Monolaurin in the Diet of Feedlot Finishing Cattle: Effects on Performance, Metabolism, Ruminal Environment, and Meat Fatty Acid Profile

Abstract

This study evaluated the effects of monolaurin intake per finishing feedlot cattle on growth performance, metabolic status, ruminal environment, and meat fatty acid profile. Twenty-four castrated Holstein males (379 ± 8.5 kg; 12 months old) were randomly assigned to two treatments: basal diet (control) or basal diet with α-monolaurin (treated: 0.762 g/kg dry matter intake; ≈6.63 g/animal/day) for 79 days. Feed intake, body weight, and feed efficiency were recorded, and blood and ruminal samples were collected during the trial. Ruminal fermentation parameters, protozoa counts, hematological and biochemical variables, oxidative status biomarkers, ruminal microbiota composition (16S rRNA sequencing), and Longissimus dorsi fatty acid profile were analyzed. Monolaurin feed did not affect dry matter intake or final body weight, but increased total weight gain, average daily gain, and feed efficiency (p ≤ 0.05), indicating improved nutrient utilization. Hematological and serum biochemical variables were largely unchanged, although total leukocyte counts were lower in treated cattle. Animals receiving monolaurin showed reduced reactive oxygen species and lower superoxide dismutase activity, suggesting improved oxidative balance without changes in lipid peroxidation. During the adaptation phase (day 14), treated cattle exhibited lower acetate, propionate, valerate, and total volatile fatty acid concentrations and higher protozoa counts, but these differences disappeared by day 79, indicating ruminal adaptation. Microbiota diversity was not altered overall, although specific genera differed in relative abundance between treatments. In meat, monolaurin increased lauric, linoleic, and arachidonic acids, reduced palmitic and heptadecanoic acids, decreased total saturated fatty acids, and increased polyunsaturated fatty acids (p ≤ 0.05). Overall, dietary monolaurin improved feed efficiency, modulated oxidative status, induced transient ruminal microbial adjustments, and enhanced the nutritional quality of beef lipids without compromising metabolic health.

1. Introduction

The intensification of beef cattle production systems has increased the need for nutritional strategies capable of improving productive efficiency without compromising animal health or food safety [1,2]. Growth-promoting antibiotics have traditionally been widely used to modulate the gastrointestinal microbiota, improve feed efficiency, and optimize animal performance in intensive production systems [3]. However, concerns regarding antimicrobial resistance and the potential dissemination of antimicrobial resistance genes through the food chain have led to increasing restrictions on their use in livestock production worldwide [4,5]. This scenario has driven the search for safe and effective alternative feed additives aligned with the principles of sustainable livestock production.

Among the proposed alternatives, lipid-derived compounds with antimicrobial activity have received increasing attention, particularly monolaurin (glycerol monolaurate), a monoglyceride of lauric acid naturally present in coconut oil and human milk [6]. Monolaurin exhibits broad-spectrum antimicrobial activity, acting primarily through disruption of the lipid membrane of Gram-positive bacteria and enveloped microorganisms [6,7]. In monogastric species, its addition to the diet has been associated with modulation of the intestinal microbiota, reduction in enteric pathogens, and improvements in productive performance [8]. In ruminants, however, its effects remain poorly understood, particularly due to the complexity of the ruminal ecosystem, which is characterized by intense interactions among bacteria, protozoa, and fungi that ultimately determine fermentative efficiency and host energy metabolism [9,10]. In addition to its direct antimicrobial action, the inclusion of lipid compounds in the diet may influence ruminal fermentation, volatile fatty acid production, and fatty acid biohydrogenation, thereby affecting the lipid profile of meat [11,12]. Microbiota alterations may also impact systemic parameters, including inflammatory responses and oxidative status, which are directly related to productive performance and final product quality [13]. Therefore, an integrated evaluation of productive performance, hematological parameters, oxidative metabolism, ruminal fermentation, microbiota composition, and fatty acid profile is essential to better understand the physiological and productive effects of novel feed additives in beef cattle.

Medium-chain fatty acids (MCFA) and their monoglycerides have attracted considerable interest as modulators of ruminal microbial ecosystems due to their antimicrobial properties and potential effects on fermentation efficiency [14]. In the rumen, microbial populations are responsible for the degradation of dietary carbohydrates and the production of volatile fatty acids, which represent the primary source of energy for the host animal. The antimicrobial activity of monolaurin is mainly directed against microorganisms possessing lipid-rich cell membranes and several Gram-positive bacterial groups [15]. Consequently, intake of monolaurin may alter microbial community structure, fermentation pathways, and hydrogen metabolism within the rumen. In a rumen simulation study using cattle inoculum, monolaurin intake substantially reduced methanogenic archaea populations and modified the abundance of selected bacterial groups, suggesting that this compound may influence both microbial ecology and fermentative processes [16]. Similarly, dietary glycerol monolaurate in the diet of weaned lambs altered ruminal microbial composition and was associated with improvements in animal performance, supporting its potential role as a rumen-modulating feed additive [17]. Nevertheless, the mechanisms underlying these responses remain incompletely understood under practical feedlot conditions.

In addition to its effects on microbial populations, monolaurin may influence lipid metabolism in ruminants through alterations in ruminal lipolysis and biohydrogenation [11,12]. Dietary lipids entering the rumen are rapidly hydrolyzed by microbial lipases, releasing free fatty acids that subsequently undergo extensive biohydrogenation by specialized ruminal microorganisms. and this process determines the profile of fatty acid intermediates reaching the small intestine and, consequently, influences the fatty acid composition of meat and milk produced by ruminants [11,12,18]. Several bacterial species involved in biohydrogenation, including Gram-positive populations, are susceptible to antimicrobial lipids and medium-chain fatty acids, suggesting that monolaurin may alter the extent and pathways of ruminal biohydrogenation [14,16]. Such modifications may affect the formation and tissue deposition of vaccenic acid, conjugated linoleic acid (CLA), and other fatty acids of nutritional relevance for human consumption [11,12,19]. Furthermore, alterations in ruminal microbial activity may modify volatile fatty acid production, fermentation efficiency, and the supply of metabolic substrates available to the host animal, thereby influencing nutrient utilization and productive performance [9,10]. Because microbial populations also play a central role in ruminal lipolysis and biohydrogenation, shifts in microbial ecology may ultimately affect the fatty acid composition and nutritional quality of beef [12,18].

