genera and categories make up smaller segments. The chart highlights compositional differences and diversity in bacterial populations among the groups as indicated by the sample names.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS6.SSS3">
<label>3.6.3</label>
<title>The effect of LE on the rumen microbial community structure (genus level) in <italic>hu</italic> lambs</title>
<p>The effects of varying levels of LE supplementation on the ruminal microbiota structure at the genus level in <italic>Hu</italic> lambs. The top 10 most abundant genera identified were <italic>Prevotella</italic>, <italic>Rikenellaceae_RC9_gut_group</italic>, <italic>Veillonellaceae_UCG-001</italic>, <italic>Prevotellaceae_UCG-001</italic>, <italic>Succiniclasticum</italic>, <italic>Prevotellaceae_UCG-003</italic>, <italic>Quinella</italic>, <italic>Selenomonas</italic>, <italic>UCG-002</italic>, and <italic>Methanobrevibacter</italic>. Among these, <italic>Prevotella</italic> and <italic>Rikenellaceae_RC9_gut_group</italic> were the dominant genera across all groups. The relative abundance of <italic>Prevotella</italic> was higher in the CON group (40.01%) compared to the treatment groups, with values of 28.10% in T1, 23.58% in T2, and 27.58% in T3. Although the relative abundance of <italic>Prevotella</italic> was lower in all treatment groups than in the CON group, the differences were not statistically significant (<italic>P</italic> &#x003E; 0.05). The relative abundance of <italic>Rikenellaceae_RC9_gut_group</italic> was higher in T1 (15.74%) and T2 (11.71%) compared to the CON and T3 groups. No significant differences in genus-level relative abundances were observed among the treatment groups (<xref ref-type="fig" rid="F6">Figure 6</xref>).</p>
<fig id="F6" position="float">
<label>FIGURE 6</label>
<caption><p>Distribution of main rumen bacteria at genus level.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g006.tif">
<alt-text content-type="machine-generated">Stacked bar chart compares relative abundance of different microbial taxa in four groups labeled CON, T1, T2, and T3, with Prevotella and others most prominent across all groups. Color-coded legend identifies each taxon.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS6.SSS4">
<label>3.6.4</label>
<title>LEfSe analysis</title>
<p>LEfSe analysis was conducted to identify taxa with significant differences in relative abundance between the groups using Linear Discriminant Analysis (LDA). The histogram in <xref ref-type="fig" rid="F7">Figure 7</xref> shows taxa with an LDA score greater than 3.5, indicating significant differences in abundance. Seventeen microbial taxa in the rumen across the four treatment groups exceeded this threshold, including 2 phyla, 2 classes, 3 orders, 5 families, 4 genera, and 1 species. In the T3 group, the significantly enriched taxa included the phylum <italic>Firmicutes</italic>; the class <italic>Clostridia</italic>; the orders <italic>Lachnospirales</italic> and <italic>Christensenellales</italic>; the families <italic>Lachnospiraceae</italic>, <italic>Christensenellaceae</italic>, and <italic>Hungateiclostridiaceae</italic>; the genera <italic>Christensenellaceae_R-7_group</italic>, <italic>Saccharofermentans</italic>, <italic>UCG-010</italic>, <italic>Lactobacillus</italic>; and the species <italic>bacterium WCE3006</italic>. In contrast, the genus <italic>Anaerovibrio</italic> was significantly enriched in the T1 group. The CON group exhibited significant enrichment in the order <italic>Bacteroidales</italic>, phylum <italic>Bacteroidota</italic>, class <italic>Bacteroidia</italic>, and the family <italic>Bacteroidales_RF16_group</italic>.</p>
<fig id="F7" position="float">
<label>FIGURE 7</label>
<caption><p>LDA Distribution.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g007.tif">
<alt-text content-type="machine-generated">Horizontal bar chart showing bacterial taxa with significant LDA scores, colored by group: red for CON, green for T1, blue for T3. Major taxa include Firmicutes and Bacteroidota, with LDA scores up to 5.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS6.SSS5">
<label>3.6.5</label>
<title>PICRUSt2 function prediction</title>
<p>The top 15 differentially ranked functions identified across the four groups, highlighting the enriched pathways. In the control group, two pathways were enriched: CMP-3-deoxy-D-manno-octulosonate biosynthesis I and adenosylcobalamin salvage from cobinamide I. In the T2 group, three pathways were enriched: nitrate reduction I (denitrification), urea cycle, and glycolysis V (Pyrococcus). Ten pathways were enriched in the T3 group: <italic>L</italic>-glutamate degradation V (via hydroxyglutarate), dTDP-N-acetylthomosamine biosynthesis, polymyxin resistance, acetylene degradation, superpathway of purine deoxyribonucleosides degradation, peptidoglycan biosynthesis IV (Enterococcus faecium), superpathway of N-acetylneuraminate degradation, superpathway of N-acetylglucosamine, N-acetylmannosamine, and N-acetylneuraminate degradation, methanol oxidation to carbon dioxide, and <italic>L</italic>-lysine biosynthesis I (<xref ref-type="fig" rid="F8">Figure 8</xref>).</p>
<fig id="F8" position="float">
<label>FIGURE 8</label>
<caption><p>Differential metabolic pathways between groups.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g008.tif">
<alt-text content-type="machine-generated">Horizontal bar chart comparing mean proportions of several metabolic and biosynthetic pathways across four groups: CON, T1, T2, and T3. Each pathway, such as CMP-3-deoxy-D-manno-octulosonate biosynthesis and L-lysine biosynthesis, shows distinct bar lengths for each group, with differences in values indicating varying pathway activity levels between groups. Color legend identifies groups as red for CON, blue for T1, orange for T2, and green for T3.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec id="S3.SS7">
<label>3.7</label>
<title>Effect of supplementing LE on the growth performance of <italic>Hu</italic> lambs</title>
<p>As shown in <xref ref-type="table" rid="T4">Table 4</xref>, there were no significant differences (<italic>P</italic> &#x003E; 0.05) in Initial Body Weight (IBW), Final Body Weight (FBW), Average Daily Feed Intake(ADFI), Average Daily Gain (ADG) or Feed Conversion Ratio across all groups throughout the trial period.</p>
<table-wrap position="float" id="T4">
<label>TABLE 4</label>
<caption><p>Effects of dietary LE supplementation on growth performance in <italic>Hu</italic> lambs (<italic>n</italic> = 7).</p></caption>
