Abstract

   Dietary l-carnosine supplementation has been shown to enhance animal
   performance and improve meat quality. However, the mechanisms
   underlying the effects of l-carnosine on the physiological functions of
   animals have not been fully elucidated. We investigated the effects of
   dietary l-carnosine supplementation on growth performance, intestinal
   microbiota diversity, and the serum metabolome in fattening lambs to
   reveal the molecular mechanism underlying the effect of l-carnosine on
   the growth performance of sheep. Sixty 3-month-old male crossbred lambs
   (Dorper ♂ × Small Tail Han ♀) with an average body weight of 30 ± 5 kg
   were randomly divided into two groups: a control group (group C) fed a
   basal diet, and an experimental group (group L) fed a basal diet
   supplemented with 400 mg/kg of l-carnosine. At the end of the 60-day
   experiment, all sheep were weighed, and fecal and blood samples were
   collected from 12 random sheep. The fecal microbiota was analyzed using
   16S rRNA sequencing, and serum metabolites were analyzed using liquid
   chromatography–tandem mass spectrometry. Spearman correlation analysis
   was employed to assess the associations between intestinal microbiota
   and serum metabolite biomarkers. The results showed that weight gain
   and daily weight gain were significantly increased in group L compared
   to group C (p < 0.01). The dominant phyla in the intestinal microbiota
   (Firmicutes and Bacteroidetes) did not significantly differ between the
   two groups (p > 0.05). At the genus level, the abundances of
   Syntrophococcus (p < 0.01) and Butyricimonas (p < 0.001) were higher,
   whereas those of Escherichia-Shigella and Candidatus Saccharimonas were
   significantly lower in group L than in group C (p < 0.05). Non-targeted
   metabolomics identified 68 differentially abundant biomarkers (VIP > 1,
   p < 0.05). The content of pyridine N-oxide glucuronide was
   significantly downregulated (p < 0.01), whereas those of l-histidinol,
   d-apiose, and isodomedin were significantly upregulated in group L
   versus group C (p < 0.001). Holdemania and Butyricimonas were
   positively correlated with l-histidine, d-apiose, and l-erythrulose
   (p < 0.001), whereas Butyricimonas was negatively correlated with
   pyridine N-oxide glucuronide (p < 0.001). This study provided new
   insights into the effects of l-carnosine on the intestinal microbiota
   and nutrient metabolism in fattening sheep that will be helpful for the
   future application of l-carnosine in ruminants.

   Keywords: fattening lamb, L-carnosine, microbiota, metabolomics,
   multi-omics analysis

1. Introduction

   With the enhancement of human living standards, the demand for
   livestock products is increasing, which is an excellent opportunity for
   animal husbandry, including the sheep farming industry ([31]1).
   Carnosine is a dipeptide found in animals ([32]2), but its content
   varies among species and animal body parts ([33]3, [34]4). Carnosine
   and l-carnosine have the same chemical structure and biological
   activity, and as the amino acid residues in carnosine have an l-form
   stereochemical configuration, it can also be referred to as
   l-carnosine. l-Carnosine is present at high concentrations in the
   skeletal muscle of most vertebrates and has critical antioxidant
   functions ([35]5). In porcine myoblasts, it promoted cell proliferation
   by activating targets of the mammalian the rapamycin signaling pathway
   and mitigated cellular damage caused by oxidative stress ([36]6). In
   mice exposed to deoxynivalenol, l-carnosine bound to Keap1, releasing
   the transcription factor Nrf2 into the nucleus, thereby activating the
   transcription of downstream genes and increasing antioxidant production
   to neutralize excess reactive oxygen species and thus reduce the
   oxidative stress caused by deoxynivalenol ([37]7). Further, l-carnosine
   helps maintain animal health through anti-glycosylation ([38]8, [39]9),
   pH stabilization, and metal chelation ([40]10). Studies have shown that
   l-carnosine ameliorates the adverse effects of oxidative stress in
   pregnant ewes, and it may also offer benefits in reducing the combined
   challenges posed by pregnancy and heat stress during the hot-dry season
   ([41]11). In finishing pigs, dietary l-carnosine increased body weight,
   feed intake, and daily gain, increased the secretion of thyroid
   hormone, and induced the proliferation of satellite cells ([42]12). In
   chickens, l-carnosine also positively influences weight gain and
   activates the enzymatic antioxidant system in the blood ([43]13,
   [44]14).