Despite their potential benefits, antimicrobial lipids may also exert undesirable effects on ruminal fermentation. Medium-chain fatty acids are known to possess broad antimicrobial activity and may inhibit not only pathogenic or undesirable microorganisms but also beneficial ruminal populations involved in fiber degradation [16,20]. In vitro studies have demonstrated that lauric acid and its derivatives can suppress cellulolytic and hydrogen-producing microorganisms, including Fibrobacter succinogenes, one of the major fibrolytic bacterial species in the rumen [16,20]. Consequently, excessive inhibition of fibrolytic populations may reduce fiber digestibility and alter fermentation characteristics, particularly when medium-chain fatty acids are supplied at elevated concentrations [14,21]. A meta-analysis evaluating dietary medium-chain fatty acids in ruminants reported reductions in methane production but also identified negative effects on fiber digestibility, highlighting the trade-off between antimicrobial activity and ruminal function [14]. Furthermore, the magnitude of these responses appears to depend on several factors, including diet composition, fatty acid source, supplementation level, and interactions with the existing ruminal microbial community [14,20]. Therefore, comprehensive in vivo studies are required to determine whether the antimicrobial effects of monolaurin can beneficially modulate ruminal ecology without impairing fermentation efficiency, nutrient utilization, or animal performance under practical feedlot conditions.

We hypothesized that dietary monolaurin intake would modulate ruminal microbial populations and lipid metabolism, resulting in improved fermentation efficiency, oxidative status, and productive performance, while excessive antimicrobial activity could potentially affect fibrolytic microorganisms and ruminal function. Despite the biological potential of monolaurin, there is still a knowledge gap regarding its in vivo effects in feedlot cattle during the finishing phase, particularly concerning the combined responses in productive performance, metabolic health, oxidative balance, ruminal ecology, and meat lipid quality. Therefore, the present study aimed to evaluate the effects of dietary monolaurin addition in finishing beef cattle on productive performance, metabolism, ruminal environment, meat fatty acid profile and oxidative status.

2. Materials and Methods

2.1. Additive

The feed additive used in this study was monolaurin, present in the commercial product (Laurimax^®, Feedis, Indaiatub, Brazil), a powder formulation stored in plastic packaging. According to the manufacturer, the product contains α-monolaurin as the active compound, a monoglyceride derived from lauric acid classified as a medium-chain fatty acid derivative with antimicrobial properties. The commercial product has a purity of 37% and was added to the concentrate during its production, at a rate of 2.85 g/kg. Thus, the real dose of α-monolaurin was 1.05 g/kg of concentrate. This information regarding the addition of monolaurin to the concentrate, combined with total feed intake (silage + concentrate), allowed us to determine the dose of monolaurin based on dry matter intake, as shown in Section 2.3. The dosage of the additive used here was determined through a pilot study.

2.2. Animals and Housing

Twenty-four castrated Holstein males (379 ± 8.5 kg and 12 months old) were used in this study. Animals were housed in individual pens, allowing precise monitoring of feed intake. Fresh water was available ad libitum, and feed was offered twice daily, in the early morning and early afternoon. Pens, feeders, and drinkers were cleaned periodically to maintain adequate hygiene and animal welfare conditions throughout the experimental period.

2.3. Experimental Design and Diet

The experimental period lasted 79 days (14 days of adaptation period and 65 days of experimental period). Animals were randomly assigned to one of two experimental groups in a completely randomized design: a control group receiving a basal diet composed of corn silage and concentrate, and a treatment group receiving the same basal diet with α-monolaurin at a dose of 0.762 g/kg of dry matter intake—DMI (equivalent to 6.63 g α-monolaurin/animal/day).

The cattle diet was formulated using the BRCorte 2016 program [22], projecting a daily weight gain of 1.5 kg. The following feedstuffs were used in the total mixed ration (TMR) with 64.58% concentrate and 35.42% roughage (

Table 1. Ingredients and chemical composition in the total mixed ration (TMR) used in this study.

Ingredients	TMR, % of Dry Matter
Corn silage	35.42
Cornmeal	30.16
Soybean meal	2.85
Wheat bran	9.48
Soybean hulls	12.45
Dried distillers grains with solubles	7.78
Common salt	0.21
Limestone	0.64
Cattle premix 1	0.32
Livestock urea	0.68
Chemistry composition
Dry matter	57.3
Crude protein	14.1
Starch	34.5
Ether extract	3.30
Neutral Detergent Fiber—NDF	36.4
Total digestible nutrients—TDN	70.8

Note ¹: Cattle Premix: Magnesium 20%, Sulfur 10%, Cobalt 0.003%, Copper 5.6%, Iodine 0.31%, Manganese 0.002%, Selenium 0.16%, Zinc 0.0023%, Vit A 2,500,000 IU/kg, Vit D 750,000 IU/kg, Vit E 12,500 IU/kg.

). The animals were fed twice a day (8:00 AM and 4:00 PM) in individual feeders, where the mixture was prepared manually by the handler.

2.4. Data and Sample Collection

Feed intake was monitored daily by weighing feed refusals each morning prior to the first feeding. Data and biological samples were collected at four time points during the experimental period (days 1, 14, 45, and 79). Body weight was measured after a fasting period using a digital scale in a squeeze chute (Toledo^®, model MGR-3000, São Bernardo do Campo, Brazil). From these data, average daily gain (ADG) and feed efficiency were calculated, with feed efficiency expressed as ADG divided by dry matter intake (DMI).

Blood samples were collected from the coccygeal vein into tubes containing ethylenediaminetetraacetic acid (EDTA) for hematological analyses and into clot-activator tubes for serum separation and subsequent biochemical analyses. Ruminal fluid samples were collected on days 14 and 79 using an esophageal probe coupled to a suction system. The collected material was divided into two aliquots: one for protozoa counting and another for volatile fatty acid profiling. The aliquot used to measure volatile fatty acids was filtered and then frozen (−80 °C). On day 79, an additional aliquot of ruminal fluid was stored using sterile swabs for subsequent microbiota analysis.

On day 80, animals were slaughtered in a commercial abattoir operating under official state inspection regulations (Brazilian Federal Inspection, Brasília, Brazil). Slaughter procedures were monitored by the research team. Hot carcass weight was recorded, and a sample of the Longissimus dorsi muscle was collected between the first and third lumbar vertebrae. Muscle samples were wrapped in plastic film and stored under refrigeration at 4 °C for 24 h, after which they were frozen at −27 °C until further analyses.