<table cellspacing="5" cellpadding="5" frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="center">Items</th>
<th valign="top" align="center" colspan="4">Groups</th>
<th valign="top" align="center"><italic>SEM</italic></th>
<th valign="top" align="center" colspan="3"><italic>P</italic>-value</th>
</tr>
<tr>
<th valign="top" align="center"/>
<th valign="top" align="center">CON</th>
<th valign="top" align="center">T1</th>
<th valign="top" align="center">T2</th>
<th valign="top" align="center">T3</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Anova</th>
<th valign="top" align="center">Linear</th>
<th valign="top" align="center">Quadratic</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">Initial body weight (IBW) (kg)</td>
<td valign="top" align="center">20.31</td>
<td valign="top" align="center">20.20</td>
<td valign="top" align="center">20.15</td>
<td valign="top" align="center">20.19</td>
<td valign="top" align="center">0.10</td>
<td valign="top" align="center">0.96</td>
<td valign="top" align="center">0.68</td>
<td valign="top" align="center">0.73</td>
</tr>
<tr>
<td valign="top" align="center">Final body weight (FBW) (kg)</td>
<td valign="top" align="center">29.05</td>
<td valign="top" align="center">29.41</td>
<td valign="top" align="center">29.61</td>
<td valign="top" align="center">29.32</td>
<td valign="top" align="center">0.17</td>
<td valign="top" align="center">0.74</td>
<td valign="top" align="center">0.54</td>
<td valign="top" align="center">0.37</td>
</tr>
<tr>
<td valign="top" align="center">Average daily feed intake (ADFI) (kg)</td>
<td valign="top" align="center">1.44</td>
<td valign="top" align="center">1.52</td>
<td valign="top" align="center">1.51</td>
<td valign="top" align="center">1.46</td>
<td valign="top" align="center">0.11</td>
<td valign="top" align="center">0.43</td>
<td valign="top" align="center">0.25</td>
<td valign="top" align="center">0.29</td>
</tr>
<tr>
<td valign="top" align="center">Average daily gain (ADG) (g)</td>
<td valign="top" align="center">194.37</td>
<td valign="top" align="center">204.76</td>
<td valign="top" align="center">210.16</td>
<td valign="top" align="center">202.86</td>
<td valign="top" align="center">3.26</td>
<td valign="top" align="center">0.40</td>
<td valign="top" align="center">0.30</td>
<td valign="top" align="center">0.19</td>
</tr>
<tr>
<td valign="top" align="center">Feed conversion ratio (F:R)</td>
<td valign="top" align="center">7.40</td>
<td valign="top" align="center">7.43</td>
<td valign="top" align="center">7.17</td>
<td valign="top" align="center">7.18</td>
<td valign="top" align="center">0.14</td>
<td valign="top" align="center">0.89</td>
<td valign="top" align="center">0.58</td>
<td valign="top" align="center">0.77</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Different lowercase letters on the same data point indicate significant differences (<italic>P</italic> &#x003C; 0.05), different uppercase letters indicate highly significant differences (<italic>P</italic> &#x003C; 0.01), and identical letters or no letters indicate no significant differences (<italic>P</italic> &#x003E; 0.05).</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS8">
<label>3.8</label>
<title>Effect of supplementing LE on blood parameters in <italic>Hu</italic> lambs</title>
<p>As presented in <xref ref-type="table" rid="T5">Table 5</xref>, at 0 h before supplementation, T levels in the T2 and T3 groups were significantly higher than those in the CON group (<italic>P</italic> &#x003C; 0.05), showing a linear increase. At 4 h after supplementation, no significant differences in T levels were observed among the groups (<italic>P</italic> &#x003E; 0.05). Additionally, there were no significant differences in the levels of E<sub>2</sub>, GH, and INS among the groups at either 0 h before or 4 h after supplementation (<italic>P</italic> &#x003E; 0.05).</p>
<table-wrap position="float" id="T5">
<label>TABLE 5</label>
<caption><p>Effects of LE supplementation on plasma hormone levels in <italic>Hu</italic> lambs (<italic>n</italic> = 5).</p></caption>
<table cellspacing="5" cellpadding="5" frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="center">Items</th>
<th valign="top" align="center">Time</th>
<th valign="top" align="center" colspan="4">Groups</th>
<th valign="top" align="center"><italic>SEM</italic></th>
<th valign="top" align="center" colspan="3"><italic>P</italic>-value</th>
</tr>
<tr>
<th valign="top" align="center"/>
<th valign="top" align="center"/>
<th valign="top" align="center">CON</th>
<th valign="top" align="center">T1</th>
<th valign="top" align="center">T2</th>
<th valign="top" align="center">T3</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Anova</th>
<th valign="top" align="center">Linear</th>
<th valign="top" align="center">Quadratic</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center" rowspan="2">Testosterone (T) (ng/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">0.62<sup>b</sup></td>
<td valign="top" align="center">0.81<sup>ab</sup></td>
<td valign="top" align="center">0.98<sup>a</sup></td>
<td valign="top" align="center">0.94<sup>a</sup></td>
<td valign="top" align="center">3.31</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">0.01</td>
<td valign="top" align="center">0.22</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">1.03</td>
<td valign="top" align="center">1.17</td>
<td valign="top" align="center">1.22</td>
<td valign="top" align="center">1.24</td>
<td valign="top" align="center">0.82</td>
<td valign="top" align="center">0.50</td>
<td valign="top" align="center">0.17</td>
<td valign="top" align="center">0.54</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Estradiol (E<sub>2</sub>) (pg/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">22.58</td>
<td valign="top" align="center">22.3</td>
<td valign="top" align="center">19.39</td>
<td valign="top" align="center">20.88</td>
<td valign="top" align="center">0.89</td>
<td valign="top" align="center">0.47</td>
<td valign="top" align="center">0.27</td>
<td valign="top" align="center">0.58</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">21.02</td>
<td valign="top" align="center">20.17</td>
<td valign="top" align="center">17.72</td>
<td valign="top" align="center">19.94</td>
<td valign="top" align="center">0.47</td>
<td valign="top" align="center">0.71</td>
<td valign="top" align="center">0.54</td>
<td valign="top" align="center">0.46</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Growth hormone (GH) (ng/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">4.83</td>