   The intestinal microbiota plays a vital role in adaptive coevolution
   with mammals ([45]15). The intestinal tract of sheep is characterized
   by a diverse microbial ecosystem ([46]16), which is influenced by
   multiple factors, such as feeding, drinking, the environment,
   physiology, and disease ([47]17–19). The intestinal microbiota also
   plays a crucial role in biological processes related to regulating
   nutrient absorption and maintaining homeostasis ([48]20). It produces
   various digestive enzymes that convert indigestible plant
   macromolecules into small molecules that are absorbable by the host
   ([49]21). For example, certain microorganisms produce pectinases that
   can degrade pectin in the plant cell wall into small molecules that can
   be utilized by ruminants ([50]22), whereas many species produce lipases
   that hydrolyze long-chain fatty acids ([51]23). Once absorbed by the
   host, these simple metabolites enter the bloodstream, altering serum
   metabolite levels ([52]24). Microbial homeostasis influences the
   efficiency with which the host animal utilizes its feed, ultimately
   affecting productive performance metrics, such as daily weight gain and
   the feed conversion rate.

   Metabolomics plays a crucial role in analyzing metabolic pathways,
   processes, and gene functions ([53]25, [54]26), and is widely used in
   the fields of animal disease diagnosis and food ingredient
   identification ([55]27). Comprehensive analysis of the correlations
   between the intestinal microbiota and serum metabolome not only enables
   identifying the relationship between dietary energy levels and lamb
   quality ([56]28) but has also been used to investigate how they reflect
   age and nutritional requirements in Tibetan sheep ([57]29).
   Furthermore, it has well explained the effects of different diets on
   intestinal microbes and metabolic pathways in Hu sheep ([58]30).

   Our knowledge about the effects of l-carnosine on the intestinal
   microbiota and serum metabolome in fattening sheep is limited, and
   published studies are scarce. We investigated the effects of dietary
   l-carnosine supplementation on the fecal microbiota and metabolite
   composition in fattening lambs using 16S rRNA sequencing and liquid
   chromatography–tandem mass spectrometry (LC–MS/MS)-based metabolomics.
   Additionally, multi-omics analysis was conducted on the fecal
   microbiota and serum metabolites to provide a reference for the
   application of l-carnosine in sheep.

2. Materials and methods

2.1. Experimental animals and experimental design

   The experiment was conducted at the Sheep Experimental Station of the
   Beijing Academy of Agriculture and Forestry Sciences in Yangyuan
   County, Zhangjiakou City, Hebei Province, China. In total, 60 male
   crossbred lambs (Dorper ♂ × Small Tail Han ♀) of 3 months of age with
   an average body weight of 30 ± 5 kg were randomly divided into two
   groups. The lambs were housed in 2 sheltered outdoor paddocks and fed a
   basal diet consisting of a total mixed ration according to the Chinese
   sheep feeding standard (NY/T816-2004). The contents of digestible
   energy, metabolizable energy, crude protein, calcium, and phosphorus in
   the diet were 11.83 MJ·kg-1, 9.73 MJ·kg-1, 14.61, 0.39, and 0.25%,
   respectively ([59]31). Animals in the control group (group C) were fed
   only the basal diet ([60]Table 1). Based on previous studies and the
   dietary supplementation level of l-carnosine used previously in
   fattening pigs ([61]12, [62]32), we determined the optimal
   supplementation level of l-carnosine for fattening lambs to be
   400 mg/kg. In the experimental l-carnosine group (group L), l-carnosine
   (purity ≥98%, Zhengzhou Luyuan Biotechnology Co., Ltd.) was added to
   the basal diet at a concentration of 400 mg/kg. Both groups were
   provided with adequate water and salt blocks during the 60-day trial
   period.

Table 1.