2.5. Laboratory Analysis

2.5.1. Feed Chemical Analysis

Samples of corn silage and concentrate were collected throughout the experimental period, composited by period, dried in a forced-air oven at 55 °C for 72 h (Marconi^®, model MA035, Piracicaba, Brazil), and ground to pass through a 1 mm screen (Thomas Scientific^®, Model 4 Wiley Mill, Swedesboro, NJ, USA). Dry matter (DM; method 934.01) and crude protein (CP; method 984.13) were determined according to AOAC [23] procedures. Neutral detergent fiber (NDF) was analyzed using the method of Van Soest et al. [24] with heat-stable amylase and expressed exclusive of residual ash. Ether extract (EE) was determined using petroleum ether extraction (AOAC method 920.39). Starch concentration was determined using an enzymatic method (AOAC Official Method 996.11; AOAC, 2019) [23] as described by Hall [25]. Results of TMR in Table 1.

2.5.2. Hematological Analysis

Hematological variables including red blood cell count, hemoglobin concentration, hematocrit, total leukocytes, and differential leukocyte counts were determined using an automated veterinary hematology analyzer (3-part EQUIP VET 3000^®, Barueri, Brazil). When necessary, blood smears were prepared, stained with Wright–Giemsa, and examined under optical microscopy (Nikon^®, Eclipse Ci-L, Tokyo, Japan) to confirm leukocyte differentiation following standard veterinary clinical pathology procedures.

2.5.3. Serum Biochemical and Oxidative Status

Blood samples collected in clot-activator tubes were centrifuged at 3000× g for 10 min to obtain serum (Fanem^®, Excelsa Baby I 206-R, São Paulo, Brazil), which was stored at −20 °C until analysis. Serum biochemical variables (e.g., glucose, total protein, albumin, cholesterol, triglycerides, urea, AST, and GGT) were determined using commercial colorimetric kits (manufacturer Analisa^®, Shah Alam, Malaysia) in an automated biochemical analyzer, following the manufacturer’s instructions.

Oxidative status was evaluated by measuring reactive oxygen species (ROS) production, lipid peroxidation, and antioxidant enzyme activity. Intracellular ROS levels were determined using a fluorometric assay based on the oxidation of 2′,7′-dichlorodihydrofluorescein diacetate (DCFH-DA), following the procedure described by LeBel et al. [26], with fluorescence measured at excitation and emission wavelengths of approximately 488 and 525 nm, respectively.

Lipid peroxidation in serum was evaluated by quantifying thiobarbituric acid reactive substances (TBARS), expressed as malondialdehyde equivalents, following the spectrophotometric method described by Buege and Aust [27] and subsequently adapted for biological fluids. This assay is based on the reaction of malondialdehyde with thiobarbituric acid under acidic and high-temperature conditions, forming a chromogen measured spectrophotometrically.

Superoxide dismutase (SOD) activity was determined using a spectrophotometric method based on the enzyme’s ability to inhibit the auto-oxidation of adrenaline (epinephrine), following the procedure described by Misra and Fridovich [28]. Enzymatic activity was expressed relative to protein concentration in the samples. All measurements were performed in duplicate to ensure analytical precision.

2.5.4. Ruminal Protozoa Counts and Volatile Fatty Acids (With References)

Ruminal fluid samples were filtered through four layers of cheesecloth immediately after collection. For protozoa enumeration, aliquots were fixed in a 10% (v/v) formaldehyde solution and counted using a Sedgewick–Rafter chamber under optical microscopy, following standard rumen microbiology procedures as described by Dehority [29] and Williams and Coleman [30].

For volatile fatty acid (VFA) analysis, ruminal fluid aliquots were acidified with metaphosphoric acid (25% w/v), centrifuged at 10,000× g for 15 min, and the supernatant stored at −20 °C until analysis. Concentrations of acetate, propionate, butyrate, and minor VFAs were determined by gas chromatography equipped with a flame ionization detector and a capillary column suitable for short-chain fatty acid separation, according to procedures described by Erwin et al. [31] and later adaptations commonly used in rumen fermentation studies [32]. A standardization of volatile fatty acid measurements in rumen fluid is presented in Table S1. The analytical methodology used in this study was described in detail by Brunetto et al. [33].

2.5.5. Fatty Acid Profile in Meat

Samples of the Longissimus dorsi muscle were thawed under refrigeration, trimmed of visible fat and connective tissue, and homogenized. Total lipids were extracted using the Folch et al. [34] chloroform–methanol method. Fatty acid methyl esters (FAMEs) were prepared by base-catalyzed transesterification according to Lago et al. [35]. FAMEs were analyzed by gas chromatography (GC-FID, Varian Chrompack CP-3800, Walnut Creek, CA, USA) equipped with a fused silica capillary column (e.g., 100 m × 0.25 mm × 0.20 µm). Individual fatty acids were identified by comparison of retention times with commercial standards (Supelco 37-component mix).

2.5.6. Ruminal Microbiota

On day 79, ruminal fluid samples were collected from 50% of the animals (n = 12; six control and six treated) and stored using 3M™ Quick Swabs for qualitative and quantitative microbial assessment through 16S rRNA gene amplicon sequencing. Total DNA was extracted from approximately 200 mg of wet sample using the ZR Fungal/Bacterial DNA MiniPrep kit (Zymo Research, Irvine, CA, USA), following the manufacturer’s instructions. The primers 515F (5′-CCTAYGGGRBGCASCAG-3′) and 806R (5′-GGACTACNNGGGTATCTAAT-3′) were used to amplify the V4 region of the bacterial 16S rRNA gene by polymerase chain reaction.