<td valign="top" align="center">5.08</td>
<td valign="top" align="center">5.06</td>
<td valign="top" align="center">5.22</td>
<td valign="top" align="center">0.10</td>
<td valign="top" align="center">0.96</td>
<td valign="top" align="center">0.63</td>
<td valign="top" align="center">0.94</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">5.77</td>
<td valign="top" align="center">5.78</td>
<td valign="top" align="center">5.99</td>
<td valign="top" align="center">5.96</td>
<td valign="top" align="center">0.06</td>
<td valign="top" align="center">0.98</td>
<td valign="top" align="center">0.73</td>
<td valign="top" align="center">0.97</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Insulin (INS) (uIU/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">14.95</td>
<td valign="top" align="center">14.04</td>
<td valign="top" align="center">13.91</td>
<td valign="top" align="center">12.79</td>
<td valign="top" align="center">0.59</td>
<td valign="top" align="center">0.63</td>
<td valign="top" align="center">0.22</td>
<td valign="top" align="center">0.93</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">13.56</td>
<td valign="top" align="center">13.03</td>
<td valign="top" align="center">13.25</td>
<td valign="top" align="center">12.45</td>
<td valign="top" align="center">0.39</td>
<td valign="top" align="center">0.76</td>
<td valign="top" align="center">0.37</td>
<td valign="top" align="center">0.86</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Different lowercase letters on the same data point indicate significant differences (<italic>P</italic> &#x003C; 0.05), different uppercase letters indicate highly significant differences (<italic>P</italic> &#x003C; 0.01), and identical letters or no letters indicate no significant differences (<italic>P</italic> &#x003E; 0.05).</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS9">
<label>3.9</label>
<title>The effect of supplementing LE on plasma antioxidant indicators in <italic>Hu</italic> lambs</title>
<p>As shown in <xref ref-type="table" rid="T6">Table 6</xref>, the NO content in the experimental group showed a secondary change at 4 h post-supplementation (<italic>P</italic> &#x003C; 0.05). However, no significant differences (<italic>P</italic> &#x003E; 0.05) were found in the plasma activities of T-AOC, CAT, SOD, GSH-Px, or MDA content between the 0-h pre-supplementation and 4-h post-supplementation time points across all experimental groups.</p>
<table-wrap position="float" id="T6">
<label>TABLE 6</label>
<caption><p>Effects of supplemental LE on plasma antioxidants in <italic>Hu</italic> lambs (<italic>n</italic> = 5).</p></caption>
<table cellspacing="5" cellpadding="5" frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="center">Items</th>
<th valign="top" align="center">Time</th>
<th valign="top" align="center" colspan="4">Groups</th>
<th valign="top" align="center"><italic>SEM</italic></th>
<th valign="top" align="center" colspan="3"><italic>P</italic>-value</th>
</tr>
<tr>
<th valign="top" align="center"/>
<th valign="top" align="center"/>
<th valign="top" align="center">CON</th>
<th valign="top" align="center">T1</th>
<th valign="top" align="center">T2</th>
<th valign="top" align="center">T3</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Anova</th>
<th valign="top" align="center">Linear</th>
<th valign="top" align="center">Quadratic</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center" rowspan="2">Total antioxidant capacity (T-AOC)<break/> (U/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">74.60</td>
<td valign="top" align="center">73.21</td>
<td valign="top" align="center">73.71</td>
<td valign="top" align="center">80.38</td>
<td valign="top" align="center">0.67</td>
<td valign="top" align="center">0.58</td>
<td valign="top" align="center">0.34</td>
<td valign="top" align="center">0.34</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">72.45</td>
<td valign="top" align="center">76.41</td>
<td valign="top" align="center">81.23</td>
<td valign="top" align="center">80.83</td>
<td valign="top" align="center">1.45</td>
<td valign="top" align="center">0.27</td>
<td valign="top" align="center">0.07</td>
<td valign="top" align="center">0.54</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Catalase (CAT)<break/> (U/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">47.08</td>
<td valign="top" align="center">48.45</td>
<td valign="top" align="center">48.56</td>
<td valign="top" align="center">48.49</td>
<td valign="top" align="center">0.09</td>
<td valign="top" align="center">0.97</td>
<td valign="top" align="center">0.69</td>
<td valign="top" align="center">0.77</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">52.33</td>
<td valign="top" align="center">51.02</td>
<td valign="top" align="center">52.45</td>
<td valign="top" align="center">55.75</td>
<td valign="top" align="center">1.17</td>
<td valign="top" align="center">0.35</td>
<td valign="top" align="center">0.18</td>
<td valign="top" align="center">0.24</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Superoxide dismutase (SOD)<break/> (U/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">4.48</td>
<td valign="top" align="center">4.50</td>
<td valign="top" align="center">3.50</td>
<td valign="top" align="center">3.82</td>
<td valign="top" align="center">2.39</td>
<td valign="top" align="center">0.11</td>
<td valign="top" align="center">0.06</td>
<td valign="top" align="center">0.64</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">3.49</td>
<td valign="top" align="center">3.47</td>
<td valign="top" align="center">3.55</td>
<td valign="top" align="center">3.42</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">0.99</td>
<td valign="top" align="center">0.93</td>
<td valign="top" align="center">0.82</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Glutathione peroxidase (GSH-Px)<break/> (U/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">9.95</td>
<td valign="top" align="center">9.48</td>
<td valign="top" align="center">9.88</td>
<td valign="top" align="center">9.65</td>
<td valign="top" align="center">1.48</td>
<td valign="top" align="center">0.26</td>
<td valign="top" align="center">0.53</td>
<td valign="top" align="center">0.52</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">10.36</td>
<td valign="top" align="center">10.32</td>
<td valign="top" align="center">10.28</td>
<td valign="top" align="center">10.37</td>
<td valign="top" align="center">0.05</td>
<td valign="top" align="center">0.98</td>