   Composition and nutrient levels of the basic diet of fattening sheep.
   Item                       Content
   Ingredients
   Corn silage                 30.90
   Corn                        44.20
   Soybean meal                17.00
   Wheat bran                  5.00
   Salt                        0.70
   Limestone powder            1.00
   Calcium hydrogen phosphate  0.20
   Premix^1                    1.00
   Total                      100.00
   Nutrientcomponent^2
   Metabolizable energy        9.73
   Digestible energy           11.83
   Crude protein               14.61
   Calcium                     0.39
   Phosphorus                  0.25
   [63]Open in a new tab

   ^1The premix provided the following per kg diets: VA 200 kIU, VD[3] 40
   kIU, VE 1000 mg, Nicotinamide 1,200 mg, Biotin 70 mg, Fe (FeSO4)
   1300 mg, Mn (MnSO4) 1000 mg, Zn (ZnSO4) 1240 mg, Se (Na2SeO3) 8.50 mg,
   Co (CoSO4) 11 mg. ^2Metabolizable energy was a calculated value, while
   the others were measured values.

2.2. Sample collection

   The morning after the feeding experiment, the 60 sheep were weighed.
   Fresh feces were individually collected from the rectum of 12 random
   sheep in each group (n = 24 in total), immediately transferred into
   sterile tubes, and frozen in liquid nitrogen. To prevent contamination,
   the outer layer of each fecal sample was discarded, and the middle
   inner portion was sampled for testing. Blood (5 mL) was collected from
   the jugular veins of the above 24 sheep using vacuum blood collection
   tubes for serum metabolomics analysis. The blood samples were
   maintained at room temperature for 4 h, followed by centrifugation at
   3000 rpm, 4°C for 10 min to collect the serum. The serum was frozen at
   −80°C until metabolomics analysis.

2.3. Microbial DNA extraction and sequencing

   Microbial DNA was extracted from the fecal using an E.Z.N.A.® Soil DNA
   Kit (Omega Bio-tek, Norcross, GA,U.S.). The DNA was examined using 2%
   agarose gel electrophoresis, and the DNA concentration and purity were
   determined with a Thermo Fisher NanoDrop-2000 spectrophotometer (Thermo
   Scientific, U.S). The variable regions V3 and V4 of the bacterial 16S
   rRNA gene were PCR-amplified using primers 338F
   (5′-ACTCCTACGGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGGTWTCTAAT-3′).
   The PCR products were recovered, purified, assayed, and quantified
   using a microfluorometer (QuantiFluor-ST; Promega, USA). The PCR
   products were mixed in equimolar amounts, and a sequencing library was
   constructed using a NEX-TFLEX Rapid DNA-Seq Kit and sequenced on the
   Illumina MiSeq PE 300 platform (Shanghai Majorbio Bio-Pharm Technology
   Co., Ltd.).

2.4. Microbiome composition analysis

   Operational taxonomic units (OTUs) at a 97% similarity level were
   clustered and compared to the 16S rRNA database (Silva
   v138/16S_bacteria) to classify annotations of the OTU sequences,
   setting the classification confidence to 0.7. All data were analyzed on
   the Shanghai Majorbio Cloud platform. The alpha diversity index was
   determined using Mothur. Differences or similarities in the composition
   of the fecal microbial communities were analyzed using principal
   coordinates analysis (PCoA). Abundance differences in intestinal
   microbial composition at various levels between the two groups were
   analyzed using Student’s t-test. The linear discriminant analysis
   effect size (LEfSe) algorithm was used to identify differences among
   various taxonomic groups. Using the acquired community abundance data,
   rigorous statistical approaches were used to perform hypothesis testing
   on species across various microbial communities. This process aims to
   evaluate the significance of species abundance differences and pinpoint
   species that exhibit notable disparities between groups. PICRUSt was
   used to normalize the OTU abundance table to obtain the corresponding
   GreenGene IDs of the OTUs, and Kyoto Encyclopedia of Genes and Genomes
   (KEGG) functional annotations were compared against the Clusters of
   Orthologous Genes database to obtain annotation information of the OTUs
   and abundance information for each function across the samples.

2.5. Metabolite extraction and metabolomics analysis

   For metabolite extraction, methanol was added to 100 μL of serum, after
   which the samples were pulverized using a cryo-mill and sonicated for
   30 min (5°C, 40 kHz). The samples were left to precipitate the proteins
   and then centrifuged. The supernatants were transferred into sample
   vials for LC–MS/MS analysis.