Sequencing libraries were quantified by quantitative PCR using the KAPA Library Quantification Kit (Illumina, San Diego, CA, USA) according to the manufacturer’s protocol. Libraries were then normalized to a final concentration of 2 nM, pooled, and sequenced on an Illumina MiSeq platform using a paired-end 150-cycle sequencing approach. Sequencing data were analyzed with the Mothur software (v1.48.3; Schloss et al. [36]), applying the procedures described in the MiSeq Standard Operating Protocol [37], with minor adjustments for dataset quality and read length. Taxonomic identification of representative oligotypes was achieved by alignment against the SILVA reference database (release 138.2 [38]). Operational taxonomic units (OTUs) were generated using a closed-reference clustering approach, and the resulting OTU tables were imported into the R environment (v4.5.2; R Core Team, R Foundation for Statistical Computing, Vienna, Austria) for downstream ecological and statistical analyses. Community structure was explored using the Phyloseq (v1.52; McMurdie & Holmes [39] and Microeco (v1.15.0; Liu et al. [40]) packages. The relative abundance of bacterial taxa was summarized and visualized for the 20 most dominant genera across all samples. To detect taxa with significant differences among experimental groups, Linear Discriminant Analysis Effect Size (LEfSe) was applied (Segata et al. [41]), applying an LDA score threshold of 1. To complement taxonomic profiling, the functional metabolic potential of ruminal bacterial communities was predicted using Tax4Fun2 [42], implemented in the R environment. OTU tables generated against the SILVA reference database (release 138.2) were normalized by 16S rRNA copy number prior to functional inference. Predicted gene families were assigned to KEGG Orthologs (KOs) and subsequently collapsed into KEGG functional pathways (levels 2 and 3) to facilitate biological interpretation. Differentially abundant predicted functions between treatments were identified using LEfSe.

Alpha diversity was computed using Shannon’s diversity index, while beta diversity was assessed through PCoA plots using Bray–Curtis dissimilarity to compare community composition between samples. All plots and visualizations were created using ggplot2 (v3.2.1 [43]).

2.6. Statistical Analysis

Data were initially subjected to descriptive analysis, followed by assessment of normality using the Shapiro–Wilk test and inspection of residual variance. As all variables showed normal distribution, statistical analyses were performed using the MIXED procedure of SAS (SAS Institute Inc., Cary, NC, USA; version 9.4). Variables related to weight gain, average daily gain, feed efficiency, and carcass efficiency were analyzed considering treatment as a fixed effect and animal nested within treatment as a random effect. Blood and ruminal fluid variables, as well as body weight and dry matter intake, were analyzed as repeated measures over time, including the fixed effects of treatment, day, and the treatment × day interaction, with animal within treatment included as a random effect. When available, day 1 values were included as an independent covariate in the model; however, these observations were excluded from the dataset used to compute treatment means. The covariance structure for repeated measures was modeled as first-order autoregressive, selected based on the lowest Akaike information criterion. Least squares means (LSMEANS) were compared using the PDIFF option (Student’s t-test), and results are presented as LSMEANS followed by the standard error of the mean (SEM). Statistical significance was declared at p ≤ 0.05.

3. Results

3.1. Growth Performance

Body weight, weight gain, feed intake, and feed efficiency are presented in

Table 2. Performance markers of Holstein males fed with the monolaurin additive.

Variables	Control	Monolaurin	SEM 2	P-Treat 1
Initial body weight, kg	388	387	8.64	0.96
Final body weight, kg	495	500	7.62	0.51
Weight gain, kg	107 b	113 a	1.33	0.05
ADG 2, kg	1.64 b	1.73 a	0.02	0.05
DMI, kg DM 2	8.97	8.71	0.12	0.29
Feed efficiency, kg/kg	0.182 b	0.198 a	0.009	0.03

¹ Treatment effect when p ≤ 0.05, illustrated by different letters on the same line. ² SEM, standard error of the mean; DM, dry matter; ADG, average daily gain; DMI, daily dry matter intake.

and Table S2. No treatment effect or treatment × day interaction was observed for body weight or feed intake (p > 0.05). However, greater total weight gain and average daily gain were observed in cattle fed with monolaurin compared with the control group (p = 0.05). Feed efficiency was better in cattle that consumed monolaurin (p = 0.032).

3.2. Hematological and Serum Biochemical Variables

Hematological and serum biochemical results are shown in

Table 3. Hematological and biochemical variables in Holstein males fed monolaurin.

Variables	Control	Monolaurin	SEM 3	P-Treat 1	P-Treat × Day 2
Hemogram
Leukocyte (×103 µL)				0.05	0.05
d14	9.72 a	7.75 b	0.43
d45	7.59	6.97	0.42
d79	10.1 a	8.73 b	0.51
Mean 1	9.16 a	7.82 b	0.47
Lymphocyte (×103 µL)	4.91	4.32	0.31	0.46	0.54
Granulocyte (×103 µL)	3.07	2.54	0.23	0.12	0.33
Monocyte (×103 µL)	1.17	0.96	0.07	0.42	0.30
Erythrocytes (×106 µL)	6.94	7.48	0.24	0.78	0.87
Hemoglobin (mg/dL)	10.1	10.3	0.20	0.91	0.94
Hematocrit (%)	28.9	30.9	0.90	0.66	0.71
Platelets (×103 µL)	286	346	38.3	0.41	0.29
Serum biochemistry
Albumin (g/dL)	2.80	2.81	0.04	0.96	0.97
Globulin (g/dL)	3.70	3.81	0.14	0.91	0.86
Total protein (g/dL)	6.50	6.62	0.13	0.92	0.88
Cholesterol (mg/dL)	84.1	79.3	3.19	0.65	0.54
Fructosamine (mg/dL	237	237	5.71	0.92	0.96
Glucose (mg/dL)	91.0	87.5	2.89	0.83	0.87
Urea (mg/dL)	17.6	18.5	1.00	0.77	0.68

¹ Treatment effect when p ≤ 0.05, illustrated by different letters on the same line. ² Treatment × day interaction when p ≤ 0.05, in this case, with a difference only for total leukocyte count. ³ SEM, standard error of the mean; d, day.

. Total leukocyte count was lower in cattle receiving monolaurin, with the most evident treatment × day interaction occurring on day 14 (end of the adaptation period). No differences between groups were observed for lymphocyte, granulocyte, monocyte, erythrocyte, or platelet counts, nor for hematocrit or hemoglobin concentration (P > 0.05). Likewise, serum concentrations of albumin, globulins, total protein, cholesterol, fructosamine, glucose, and urea were not affected by treatment (P > 0.05).

3.3. Oxidative Status

Biomarkers of oxidative status are presented in

Table 4. Lipid peroxidation (TBARS) and reactive oxygen species (ROS) in serum, and superoxide dismutase (SOD) in the blood of Holstein males fed monolaurin.

Variables	Control	Monolaurin	SEM 3	P-Treat 1	P-Treat × Day 2
TBARS (nmol/mL)	10.2	9.87	0.97	0.92	0.87
ROS (Flu)				0.021	0.001
d14	118 a	102 b	3.47
d45	111 a	95.3 b	3.28
d79	108 a	92.4 b	3.35
Mean 1	112 a	96.5 b	3.36
SOD (U/mg of protein)				0.05	0.034
d14	1.74 a	1.52 b	0.05
d45	1.63	1.53	0.05
d79	1.56	1.48	0.04
Mean 1	1.64 a	1.51 b	0.04

¹ Treatment effect when p ≤ 0.05, illustrated by different letters on the same line. ² Treatment × day interaction when p ≤ 0.05, illustrated by different letters on the same line for each day. ³ SEM, standard error of the mean; d, day.