<td valign="top" align="center">0.96</td>
<td valign="top" align="center">0.73</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Malondialdehyde (MDA)<break/> (nmol/mL)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">154.82</td>
<td valign="top" align="center">152.82</td>
<td valign="top" align="center">159.93</td>
<td valign="top" align="center">155.03</td>
<td valign="top" align="center">0.18</td>
<td valign="top" align="center">0.91</td>
<td valign="top" align="center">0.80</td>
<td valign="top" align="center">0.84</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">170.92</td>
<td valign="top" align="center">161.62</td>
<td valign="top" align="center">161.78</td>
<td valign="top" align="center">170.47</td>
<td valign="top" align="center">0.67</td>
<td valign="top" align="center">0.58</td>
<td valign="top" align="center">0.97</td>
<td valign="top" align="center">0.18</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Nitric oxide (NO)<break/> (&#x03BC;mol/L)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">49.85</td>
<td valign="top" align="center">52.13</td>
<td valign="top" align="center">51.39</td>
<td valign="top" align="center">45.42</td>
<td valign="top" align="center">1.80</td>
<td valign="top" align="center">0.19</td>
<td valign="top" align="center">0.18</td>
<td valign="top" align="center">0.08</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">57.64<sup>a</sup></td>
<td valign="top" align="center">49.37<sup>b</sup></td>
<td valign="top" align="center">49.84<sup>b</sup></td>
<td valign="top" align="center">52.67<sup>ab</sup></td>
<td valign="top" align="center">4.62</td>
<td valign="top" align="center">0.02</td>
<td valign="top" align="center">0.09</td>
<td valign="top" align="center">&#x003C;0.01</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Different lowercase letters on the same data point indicate significant differences (<italic>P</italic> &#x003C; 0.05), different uppercase letters indicate highly significant differences (<italic>P</italic> &#x003C; 0.01), and identical letters or no letters indicate no significant differences (<italic>P</italic> &#x003E; 0.05).</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS10">
<label>3.10</label>
<title>The effect of LE on plasma protein levels in <italic>Hu</italic> lambs</title>
<p>As shown in <xref ref-type="table" rid="T7">Table 7</xref>, no significant differences were observed in the levels of TP, ALB, and GLB at 0 h before or 4 h after supplementation among the experimental groups compared to the CON group (<italic>P</italic> &#x003E; 0.05).</p>
<table-wrap position="float" id="T7">
<label>TABLE 7</label>
<caption><p>Effects of LE on plasma proteins in <italic>Hu</italic> lambs (<italic>n</italic> = 5).</p></caption>
<table cellspacing="5" cellpadding="5" frame="box" rules="all">
<thead>
<tr>
<th valign="top" align="center">Items</th>
<th valign="top" align="center">Time</th>
<th valign="top" align="center" colspan="4">Groups</th>
<th valign="top" align="center"><italic>SEM</italic></th>
<th valign="top" align="center" colspan="3"><italic>P</italic>-value</th>
</tr>
<tr>
<th valign="top" align="center"/>
<th valign="top" align="center"/>
<th valign="top" align="center">CON</th>
<th valign="top" align="center">T1</th>
<th valign="top" align="center">T2</th>
<th valign="top" align="center">T3</th>
<th valign="top" align="center"/>
<th valign="top" align="center">Anova</th>
<th valign="top" align="center">Linear</th>
<th valign="top" align="center">Quadratic</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center" rowspan="2">Total protein (TP)<break/> (g/L)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">61.78</td>
<td valign="top" align="center">60.24</td>
<td valign="top" align="center">61.66</td>
<td valign="top" align="center">60.92</td>
<td valign="top" align="center">0.23</td>
<td valign="top" align="center">0.88</td>
<td valign="top" align="center">0.77</td>
<td valign="top" align="center">0.79</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">57.70</td>
<td valign="top" align="center">56.96</td>
<td valign="top" align="center">57.20</td>
<td valign="top" align="center">57.22</td>
<td valign="top" align="center">0.08</td>
<td valign="top" align="center">0.97</td>
<td valign="top" align="center">0.81</td>
<td valign="top" align="center">0.73</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Albumin (ALB)(g/L)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">31.56</td>
<td valign="top" align="center">32.52</td>
<td valign="top" align="center">32.76</td>
<td valign="top" align="center">32.26</td>
<td valign="top" align="center">0.21</td>
<td valign="top" align="center">0.89</td>
<td valign="top" align="center">0.65</td>
<td valign="top" align="center">0.53</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">31.56</td>
<td valign="top" align="center">30.20</td>
<td valign="top" align="center">31.16</td>
<td valign="top" align="center">30.42</td>
<td valign="top" align="center">0.32</td>
<td valign="top" align="center">0.81</td>
<td valign="top" align="center">0.63</td>
<td valign="top" align="center">0.79</td>
</tr>
<tr>
<td valign="top" align="center" rowspan="2">Globulin (GLB)(g/L)</td>
<td valign="top" align="center">0 h</td>
<td valign="top" align="center">30.22</td>
<td valign="top" align="center">27.92</td>
<td valign="top" align="center">28.90</td>
<td valign="top" align="center">28.66</td>
<td valign="top" align="center">0.18</td>
<td valign="top" align="center">0.91</td>
<td valign="top" align="center">0.72</td>
<td valign="top" align="center">0.66</td>
</tr>
<tr>
<td valign="top" align="center">4 h</td>
<td valign="top" align="center">26.14</td>
<td valign="top" align="center">26.76</td>
<td valign="top" align="center">26.04</td>
<td valign="top" align="center">26.80</td>
<td valign="top" align="center">0.06</td>
<td valign="top" align="center">0.98</td>
<td valign="top" align="center">0.87</td>
<td valign="top" align="center">0.97</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn><p>Different lowercase letters on the same data point indicate significant differences (<italic>P</italic> &#x003C; 0.05), different uppercase letters indicate highly significant differences (<italic>P</italic> &#x003C; 0.01), and identical letters or no letters indicate no significant differences (<italic>P</italic> &#x003E; 0.05).</p></fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="S3.SS11">
<label>3.11</label>
<title>Correlation analysis between growth performance of <italic>Hu</italic> lambs and rumen microorganisms</title>