   The samples were separated by ultra-high performance liquid
   chromatography system (ACQUITY UPLCHSS T3, Waters Corp., USA) and
   detected. The raw data included quality control (QC) and detection
   samples. Data pre-processing for appropriate data analysis encompassed
   the filtering of the raw data, recoding of missing values,
   normalization, QC verification, and data conversion and was conducted
   using the Progenesis QI 2.3 software.

   The MS data were matched with the metabolite database HMDB[64]^1 and
   Metlin,[65]^2 and data analysis was performed on the Shanghai Majorbio
   Cloud platform. Projected variable importance (VIP) values were
   calculated using orthogonal least partial squares discriminant analysis
   (OPLS-DA) modeling, and the validity of the OPLS-DA model was evaluated
   using R2Y and Q2.

   Enrichment analysis was performed using Fisher’s exact test. p-values
   were corrected using the Benjamini-HochbergBH method, and the corrected
   p-values were thresholded at 0.05. KEGG pathways meeting this criterion
   were considered significantly enriched in the metabolite set, and the
   significantly enriched pathways were accurately examined using the
   Scipy software v1.0.0 (p < 0.05). The raw sequencing reads generated in
   this study have been deposited in the NCBI Sequence Read Archive (SRA)
   under BioProject accession number PRJNA1175011.[66]^3

2.6. Correlation analysis

   The Spearman correlation coefficients between fecal microbial taxa and
   differential serum metabolites were calculated using the Python
   software. Correlation heatmaps were generated to visualize and analyze
   the associations. Spearman’s correlation analysis is a statistical
   technique used to assess the relationship and the strength of influence
   between an independent variable and a dependent variable by analyzing
   the rank order of two sets of variables. It involves three primary
   steps: first, ranking the data from both sets of variables based on
   their magnitude; second, replacing the original data with these ranks;
   and finally, calculating the correlation between these ranks. This
   method provides insights into the association and impact of the
   independent variable on the dependent variable.

3. Results

3.1. Growth performance

   The effect of l-carnosine on the weight gain of fattening lambs is
   presented in [67]Table 2. Total weight gain and average daily weight
   gain (ADG) were significantly increased, by 13.31 and 13.28%,
   respectively, in group L compared to group C (p < 0.01).

Table 2.

   Effect of l-carnosine on weight gain in fattening lambs.
   Groups Number Initial weight/kg Final weight/kg Total weight gain/kg
   Average daily gain/g
   Group C 30 33.02 ± 2.28 47.45 ± 2.95 14.43 ± 1.79 240.56 ± 29.82
   Group L 30 31.88 ± 2.65 48.25 ± 1.88 16.35 ± 1.23** 272.50 ± 20.55**
   [68]Open in a new tab

   Data are presented as mean ± standard error of mean. **p < 0.01 vs.
   group C. “Group C” indicated the control group, “Group L” represented
   the l-carnosine of 400 mg/kg. The same as below.

3.2. Fecal microbiota richness and diversity

   At the 97% similarity threshold, a total of 1,662 OTUs were found in
   samples from groups C and L ([69]Figure 1). The microbiota of group C
   and group L samples shared 1,260 OTUs, and 312 and 90 OTUs were
   uniquely identified in group C and group L samples, respectively.
   Diversity indices were calculated based on the OTUs of each library. We
   assessed alpha diversity in the two groups using five indices (Shannon,
   Simpson, ACE, Chao, and coverage) ([70]Table 3). No significant
   differences between the two groups in these indicators were found
   (p > 0.05). Beta diversity was evaluated using PCoA. A PCoA plot based
   on the Bray–Curtis algorithm ([71]Figure 2) showed that groups C and
   group L differed in terms of beta diversity (p < 0.05). Notably, the
   group C samples exhibited a dispersed distribution in the PCoA plot,
   indicating substantial variation in the microbial community structures
   within the group. Conversely, the group L samples clustered more
   compactly, suggesting a higher degree of similarity in the intestinal
   microbial community structures among sheep supplemented with
   l-carnosine.

Figure 1.

   Figure 1
   [72]Open in a new tab

   Venn diagram showing the OTUs in the fecal microbiota of fattening
   sheep. “C” indicated the control group, “L” represented the l-carnosine
   of 400 mg/kg. The same as below.

Table 3.