. No differences between groups were detected for TBARS levels (p > 0.05). In contrast, treatment effects and treatment × day interactions were observed for ROS concentrations and SOD activity. Lower serum ROS levels were found in cattle fed with monolaurin on days 14, 45, and 79 compared with the control group. SOD activity was also lower in animals receiving monolaurin, with the most pronounced difference observed on day 14 (p = 0.034).

3.4. Ruminal Fluid: Protozoa, Microbiota, and Volatile Fatty Acids

A treatment × day interaction was observed for acetate, propionate, and isovalerate concentrations, which were lower in ruminal fluid from monolaurin-fed cattle on day 14 (

Table 5. Short-chain fatty acid (SCFA) profile and number of protozoa in ruminal fluid of Holstein males fed monolaurin.

Variables	Control	Monolaurin	SEM 3	P-Treat 1	P-Treat × Day 2
Acetic acid (mmol/L)				0.76	0.01
d14	48.3 a	41.2 b	1.87
d79	37.8	39.3	1.65
Propionic acid (mmol/L)				0.65	0.05
d14	12.1 a	10.4 b	0.44
d79	8.75	9.05	0.47
Isobutyric acid (mmol/L)				0.95	0.92
d14	1.19	1.16	0.02
d79	0.94	0.93	0.02
Butyric acid (mmol/L)				0.43	0.21
d14	7.73	7.31	0.25
d79	6.37	6.12	0.24
Isovaleric acid (mmol/L)				0.39	0.27
d14	1.85	1.68	0.06
d79	1.29	1.25	0.04
Valeric acid (mmol/L)				0.55	0.05
d14	0.85 a	0.67 b	0.03
d79	0.57	0.56	0.03
Total SCFA (mmol/L)				0.68	0.01
d14	72.2 a	62.5 b	2.43
d79	55.7	57.2	2.39
Protozoa number (×108/L)				0.51	0.04
d14	10.5 b	13.9 a	0.85
d79	12.4	12.9	0.82

¹ Treatment effect when p ≤ 0.05, illustrated by different letters on the same line. ² Treatment × day interaction when p ≤ 0.05, illustrated by different letters on the same line for each day. ³ SEM, standard error of the mean; d, day.

). Consequently, total VFA concentration was also lower at this time point (p < 0.05). Protozoa counts were higher on day 14 in cattle receiving monolaurin (Table 5). On day 79, no statistical differences were observed between groups for any VFA concentration or protozoa counts (Table 5).

Regarding ruminal microbiota composition, the 20 most abundant genera are shown in Figure 1A. The genera Comamonas, Pseudomonas, and Denitrificimonas were among the most abundant and were detected at similar proportions in both groups. In contrast, the genus Alcaligenes was detected at a 44% lower relative abundance in cattle fed with monolaurin compared with controls.

Individual relative abundance profiles (Figure 1B) revealed substantial inter-animal variability, suggesting a strong individual effect independent of treatment, such as the marked proliferation of Aeromonas in animal 12 from the treatment group. This pattern was supported by beta-diversity analysis (Figure 2A) and alpha-diversity analysis (Figure 2B), which showed no significant differences between groups (p > 0.05).

LEfSe analysis identified taxa differentially associated with treatment (Figure 3). The genera Staphylococcus and Turicibacter were less abundant in the rumen of monolaurin-fed cattle, whereas Anaerovorax, Marvinbryantia, and Proteiniclasticum were more abundant in the treated group.

Predicted metabolic functions inferred by Tax4Fun are presented in Figure 4. LEfSe analysis identified six KEGG Ortholog groups differentially enriched between treatments. Cattle fed monolaurin showed enrichment of predicted functions related to Cysteine and methionine metabolism; systemic Renin-angiotensin system (RAS) modulation and steroid degradation. Conversely, the control group showed higher predicted abundance of functions associated with Fatty acid degradation, Melanogenesis and Apoptosis. Despite these differences in specific pathways, no global shift in overall functional diversity was observed, indicating selective modulation of metabolic potential rather than broad functional restructuring of the ruminal microbiome.

3.5. Fatty Acid Profile in Meat

Total lipid content and fatty acid composition of meat are presented in

Table 6. Fatty acid profile in beef from Holstein males fed monolaurin.

Variables (%)	Control	Monolaurin	SEM 3	P-Treat 1
Total lipids	2.28	2.37	0.050	0.591
C4:0 (Butyric)	0.16	0.15	0.002	0.989
C11:0 (Undecanoic)	0.01	0.01	0.001	0.997
C12:0 (Lauric)	0.00b	0.30a	0.002	0.018
C13:0 (Tridecanoic)	0.04	0.04	0.002	0.996
C14:0 (Myristic)	0.22	0.27	0.006	0.242
C14:1 (Myristoleic)	0.09	0.09	0.003	0.991
C15:0 (Pentadecanoic)	0.12	0.12	0.000	0.995
C16:0 (Palmitic)	25.50a	23.14b	0.134	0.003
C16:1 (Palmitoleic)	2.29	1.99	0.830	0.568
C17:0 (Heptadecanoic)	3.23a	2.11b	0.040	0.013
C18:0 (Stearic)	20.70	20.41	0.103	0.965
C18:1n9t (Elaidic)	1.61	1.60	0.001	0.987
C18:1n9c (Oleic)	35.23	36.08	0.301	0.432
C18:2n6c (Linoleic)	8.62b	10.50a	0.117	0.050
C20:0 (Arachidic)	0.12	0.13	0.005	0.986
C18:3n6 (?-Linolenic)	0.04	0.05	0.003	0.993
C20:1n9 (cis-11-Eicosenoic)	0.08	0.09	0.004	0.980
C18:3n3 (a-Linolenic)	0.17	0.17	0.001	0.995
C21:0 (Henicosanoic)	0.24	0.24	0.002	0.989
C20:2 (cis-11,14-Eicosadienoic)	0.12	0.13	0.002	0.982
C22:0 (Behenic)	0.02	0.03	0.001	0.947
C20:3n6 (cis-8,11,14-Eicosatrienoic)	0.48	0.52	0.013	0.798
C20:4n6 (Arachidonic)	0.73b	1.93a	0.014	0.011
C22:2 (cis-13,16-Docosadienoic)	0.02	0.02	0.000	0.993
C24:0 (Lignoceric)	0.06	0.06	0.001	0.987
C20:5n3 (cis-5,8,11,14,17-Eicosapentaenoic)	0.05	0.06	0.003	0.971
C24:1n9 (Nervonic)	0.03	0.04	0.001	0.990
C22:6n3 (cis-4,7,10,13,16,19-Docosahexaenoic)	0.02	0.02	0.003	0.985
∑ SFA 2	50.41a	47.01b	0.365	0.026
∑ MUFA 2	39.34	39.89	0.414	0.954
∑ PUFA 2	10.25b	13.40a	0.287	0.001