<p>The results of correlation analysis between the growth performance of <italic>Hu</italic> lambs and the rumen microbiota in <xref ref-type="fig" rid="F9">Figure 9</xref>. At the phylum level, the abundance of <italic>Firmicutes</italic> in rumen fluid showed a significant positive correlation with the ADG of <italic>Hu</italic> lambs (<italic>P</italic> &#x003C; 0.05), while the abundance of <italic>Bacteroidota</italic> in rumen fluid exhibited a significant negative correlation with ADG (<italic>P</italic> &#x003C; 0.05). At the family level, the abundance of <italic>Selenomonadaceae</italic> in rumen fluid demonstrated a significant positive correlation with ADG (<italic>P</italic> &#x003C; 0.05). At the genus level, <italic>Prevotella</italic> abundance in rumen fluid was negatively correlated with ADG (<italic>P</italic> &#x003C; 0.05).</p>
<fig id="F9" position="float">
<label>FIGURE 9</label>
<caption><p>Relationship between ruminal microbiota features and lamb growth performance traits.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g009.tif">
<alt-text content-type="machine-generated">Heatmap showing the association of various bacterial taxa and groups with ADG values. Taxa names are displayed along the horizontal axis, with colors ranging from blue (negative association, -0.4) to red (positive association, 0.4) according to the color scale on the right.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS12">
<label>3.12</label>
<title>Phylum level correlation analysis</title>
<p>The results of a correlation analysis investigating the relationships between LE supplementation and growth performance, reproductive hormone indicators, and rumen microbiota in <italic>Hu</italic> lambs, which showed in <xref ref-type="fig" rid="F10">Figure 10</xref>. At the phylum level, the top 10 bacterial phyla correlated with growth performance and hormone levels were <italic>Bacteroidota</italic>, <italic>Firmicutes</italic>, <italic>Euryarchaeota</italic>, <italic>Proteobacteria</italic>, <italic>Spirochaetota</italic>, <italic>Patescibacteria</italic>, <italic>Synergistota</italic>, <italic>Cyanobacteria</italic>, <italic>Fibrobacterota</italic>, and <italic>Verrucomicrobiota</italic>. Among these, <italic>Patescibacteria</italic> was significantly negatively correlated with ADG (<italic>P</italic> &#x003C; 0.05), while it was positively correlated with rumen fermentation parameters (<italic>P</italic> &#x003C; 0.05). Additionally, <italic>Firmicutes</italic> and <italic>Verrucomicrobiota</italic> exhibited a highly significant positive correlation with fermentation parameters (<italic>P &#x003C;</italic> 0.01). Regarding hormone levels, <italic>Bacteroidota</italic> and <italic>Euryarchaeota</italic> were significantly negatively correlated (<italic>P</italic> &#x003C; 0.05), and <italic>Patescibacteria</italic> showed a highly significant negative correlation with hormone levels (<italic>P</italic> &#x003C; 0.01).</p>
<fig id="F10" position="float">
<label>FIGURE 10</label>
<caption><p>Clustered heatmap of phylum-level correlation analysis. &#x002A;Indicates <italic>P</italic> &#x003C; 0.05. &#x002A;&#x002A;Indicates <italic>P</italic> &#x003C; 0.01.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g010.tif">
<alt-text content-type="machine-generated">Heatmap showing correlations between various biological parameters (listed on the left) and bacterial phyla (listed at the bottom), with colors ranging from blue (negative correlation) to red (positive correlation) and asterisks marking significance.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS13">
<label>3.13</label>
<title>Correlation analysis of family levels</title>
<p>The top 10 bacterial families correlated with growth performance, hormone levels, and rumen fermentation parameters illustrated <xref ref-type="fig" rid="F11">Figure 11</xref>, which includes <italic>Prevotellaceae</italic>, <italic>Selenomonadaceae</italic>, <italic>Rikenellaceae, F082</italic>, <italic>Lachnospiraceae</italic>, <italic>Acidaminococcaceae</italic>, <italic>Bacteroidales_RF16_group</italic>, <italic>Oscillospiraceae</italic>, <italic>Eubacterium_coprostanoligenes_group</italic>, and <italic>Methanobrevibacteraceae</italic>. At the family level, no significant correlation with ADG was observed, although a general positive trend was observed. Regarding rumen fermentation parameters, <italic>Lachnospiraceae</italic>, <italic>Oscillospiraceae</italic>, and <italic>Eubacterium_coprostanoligenes_group</italic> exhibited a highly significant positive correlation (<italic>P</italic> &#x003C; 0.01). In terms of hormonal associations, a significant negative correlation was identified between estrogen levels at 4 h and the family <italic>F082</italic> (<italic>P</italic> &#x003C; 0.05), while <italic>Rikenellaceae</italic> showed a significant negative correlation with GH levels at 4 h (<italic>P</italic> &#x003C; 0.05).</p>
<fig id="F11" position="float">
<label>FIGURE 11</label>
<caption><p>Clustered heatmap of family-level correlation analysis. &#x002A;Indicates <italic>P</italic> &#x003C; 0.05. &#x002A;&#x002A;Indicates <italic>P</italic> &#x003C; 0.01.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g011.tif">
<alt-text content-type="machine-generated">Heatmap showing correlations between various bacterial families and metabolic indicators, with color ranging from blue for negative correlation to red for positive, and stars marking statistical significance. Vertical labels represent bacterial families; horizontal labels represent metabolic variables.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S3.SS14">
<label>3.14</label>
<title>Correlation analysis of genus levels</title>
<p>The effects of varying levels of LE supplementation on the rumen microbiota structure at the genus level in <italic>Hu</italic> lambs, which presents <xref ref-type="fig" rid="F12">Figure 12</xref>. The top 10 most abundant genera were <italic>Prevotella</italic>, <italic>Rikenellaceae_RC9_gut_group</italic>, <italic>Veillonellaceae_UCG-001</italic>, <italic>Prevotellaceae_UCG-001</italic>, <italic>Succiniclasticum</italic>, <italic>Prevotellaceae_UCG-003</italic>, <italic>Quinella</italic>, <italic>Selenomonas</italic>, <italic>UCG-002</italic>, and <italic>Methanobrevibacter</italic>. At the genus level, <italic>Quinella</italic> showed a highly significant positive correlation with propionate and isovalerate (<italic>P</italic> &#x003C; 0.01) and a significant positive correlation with isobutyrate and total volatile fatty acids (TVFA) (<italic>P</italic> &#x003C; 0.05). The genus <italic>UCG-002</italic> exhibited a significant positive correlation with INS levels (<italic>P</italic> &#x003C; 0.05). In contrast, the genera <italic>Prevotellaceae_UCG-003</italic>, <italic>Succiniclasticum</italic>, <italic>Prevotella</italic>, <italic>Prevotellaceae_UCG-001</italic>, and <italic>Methanobrevibacter</italic> were negatively correlated with hormone levels. Notably, <italic>Prevotellaceae_UCG-003</italic> showed a highly significant negative correlation with T concentration at 0 h (<italic>P</italic> &#x003C; 0.01).</p>