   Effect of l-carnosine on five alpha diversity indices related to the
   fecal microbiota of fattening sheep.
   Groups Shannon Simpson Ace Chao Coverage
   Group C 4.60 ± 0.55 0.035 ± 0.031 765.5 ± 161.3 786.2 ± 165.5
   0.9965 ± 0.0006
   Group L 4.78 ± 0.45 0.024 ± 0.018 751.6 ± 129.1 766.2 ± 134.0
   0.9966 ± 0.0006
   [73]Open in a new tab

Figure 2.

   [74]Figure 2
   [75]Open in a new tab

   PCoA plot of microbial beta-diversity (based on the Bray–Curtis
   algorithm).

3.3. Fecal microbiota composition

   To investigate the differences in the fecal microbiota composition
   between groups C and L, we used the Wilcoxon rank-sum test to compare
   the mean relative abundances of dominant bacteria at the phylum and
   genus levels. The dominant phyla in the two groups were Firmicutes and
   Bacteroidota. The abundances of Actinobacteriota and Proteobacteria
   were decreased, whereas those of Bacteroidota and Spirochaetota were
   increased in group L compared to group C ([76]Figure 3A). The top three
   dominant genera in the two groups were UCG-005,
   norank_f_Muribaculaceae, and Rikenellaceae_RC9_gut_group ([77]Figure
   3B). Further analyses revealed that, at the phylum level ([78]Figure
   4A), the abundance of Patescibacteria was significantly lower in group
   L than in group C (p < 0.01). At the genus level ([79]Figure 4B), the
   abundances of Syntrophococcus (p < 0.01) and Butyricimonas (p < 0.001)
   were higher in group L than in group C. In contrast, the abundances of
   Escherichia-Shigella and Candidatus Saccharimonas were significantly
   lower in group L than in group C (p < 0.05).

Figure 3.

   [80]Figure 3
   [81]Open in a new tab

   Effect of l-carnosine on fecal microbiota composition of fattening
   lambs. (A) Bacterial abundance at the phylum level. (B) Bacterial
   abundance at the genus level.

Figure 4.

   [82]Figure 4
   [83]Open in a new tab

   Differences in the major bacterial (A) phyla and (B) genera in lamb of
   control and l-carnosine group based on Wilcoxon rank-sum tests.
   *p < 0.05, **p < 0.01, ***p < 0.001.

3.4. Metabolomics analysis

   Using non-targeted metabolomics technology, serum samples from groups C
   and L were analyzed to characterize the blood metabolites in fattening
   lambs with or without l-carnosine supplementation. The differences
   between the groups were analyzed using OPLS-DA. As shown in the OPLS-DA
   score plot ([84]Supplementary Figure S1A), the samples of the two
   groups were clearly distinguished. The values of R2Y (0.995) and Q2
   (0.657) were > 0.5 ([85]Supplementary Figure S1B), indicating that the
   OPLS-DA model had a good fit and good predictive ability, and that VIP
   values could be calculated based on the data to screen for differential
   marker metabolites.

   Using VIP > 1 and p < 0.05 as the optimal thresholds, 68 differential
   metabolites were identified ([86]Figure 5A). The clustering heatmap of
   the differential metabolites shows the differential metabolite
   expression profiles and VIP values for the metabolites with the top 30
   VIP values ([87]Figure 5B; [88]Supplementary Table S1). Pyridine
   N-oxide glucuronide was downregulated (p < 0.01), whereas l-histidinol,
   d-apiose, and isodomedin were upregulated in group L (p < 0.001)
   compared to group C.

Figure 5.

   [89]Figure 5
   [90]Open in a new tab

   Effect of l-carnosine on the serum metabolome in fattening lambs. (A)
   Volcano plots showing the distribution of differential metabolites
   identified based on p < 0.05 and VIP > 1. (B) Profiling, VIP score, and
   p-values for the top 30 differential serum metabolites in groups L and
   C. *p < 0.05, **p < 0.01, ***p < 0.001. (C) KEGG metabolic pathway
   enrichment analysis of the differential serum metabolites in
   l-carnosine and control groups. *p < 0.05, **p < 0.01 vs. group C.

   Differential metabolites were significantly enriched in eight KEGG
   pathways (p < 0.05): choline metabolism in cancer, ascorbate and
   alternate metabolism, pyrimidine metabolism, tryptophan metabolism,
   histidine metabolism, protein digestion and absorption, lysine
   degradation, and glycerophospholipid metabolism ([91]Figure 5C).