Note ¹: when p < 0.05, a significant difference was observed between the groups, with different letters (a, b) on the same line used for illustration. Note ²: ∑ SFA, sum of saturated fatty acids; ∑ MUFA, sum of monounsaturated fatty acids; ∑ PUFA, sum of polyunsaturated fatty acids. Note ³: SEM, standard error of the mean.

. Cattle fed with monolaurin showed higher proportions of lauric, linoleic, and arachidonic acids compared with the control group (p ≤ 0.05). Conversely, palmitic and heptadecanoic acid proportions were lower in meat from monolaurin-fed cattle. Overall, the sum of saturated fatty acids decreased, whereas the proportion of polyunsaturated fatty acids increased in meat from animals receiving monolaurin.

4. Discussion

Intake of monolaurin improved productive performance in finishing cattle, as indicated by the greater total weight gain, higher average daily gain, and improved feed efficiency, despite no differences in dry matter intake. This pattern suggests that monolaurin enhanced nutrient utilization efficiency rather than feed consumption, likely through modulation of ruminal microbial activity and fermentation processes. Antimicrobial lipids such as monoglycerides are known to selectively inhibit susceptible Gram-positive bacteria, potentially altering substrate competition and microbial energy losses, thereby improving the efficiency of nutrient conversion into animal growth [6,44,45,46]. The transient reduction in acetate, propionate, and total volatile fatty acids observed during the adaptation phase (day 14) may reflect a short-term microbial adjustment to the additive. Similar transient responses have been described following the inclusion of medium-chain fatty acids and other antimicrobial lipids in ruminant diets, although the magnitude and duration of these effects appear to depend on dose, diet composition, and the adaptive capacity of the ruminal microbiota [14,20,47].

The lower concentrations of acetate, propionate, and valerate at d14 suggest that the dietary inclusion of monolaurin temporarily affected ruminal fermentation during the initial phase of the experiment. However, the absence of differences between treatments at d79 indicates that these effects were transient and that the ruminal microbial ecosystem may have adapted over time to the presence of monolaurin in the diet. An analysis of the ruminal microbiota at the end of the adaptation period could have provided valuable insights into the mechanisms underlying the reduction in volatile fatty acid concentrations observed at d14. Medium-chain fatty acids and their derivatives exhibit antimicrobial activity against several ruminal microbial groups and may alter the abundance of fibrolytic microorganisms involved in plant cell wall degradation [16,20]. Because fibrolytic bacteria play a central role in fiber digestion and contribute to the production of volatile fatty acids, changes in their abundance may directly affect ruminal fermentation patterns and energy availability to the host animal [9,48]. Furthermore, we acknowledge as a limitation of this study the absence of intermediate evaluations of ruminal microbiota composition and fatty acid metabolism during the feeding period. Measurements obtained at a midpoint of the experiment (e.g., d45) could have provided additional information regarding the temporal dynamics of microbial adaptation and lipid metabolism, thereby improving our understanding of the mechanisms associated with the dietary inclusion of monolaurin in finishing cattle.

The transient increase in ruminal protozoa observed during the initial phase of the experiment may partially explain the concomitant reduction in total volatile fatty acid (VFA) concentrations. Protozoa play a central role in ruminal microbial ecology by engulfing and digesting bacterial cells, thereby influencing bacterial turnover and fermentation dynamics [30,49]. In addition, many ciliate protozoa are capable of engulfing starch granules and soluble carbohydrates, temporarily reducing substrate availability to free-living amylolytic bacteria and potentially altering fermentation patterns [30,50]. Consequently, increases in protozoal abundance may contribute to reduced bacterial fermentation activity and lower VFA production during periods of microbial restructuring, such as those occurring after dietary changes or the inclusion of antimicrobial compounds [49,51]. The absence of differences in VFA concentrations at the end of the experimental period suggests that these effects were transient and that the ruminal microbial ecosystem may have adapted over time, restoring fermentative activity. Furthermore, elevated protozoal populations have frequently been associated with increased bacterial predation, reduced microbial protein flow to the small intestine, and greater methane production, which may represent undesirable consequences from the perspective of ruminal efficiency [49,50,51]. Therefore, the temporary increase in protozoal abundance observed during the adaptation period likely reflects a short-term shift in microbial interactions rather than a persistent impairment of ruminal fermentation.

These microbial and fermentative adjustments may also help explain the changes observed in the fatty acid composition of meat. Animals receiving monolaurin showed reduced proportions of saturated fatty acids and increased polyunsaturated fatty acids, including linoleic and arachidonic acids. Dietary lipids and antimicrobial fatty acid derivatives can influence ruminal lipolysis and biohydrogenation pathways, potentially reducing the extent of microbial hydrogenation of unsaturated fatty acids and allowing greater absorption of PUFA in the intestine and subsequent deposition in tissues [11,12]. Such shifts in lipid metabolism are consistent with improved feed efficiency, as altered microbial biohydrogenation and energy partitioning may enhance metabolic use of dietary nutrients. Therefore, the combined evidence from growth performance, transient fermentation changes, and tissue fatty acid profile supports the hypothesis that monolaurin acts primarily through selective modulation of ruminal microbial metabolism and lipid transformation, improving nutrient-use efficiency without affecting feed intake or overall rumen stability.