<fig id="F12" position="float">
<label>FIGURE 12</label>
<caption><p>Clustered heatmap of genus-level correlation analysis. &#x002A;Indicates <italic>P</italic> &#x003C; 0.05. &#x002A;&#x002A;Indicates <italic>P</italic> &#x003C; 0.01.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g012.tif">
<alt-text content-type="machine-generated">Heatmap showing correlations between bacterial genera (listed along the bottom) and various metabolic parameters (listed along the left side). Color ranges from blue (negative correlation) to red (positive correlation), with darker colors indicating stronger correlations. Asterisks within cells indicate statistical significance.</alt-text>
</graphic>
</fig>
</sec>
</sec>
<sec id="S4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>The efficient degradation of feed in ruminants largely depends on the homeostasis of the ruminal internal environment, which is closely associated with rumen pH, NH<sub>3</sub>-N concentration, and VFA levels (<xref ref-type="bibr" rid="B3">Castro-Montoya et al., 2011</xref>). Rumen pH serves as a critical physiological indicator of this balance, and deviations from the normal range (typically 5.5&#x2013;7.5) can disrupt fermentation processes (<xref ref-type="bibr" rid="B29">Qiu et al., 2022</xref>). In the present study, rumen pH values across all lamb groups remained within the normal physiological range following LE supplementation, indicating that LE administration did not significantly affect ruminal fermentation.</p>
<p>The NH<sub>3</sub>-N in the rumen is derived from the microbial breakdown of non-fiber feed components. It serves as a key nitrogen substrate in microbial anabolism, supporting the growth and proliferation of bacteria and other microorganisms essential for microbial protein synthesis (<xref ref-type="bibr" rid="B13">Jefferson et al., 2022</xref>). Receptors for steroid sex hormones, such as T, E<sub>2</sub>, and progesterone (P), have been identified in the cytoplasm and nuclei of rumen bacteria. The binding of these hormones to their receptors can influence ruminal metabolism in ruminants (<xref ref-type="bibr" rid="B10">Han, 2006</xref>). <xref ref-type="bibr" rid="B5">Chen et al. (1999)</xref> demonstrated that daidzein supplementation via duodenal infusion in male water buffaloes increased blood T levels and significantly elevated ruminal concentrations of both NH<sub>3</sub>-N and TVFA. The increase in ruminal NH<sub>3</sub>-N concentration following LE-induced elevation in plasma T is likely mediated by T binding to microbial hormone receptors. This suggests that elevated T may interact with hormone receptors on rumen microbes, modulating the microbial community and thereby enhancing NH<sub>3</sub>-N production.</p>
<p>Short-chain fatty acids (SCFAs) in the rumen are primarily synthesized through microbial fermentation of feed. The VFAs, a major component of SCFAs, serve as the primary energy source for ruminants, providing 70-80% of their total energy needs (<xref ref-type="bibr" rid="B18">Kumar et al., 2024</xref>). The present study demonstrated that LE supplementation induced a significant shift in the ruminal A:P, indicating a broader modulatory effect of LE on rumen fermentation. Propionate is a critical contributor to weight gain in ruminants, with its adequate availability being essential for maintaining healthy growth (<xref ref-type="bibr" rid="B44">Zhang et al., 2022</xref>). A highly significant linear increase in ruminal propionate concentration was observed with increasing doses of LE, likely due to T-enhanced microbial carbohydrate degradation. However, this shift in ruminal fermentation did not result in improved growth performance, such as ADG, in lambs. This lack of response may be attributed to the relatively short trial duration, suggesting that further investigation is needed to determine the optimal dosage and duration of LE supplementation for maximizing growth performance.</p>
<p>The rumen of ruminants harbors a complex consortium of symbiotic microorganisms, including bacteria, archaea, ciliates, fungi, and viruses (<xref ref-type="bibr" rid="B6">Firkins and Yu, 2015</xref>). Among these, the phyla <italic>Firmicutes</italic> and <italic>Bacteroidetes</italic> are the most abundant, containing numerous fibrolytic genera such as <italic>Succiniclasticum</italic>, <italic>Prevotella</italic>, and <italic>Ruminococcus</italic>, which form the core ruminal microbiota (<xref ref-type="bibr" rid="B25">Mizrahi et al., 2021</xref>). These microbes play a critical role in degrading plant fibers and polysaccharides, fermenting them into intermediates such as succinate, lactate, and fumarate, which are then converted into end products including VFAs, microbial protein, and other nutrients that provide energy to the host (<xref ref-type="bibr" rid="B34">Schwab and Broderick, 2017</xref>). Consequently, the rumen microbiota is central to the digestive and metabolic processes of ruminants. A key finding of this study was the significant alteration in the core ruminal microbiota following LE supplementation, specifically a decrease in the relative abundance of <italic>Bacteroidetes</italic> and an increase in <italic>Firmicutes</italic> compared to the CON group. Furthermore, the correlation analysis between the growth performance of <italic>Hu</italic> sheep lambs and rumen microbiota revealed a significant positive correlation between the relative abundance of Firmicutes and the average daily gain (ADG) of lambs. Given that <italic>Firmicutes</italic> are involved in the conversion of dietary fiber to VFAs (<xref ref-type="bibr" rid="B15">Ko et al., 2020</xref>), while <italic>Bacteroidetes</italic> are critical for polysaccharide breakdown, this shift suggests a potential modification in the ruminal metabolic landscape. Previous studies have linked a higher <italic>Firmicutes-to-Bacteroidetes</italic> (F/B) ratio with improved growth performance (<xref ref-type="bibr" rid="B2">Bauman et al., 2011</xref>; <xref ref-type="bibr" rid="B12">Huangfu, 2023</xref>). Our correlation analysis between the rumen microbiota and growth parameters in lambs produced similar findings, further supporting this relationship. The observed increase in TVFA and propionate levels may be attributed to the elevated relative abundance of <italic>Firmicutes</italic>. At the genus level, <italic>Succiniclasticum</italic> abundance was consistently higher in all treatment groups compared to the CON group. This genus is known for its ability to degrade fiber to produce succinate, which is then converted to propionate, providing energy to the host. Therefore, the increase in <italic>Succiniclasticum</italic> abundance likely contributed to the elevated propionate concentration observed in this study.</p>