3.5. Correlations between fecal microbial and serum metabolites

   The correlations between 20 genera and 40 metabolites were analyzed
   using Spearman correlation analysis ([92]Figure 6). Holdemania and
   Butyricimonas were significantly positively correlated with
   l-histidinol, d-apiose, and l-erythrulose (p < 0.001). A highly
   significant negative correlation existed between Butyricimonas and
   pyridine N-oxide glucuronide (p < 0.001). Pygmaiobacter was positively
   correlated with phenylacetylglutamine (p < 0.05). A significant
   positive correlation was observed between Butyricimonas and stachydrine
   (p < 0.05).

Figure 6.

   [93]Figure 6
   [94]Open in a new tab

   Correlation analysis of fecal microbiota and serum metabolites in
   fattening lambs. Red indicates a positive correlation, blue indicates a
   negative correlation. *p < 0.05, **p < 0.01, ***p < 0.001 indicate
   statistically significant correlation between fecal microbiota and
   serum metabolites.

4. Discussion

   The dipeptide l-carnosine has been used in pig and chicken production
   to improve productive performance and antioxidant capacity and to
   maintain livestock health ([95]33–35). However, reports on its
   application in sheep are scarce. Because of the unique digestive
   mechanism and dietary characteristics of ruminants, their intestinal
   microbiota is crucial for maintaining intestinal health and nutrient
   absorption. Intestinal microbial communities indirectly but profoundly
   influence the animal feed conversion efficiency and production
   performance by regulating the production of endogenous metabolites and
   various metabolic pathways ([96]36).

   The present study investigated the effects of dietary l-carnosine
   supplementation on the growth performance of fattening lambs. The
   dietary supplementation induced an increase in the total weight gain
   and ADG in the fattening lambs. Similar positive effects have been
   observed in other animal species. l-Carnosine supplementation in pigs
   increased the final weight, average daily feed intake, and ADG
   ([97]12), and in chickens, it effectively increased body weight and
   breast muscle development ([98]14). However, the mechanism by which
   l-carnosine is able to improve growth performance in fattening sheep
   remained unclear. Therefore, we analyzed the effects of l-carnosine
   supplementation on intestinal microbiota composition and serum
   metabolite profiles to gain insights into the mechanisms underlying its
   growth-promoting effects in fattening sheep.

   The results revealed that the addition of l-carnosine did not affect
   the diversity and dominant species in the intestinal microbiota of
   fattening lambs. At the phylum level, the intestinal microbiota of
   fattening lambs was enriched in Firmicutes and Bacteroidetes both in
   the C and L groups, which is consistent with the prior findings in
   herbivores ([99]37, [100]38). Firmicutes and Bacteroidetes are
   primarily responsible for carbohydrate, protein, and fiber metabolism
   ([101]18, [102]39). At the genus level, l-carnosine supplementation
   significantly increased the relative abundances of Syntrophococcus and
   Butyricimonas. Syntrophococcus, a member of Firmicutes, can digest
   various carbohydrates and produce short-chain fatty acids (SCFAs)
   ([103]40). In a previous study, an increase in solid feed intake was
   accompanied by an elevation in the relative abundance of
   Syntrophococcus, thereby enhancing the carbohydrate digestive capacity
   of early-weaned lambs ([104]41). Syntrophococcus is involved in the
   utilization of non-fibrous carbohydrates and the production of acetic
   acid. Butyricimonas is a butyrate producer ([105]42). Acetic acid and
   butyrate are SCFAs. In the gastrointestinal tract, SCFAs can enhance
   intestinal barrier integrity, regulate glucose and lipid metabolism and
   the immune system, modulate inflammatory responses, suppress pathogenic
   bacterial growth, and manage blood pressure ([106]43, [107]44).
   l-carnosine supplementation increased the abundance of Syntrophococcus
   and Butyricimonas, which possibly improved the utilization efficiency
   of non-fibrous carbohydrates and SCFA levels. The abundances of
   Escherichia-Shigella and Candidatus Saccharimonas were significantly
   reduced in the L group versus the C group. Escherichia-Shigella, common
   intestinal pathogens, can cause intestinal diseases (e.g., enteritis,
   diarrhea, and dysentery) or extraintestinal conditions (e.g., urinary
   tract infections, meningitis, or sepsis) through attachment to
   epithelial cells and/or invasion of target host cells ([108]45).
   Candidatus Saccharimonas, an opportunistic pathogen in the intestinal
   tract, is associated with gastrointestinal disorders and causes
   inflammatory diseases of the intestinal mucosa ([109]46, [110]47). A
   previous study revealed a negative correlation between Candidatus
   Saccharimonas and production performance in geese ([111]48). Our
   findings support that dietary l-carnosine supplementation in sheep
   increases the relative abundance of beneficial bacteria in the
   intestine, while decreasing that of pathogenic bacteria.