The changes observed in the fatty acid composition of meat from monolaurin-fed cattle may be considered nutritionally favorable from a consumer health perspective. The reduction in total saturated fatty acids, particularly palmitic acid, together with the increase in polyunsaturated fatty acids such as linoleic and arachidonic acids, suggests an improvement in the lipid quality of the beef [52,53]. High intake of saturated fatty acids has been associated with increased cardiovascular risk, whereas greater consumption of polyunsaturated fatty acids is linked to beneficial effects on lipid metabolism, inflammatory regulation, and overall cardiovascular health [52]. In ruminant products, increases in PUFA content are often limited by extensive ruminal biohydrogenation; therefore, dietary strategies capable of partially limiting this process and enhancing tissue deposition of unsaturated fatty acids are considered desirable [11,12]. The present results indicate that monolaurin intake may have influenced ruminal lipid metabolism in a way that allowed greater escape and incorporation of unsaturated fatty acids into muscle tissue. From a production standpoint, such improvements add value to the final product by aligning beef composition with current consumer demand for healthier animal-derived foods, suggesting that monolaurin could contribute not only to productive efficiency but also to the nutritional quality and market appeal of beef.

The detection of lauric acid in the meat of cattle fed with monolaurin is consistent with the direct dietary supply of this fatty acid, since monolaurin is a monoglyceride derived from lauric acid (C12:0). Medium-chain fatty acids such as lauric acid differ metabolically from long-chain saturated fatty acids, as they are more rapidly absorbed, preferentially oxidized for energy, and less prone to deposition in adipose tissues [54]. In ruminants, most dietary unsaturated fatty acids undergo extensive microbial transformation in the rumen; however, medium-chain fatty acids and their derivatives may partially escape complete microbial modification or be incorporated into tissues following digestion and absorption, explaining their presence in muscle when supplied in the diet [11,12]. From a consumer health perspective, lauric acid has been reported to exhibit antimicrobial activity and may increase HDL cholesterol concentrations, although it can also raise total cholesterol levels, indicating that its nutritional impact differs from that of longer-chain saturated fatty acids such as palmitic acid [55]. Considering the relatively low proportion detected in the present study and the simultaneous reduction in total saturated fatty acids alongside increased PUFA content, the presence of lauric acid in meat from monolaurin-fed cattle is unlikely to represent a negative nutritional attribute and may instead reflect the metabolic fate of the additive, without compromising overall lipid quality.

The inclusion of monolaurin in the diet of finishing cattle appeared to exert a selective rather than global effect on ruminal microbial ecology, as indicated by the absence of differences in alpha and beta diversity, despite shifts in specific bacterial taxa identified by LEfSe analysis. This pattern suggests that monolaurin modulates microbial structure through targeted antimicrobial activity without disrupting overall community stability, a response commonly observed when antimicrobial lipids act primarily on susceptible Gram-positive populations while preserving ecological redundancy within the rumen microbiome [56,57].

The reduced relative abundance of Staphylococcus in monolaurin-fed cattle is biologically consistent with the well-documented susceptibility of Gram-positive bacteria to monoglycerides. Monolaurin disrupts cytoplasmic membrane integrity, interferes with signal transduction, and can inhibit toxin production in several Gram-positive genera [6,58]. Although Staphylococcus is not typically considered a dominant functional ruminal genus, its presence may reflect transient environmental or oral contaminants or opportunistic taxa associated with inflammatory or dysbiotic conditions in livestock [59]. Therefore, its reduction may indicate a health-supportive antimicrobial selectivity rather than a nutritionally relevant fermentative shift. Similarly, the decrease in Turicibacter abundance may also be meaningful. Members of this genus have been linked to host immune modulation and intestinal inflammatory responses in mammals, and their abundance has been shown to vary with dietary antimicrobial compounds and lipid supplementation [56,60]. Although their specific metabolic role in the rumen remains unclear, reductions in Turicibacter have been reported in association with improved gut health status and reduced inflammatory signaling, supporting the hypothesis that monolaurin may indirectly influence host–microbiota immune interactions.

Conversely, the higher abundance of Anaerovorax, Proteiniclasticum, and Marvinbryantia in treated animals suggests a possible shift toward specialized anaerobic fermentative pathways. Both Anaerovorax and Proteiniclasticum are strictly anaerobic bacteria involved in amino-acid fermentation and protein degradation, generating short-chain fatty acids such as acetate and butyrate as end products [61,62]. Their enrichment may reflect an altered substrate competition or microbial niche availability following suppression of susceptible Gram-positive taxa. In the rumen, proteolytic and amino-acid-fermenting bacteria play an important role in nitrogen turnover and microbial protein synthesis efficiency, potentially influencing host nutrient utilization [63]. The increase in Marvinbryantia may also be relevant from a fiber-degradation perspective. Species within this genus belong to the family Lachnospiraceae and have been associated with polysaccharide and plant-fiber fermentation in herbivore gastrointestinal systems [64]. Changes in their abundance could indicate subtle alterations in carbohydrate fermentation dynamics or cross-feeding interactions among fibrolytic consortia, although the absence of differences in total VFA concentration at day 79 suggests that such microbial shifts did not translate into long-term changes in global fermentative output.

The functional prediction enrichment of cysteine and methionine metabolism in monolaurin-fed cattle suggests potential alterations in microbial sulfur amino acid turnover and redox balance. Sulfur-containing amino acids play critical roles in microbial protein synthesis and antioxidant defense via glutathione biosynthesis [65]. Although the RAS is classically described as a host endocrine regulator of blood pressure and fluid balance, components of RAS-related pathways identified in KEGG annotations often reflect bacterial peptidase systems and bioactive peptide metabolism. Monolaurin’s selective effects on Gram-positive bacteria may alter microbial proteolytic activity, potentially explaining the predicted enrichment of RAS-associated functions. The enrichment of steroid degradation pathways suggests an altered microbial capacity for metabolizing steroid-like compounds, including bile acid derivatives and plant secondary metabolites. In ruminants, microbial transformation of steroidal compounds can influence lipid digestion, hormone metabolism, and microbial membrane dynamics [66].

The transient reduction in acetate, propionate, and total SCFA concentration observed on day 14, together with the higher protozoal counts in the monolaurin group, may reflect an adaptation phase of the ruminal ecosystem to the antimicrobial lipid. Dietary lipids and antimicrobial fatty acid derivatives can temporarily suppress bacterial fermentation activity while protozoa proliferate due to reduced bacterial competition or predation dynamics [44,45]. Over time, microbial adaptation and community resilience typically restore fermentation patterns, which is consistent with the lack of differences in SCFA profiles at day 79. Importantly, the large inter-animal variability observed in individual microbial profiles reinforces the concept that host-specific factors strongly shape ruminal microbiota composition, often exceeding dietary effects when sample size is limited. Such individuality has been consistently reported in rumen microbiome studies and reflects host genetics, early colonization history, and stochastic ecological processes [67,68].