<p>The growth, development, and metabolic processes of animals are regulated by various factors, with hormones and growth factors playing pivotal roles (<xref ref-type="bibr" rid="B24">Mei, 2024</xref>). In male animals, T, as a primary reproductive hormone, not only exerts hormonal effects but also regulates critical physiological processes such as appetite control, protein metabolism, and lipid metabolism (<xref ref-type="bibr" rid="B43">Yutong et al., 2025</xref>). During osteoblast differentiation, T helps maintain bone growth and ameliorate osteoporosis (<xref ref-type="bibr" rid="B38">Vanderschueren et al., 2014</xref>). Endogenous T has also been found to suppress the response of melanin-concentrating hormone (MCH) neurons to glucose, thereby reducing post-fasting plasma glucose levels, enhancing induced satiety, and increasing feed intake (<xref ref-type="bibr" rid="B8">Fukushima et al., 2015</xref>). It has further been shown to promote protein synthesis in skeletal muscle and facilitate skeletal growth, contributing to improved overall growth performance in animals (<xref ref-type="bibr" rid="B23">McClure et al., 2000</xref>; <xref ref-type="bibr" rid="B45">Zhang et al., 2019</xref>). Research indicates that sustained T circulation in lambs has both direct and indirect effects on muscle protein synthesis and bone growth, which collectively enhance growth performance (<xref ref-type="bibr" rid="B32">Schanbacher et al., 1980</xref>). A study by <xref ref-type="bibr" rid="B19">Li et al. (2019)</xref> found that laying hens supplemented with 0.5 mg/d of LE for 6 weeks showed a significant increase in body weight. Similarly, <xref ref-type="bibr" rid="B30">Rezaei et al. (2020)</xref> demonstrated that LE supplementation in goats significantly increased ADG and F:G, positively affecting growth performance. However, in the present study, no significant changes in growth performance were observed in lambs following LE supplementation. Existing research indicates that T plays a role in regulating both protein and lipid metabolism, promoting protein anabolism while also stimulating lipid catabolism (<xref ref-type="bibr" rid="B9">Guo, 2015</xref>). Lipid metabolism is particularly crucial for the short-term improvement of animal growth performance. In this trial, although LE supplementation increased circulating T concentrations in lambs, it did not result in enhanced ADG. It is hypothesized that the weight gain from T-stimulated muscle protein synthesis may have been counteracted by concurrent lipid catabolism, leading to no net improvement in overall growth performance.</p>
<p>Animal growth is regulated by GH, and elevated T levels can stimulate GH secretion, which, in turn, plays a key role in various developmental and metabolic processes such as protein synthesis, growth promotion, and lipolysis (<xref ref-type="bibr" rid="B36">Song et al., 2023</xref>). In contrast, INS exerts opposing effects to GH in lipogenesis, enhancing tissue glucose uptake and fatty acid synthesis by promoting fatty acid synthase (FAS) expression (<xref ref-type="bibr" rid="B9">Guo, 2015</xref>). As a highly selective cytochrome P450 aromatase inhibitor, LE effectively blocks the conversion of T to E<sub>2</sub>, thereby elevating systemic T levels. This action is hormonally selective and does not interfere with the normal secretion of corticosteroids or thyroid hormones (<xref ref-type="bibr" rid="B22">Liu et al., 2024</xref>). <xref ref-type="bibr" rid="B7">Fu (2023)</xref> demonstrated that oral administration of varying doses of LE (0.1, 1.0, and 10 mg/kg/d) to female juvenile mice reduced ovarian E<sub>2</sub> levels and increased T levels. Similarly, <xref ref-type="bibr" rid="B26">Ortiz-Carrera et al. (2019)</xref> observed a significant increase in serum T levels following supplementation with 2.5 mg/d LE in male goats, with serum E<sub>2</sub> levels remaining unchanged. These findings align with the results of the present study.</p>
<p>Plasma biomarkers such as TP, ALB, and GLB&#x2014;which reflect protein assimilation, transport and repair, and immune function, respectively (<xref ref-type="bibr" rid="B27">Peng et al., 2020</xref>)&#x2014;were analyzed. All concentrations were within normal physiological ranges, and no significant differences were observed among groups. This suggests that LE supplementation did not have an overt impact on these parameters under the current experimental conditions. Therefore, the potential immunomodulatory effects of LE in <italic>Hu</italic> lambs warrant further investigation under different conditions or with more targeted immune challenges.</p>
<p>During metabolic processes, organisms generate various highly reactive oxygen species (ROS), reactive nitrogen species (RNS), and singlet oxygen. When present in excessive concentrations, these molecules can damage intracellular macromolecules, such as DNA and proteins, contributing to the pathogenesis of numerous diseases (<xref ref-type="bibr" rid="B28">Pisoschi and Pop, 2015</xref>). It has been suggested that androgens help mitigate oxidative stress in organisms. A study by <xref ref-type="bibr" rid="B39">Wang (2023)</xref> found that T deficiency exacerbated oxidative damage in the hippocampal region of male APP/PS1 mice, a model of Alzheimer&#x2019;s disease. Additionally, <xref ref-type="bibr" rid="B41">Yao (2022)</xref> reported that during heat stress, castrated beef cattle showed significantly lower activities of T-AOC, SOD, and GSH-Px compared to partially castrated and sham-operated groups. <xref ref-type="bibr" rid="B4">Chen (2016)</xref> observed that LE supplementation in bulls increased T-AOC and reduced MDA content in seminal plasma. As an aromatase inhibitor, LE works by inhibiting aromatase activity, thus blocking the conversion of androstenedione (AD) and T to estrogens, which indirectly elevates androgen levels in muscle tissue (<xref ref-type="bibr" rid="B1">Bai et al., 2015</xref>). In the present study, LE supplementation did not significantly affect most plasma antioxidant parameters (T-AOC, CAT, SOD, GSH-Px) or MDA levels in <italic>Hu</italic> lambs. However, a notable decrease in NO concentration was recorded 4 h after supplementation in the T1 and T2 groups. The discrepancy between these results and previous findings may be attributed to the varying stress conditions inherent to the experimental models.</p>