   The serum concentrations of the metabolites l-histidine, d-apiose, and
   isodomedin were highly significantly upregulated in group L. d-Apiose
   is a branched pentose in the cell walls of higher plants ([112]49) that
   has an antioxidant effect ([113]50). The differential metabolites were
   significantly enriched in the histidine metabolic pathway, in which
   l-histidine was upregulated in group L. l-Histidine, as a precursor of
   histidine synthesis ([114]51), increases the synthesis of ammonia,
   alanine, and glutamine in muscle and affects the anabolism of proteins
   ([115]52). Isodomedin belongs to the class of diterpenes ([116]53),
   which exhibit anti-inflammatory, antioxidant, and antimicrobial
   properties ([117]54). Pyridine N-oxide glucuronide, a glucuronic
   acid-derivative, was highly significantly downregulated in group L. It
   has been shown that glucuronic acid is closely related to inflammation
   by acting on Toll-like receptor 4 and inducing pain in rats ([118]55).
   We speculate that the addition of l-carnosine increased the antioxidant
   capacity in the fattening lambs to a certain extent. In summary,
   l-carnosine supplementation may have increased the antioxidant capacity
   and enhanced protein synthesis in the fattening lambs.

   Comprehensive analysis of the microbiomes and non-target metabolomes
   unveiled the relationships between differential microbiota genera and
   differential metabolites. Notably, our results indicated a positive
   correlation between Butyricimonas and l-histidine and d-apiose. SCFAs,
   produced through microbial fermentation in the intestine, exhibit
   diverse physiological functions ([119]56). Butyricimonas is a putative
   SCFA producer with potent anti-inflammatory and immunomodulatory
   effects ([120]57). Amino acids serve as precursors for bacterial SCFA
   synthesis, demonstrating an interaction between microbial activity and
   the homeostasis of host amino acids and SCFAs ([121]58). Stachydrine
   exerts potent anti-inflammatory action via the NF-κB signaling pathway
   ([122]59) and prevents oxidative stress by increasing the activity of
   antioxidant enzymes such as superoxide dismutase ([123]60). These
   findings suggest that Butyricimonas may enhance the nutrient conversion
   capacity and production performance by alleviating inflammatory
   responses and influencing metabolic processes associated with amino
   acids and carbohydrates. Phenylacetylglutamine is a metabolic byproduct
   of intestinal bacteria ([124]41) and serves as a substitute for urea in
   the urea cycle to facilitate the excretion of nitrogenous waste from
   the body ([125]61). Pygmaiobacter is the main butyric acid producer,
   and the correlation analysis showed that it was significantly
   positively correlated with phenylacetylglutamine, which may induce
   changes in intestinal microbes. We found a negative correlation between
   Butyricimonas and pyridine N-oxide glucuronide. Pyridine N-oxide
   glucuronide promotes inflammation. These findings corroborate that
   l-carnosine has anti-inflammatory properties. Comprehensive analysis of
   the microbiome and non-target metabolomes further showed that
   l-carnosine promoted weight gain in fattening sheep by exerting
   anti-inflammatory and increasing antioxidant property.

5. Conclusion

   Dietary l-carnosine supplementation in fattening lambs was found to
   improve growth performance by positively influencing the intestinal
   microbiota and serum metabolites. Enhanced oxidative capacity, protein
   synthesis ability, and anti-inflammatory activity may be among the main
   mechanisms of l-carnosine in increasing weight gain during the
   fattening period. Therefore, l-carnosine shows promise for application
   in the sheep industry.

Acknowledgments