Dietary monolaurin selectively modulated the predicted metabolic potential of the ruminal microbiota without promoting a broad functional restructuring, a pattern commonly reported when feed additives exert targeted antimicrobial effects while preserving functional redundancy within the rumen ecosystem [57,68]. The enrichment of pathways related to cysteine and methionine metabolism in monolaurin-fed cattle suggests a shift toward microbial processes linked to sulfur amino acid turnover and antioxidant-related metabolism, since sulfur-containing amino acids are central to microbial protein synthesis and glutathione-dependent redox regulation [65,69]. This functional pattern may be consistent with the lower systemic ROS concentrations observed in treated animals. The higher prediction of steroid degradation pathways may reflect altered microbial utilization of lipid-derived or steroid-like compounds, as ruminal microorganisms are known to metabolize sterols, bile derivatives, and plant secondary metabolites, influencing lipid digestion and host metabolic signaling [11,66]. In addition, the predicted modulation of the renin–angiotensin system, although inferred from microbial gene annotation and not directly measured at the host level, may indicate shifts in microbial peptidase activity and bioactive peptide metabolism, which are increasingly recognized as potential mediators of host–microbiome physiological interactions [13,65]. Conversely, the greater abundance of pathways linked to fatty acid degradation, apoptosis, and melanogenesis in the control group may reflect relatively higher microbial turnover and lipid catabolism in the absence of monolaurin, consistent with the known capacity of ruminal microbiota to extensively transform dietary lipids and regulate microbial cell dynamics [44,45]. Taken together, these findings indicate that monolaurin acts primarily as a selective modulator of microbial metabolic functions rather than a driver of large-scale microbiome functional shifts, supporting the concept that improvements in animal performance and oxidative status may be mediated by targeted microbial metabolic adjustments.

Taken together, these findings indicate that monolaurin intake promotes targeted antimicrobial modulation of the ruminal microbiota, reducing potentially undesirable Gram-positive taxa while favoring strictly anaerobic fermentative bacteria, without compromising overall microbial diversity or long-term fermentation stability. This selective ecological modulation may partly explain the improved feed efficiency and weight gain observed in treated cattle, suggesting enhanced microbial functional efficiency rather than large-scale compositional restructuring of the rumen microbiome.

The lower leukocyte count observed in fed animals with the additive may indicate a mild anti-inflammatory effect rather than a negative physiological response. In cattle, leukocyte numbers within the normal range but slightly reduced are often interpreted as reflecting decreased basal inflammatory stimulation and improved immune homeostasis [70,71]. Feed additives capable of modulating rumen microbiota or reducing microbial antigen load can indirectly attenuate systemic immune activation, leading to subtle reductions in circulating leukocytes [72]. Moreover, lipid-derived compounds such as monolaurin and related medium-chain fatty acids have documented antimicrobial and anti-inflammatory properties that may contribute to lower immune stimulation without impairing host defense [73,74]. Therefore, the leukocyte reduction observed here is consistent with a modest immunomodulatory effect of the additive.

The absence of significant differences in serum biochemical metabolites indicates that supplementation did not adversely affect hepatic function, protein metabolism, or overall metabolic status. Stable concentrations of key biochemical markers suggest that animals maintained normal physiological homeostasis throughout the experimental period, supporting the metabolic safety of the additive. According to the literature, the functional dietary supplements in cattle can alter ruminal fermentation and improve performance without detectable alterations in systemic biochemical indicators, reinforcing that such additives can modulate digestion and performance without compromising metabolic health [75].

The oxidative status results indicate that monolaurin intake did not promote systemic oxidative stress and may have contributed to maintaining redox balance in the animals. Stable or improved antioxidant markers together with unchanged lipid peroxidation indices suggest that the additive did not impair cellular oxidative stability and may have supported antioxidant defenses. In ruminants, dietary lipid-derived compounds and microbiota-modulating additives can influence oxidative metabolism by reducing inflammatory stimuli and improving metabolic efficiency [76], which in turn helps limit reactive oxygen species production. Similar responses have been reported in cattle where nutritional interventions enhanced antioxidant capacity or maintained oxidative markers within physiological ranges, indicating preserved cellular integrity and metabolic health [76,77]. Overall, the present findings support that additive intake was compatible with normal oxidative metabolism and may provide subtle protective effects against oxidative imbalance.

The present findings align with previous studies evaluating glycerol monolaurate or monolaurin in ruminants, which consistently indicate that this compound can modulate ruminal microbial populations and fermentation dynamics [16,78]. Rumen simulation studies have shown that monolaurin suppresses methanogenic archaea and reduces archaeal abundance, demonstrating selective antimicrobial activity within the rumen ecosystem [16]. Rusitec experiments further confirmed that monolaurin intake can decrease methane production and protozoal counts while modifying fermentation patterns, although effects on fibre degradation appear dose-dependent [21,79]. In vivo evidence in dairy cows indicates that glycerol monolaurate may alter milk fatty-acid synthesis and composition without impairing productive performance, supporting its metabolic and ruminal influence [80]. Studies in small ruminants also report improved growth performance and feed efficiency in lambs receiving dietary glycerol monolaurate, accompanied by shifts in rumen microbial structure [17]. Collectively, these findings support the concept that monolaurin acts primarily through targeted modulation of ruminal microbiota and microbial metabolism, which may explain the productive and compositional responses observed in the present study.

5. Conclusions

Monolaurin intake (6.63 g/animal/day) per finishing feedlot cattle improved growth performance and feed efficiency without affecting feed intake or systemic metabolic indicators. The lower amount of volatile fatty acids at the end of the adaptation period indicates that monolaurin temporarily interferes with ruminal fermentation; this does not occur at the end of the study. The additive contributed to improved oxidative balance and was associated with changes in the relative abundance of specific ruminal bacterial taxa, while overall microbial diversity and community structure remained unchanged. In addition, monolaurin enhanced meat lipid quality by reducing saturated fatty acids and increasing polyunsaturated fatty acids. Overall, these findings indicate that monolaurin may represent a promising nutritional strategy to improve productive performance and beef nutritional value in finishing cattle. Although changes in specific microbial taxa and predicted metabolic pathways were observed, the absence of differences in overall microbial diversity suggests that further studies are required to clarify the microbial mechanisms underlying the responses observed.