<p>In summary, dietary LE supplementation appears to enhance the ruminal fermentation pattern and fiber degradation capacity by modulating the microbial community (<xref ref-type="fig" rid="F13">Figure 13</xref>). This aligns with previous research identifying E<sub>2</sub>, P, and T in ruminant rumen fluid, with T shown to promote ruminal fermentation (<xref ref-type="bibr" rid="B10">Han, 2006</xref>). Additionally, <xref ref-type="bibr" rid="B35">Silva et al. (2024)</xref> reported greater ruminal microbial diversity in male ruminants compared to females. Alpha-diversity indices (including Observed OTUs, Chao1, and Simpson) reflect community richness and diversity. In this study, Group T3 exhibited a significantly higher number of OTUs compared to the CON group, with an even more pronounced increase compared to Group T1. Furthermore, all alpha-diversity indices (OTUs, Chao1, Simpson) showed significant enhancement with increasing LE doses. These findings collectively suggest that LE supplementation increased both the diversity and richness of the ruminal microbiota in lambs, likely due to LE&#x2019;s inhibition of androgen aromatization, which indirectly shaped the ruminal microbial environment.</p>
<fig id="F13" position="float">
<label>FIGURE 13</label>
<caption><p>Effect of LE on rumen microflora structure and blood biochemical indexes of lambs.</p></caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmicb-17-1734219-g013.tif">
<alt-text content-type="machine-generated">Diagram illustrating how dietary intake (LE) in a lamb affects the rumen&#x2019;s microbial composition, which influences the production of microbial protein, volatile fatty acids, and certain metabolites, impacting blood vessel biochemistry and testosterone levels.</alt-text>
</graphic>
</fig>
</sec>
<sec id="S5" sec-type="conclusion">
<label>5</label>
<title>Conclusion</title>
<p>Under the experimental conditions, LE supplementation increased lambs&#x2019; concentrations of NH<sub>3</sub>-N, propionic acid, and isovaleric acid, elevated the relative abundance of the <italic>Firmicutes</italic>, reduced the relative abundance of the <italic>Bacteroidetes</italic>, altered rumen fermentation patterns, and promoted an increase in plasma testosterone concentration. In comparison, LE supplementation at a dose of 0.2 mg/kg BW yielded superior effects.</p>
</sec>
</body>
<back>
<sec id="S6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The data presented in this study are publicly available. The data can be found here: <ext-link ext-link-type="uri" xlink:href="https://www.ncbi.nlm.nih.gov/sra">https://www.ncbi.nlm.nih.gov/sra</ext-link>, accession <ext-link ext-link-type="DDBJ/EMBL/GenBank" xlink:href="PRJNA1353064">PRJNA1353064</ext-link>.</p>
</sec>
<sec id="S7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>All procedures in this study were approved by the Animal Experiment Ethics Committee of Xinjiang Agricultural University (Protocol Permit Number: 2020032, 7 May 2020; permit number: 2020024, 20 March 2020). All experimental animals, design, and management were conducted in compliance with the &#x201C;Animal Research: Reporting of In Vivo Experiments&#x201D; (ARRIVE) guidelines (<ext-link ext-link-type="uri" xlink:href="https://arriveguidelines.org">https://arriveguidelines.org</ext-link>). The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent was obtained from the owners for the participation of their animals in this study.</p>
</sec>
<sec id="S8" sec-type="author-contributions">
<title>Author contributions</title>
<p>LY: Data curation, Methodology, Writing &#x2013; review &#x0026; editing, Writing &#x2013; original draft. TL: Writing &#x2013; review &#x0026; editing, Data curation, Methodology. RL: Writing &#x2013; review &#x0026; editing, Methodology, Data curation. YZ: Writing &#x2013; review &#x0026; editing, Data curation, Methodology. MA: Data curation, Methodology, Writing &#x2013; review &#x0026; editing. SW: Data curation, Methodology, Writing &#x2013; review &#x0026; editing. ZL: Writing &#x2013; review &#x0026; editing, Methodology, Data curation. KY: Conceptualization, Methodology, Investigation, Supervision, Funding acquisition, Writing &#x2013; review &#x0026; editing, Software, Project administration, Formal analysis, Writing &#x2013; original draft, Visualization, Resources, Data curation, Validation. CW: Project administration, Writing &#x2013; review &#x0026; editing, Supervision, Investigation, Writing &#x2013; original draft, Conceptualization, Methodology, Funding acquisition, Visualization, Data curation, Formal analysis, Resources, Validation, Software.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>We express the gratitude to the Xinjiang Herbivore Nutrition Laboratory for Meat &#x0026; Milk and the support of Xinjiang Shangpin Meiyang Technology Co., Ltd.</p>
</ack>
<sec id="S10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>ZL was employed by the Xinjiang Shangpin Meiyang Technology Co., Ltd.</p>
<p>The remaining author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</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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<fn-group>
<fn id="n1" fn-type="custom" custom-type="edited-by"><p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1420077/overview">P. K. Malik</ext-link>, National Institute of Animal Nutrition and Physiology (ICAR), India</p></fn>
<fn id="n2" fn-type="custom" custom-type="reviewed-by"><p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/715433/overview">Jitendra Kumar Sundaray</ext-link>, Indian Council of Agricultural Research, India</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/3317266/overview">Lamella Ojha</ext-link>, ICAR - Mahatma Gandhi Integrated Farming Research Institute, India</p></fn>
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