Research note: Exploring the effects of glycerol monolaurate on lipid metabolism in young broilers based on molecular dynamics simulation and 16S rRNA analysis

Abstract

This study aimed to investigate the effects of glycerol monolaurate (GML) on lipid metabolism in young broilers, with focus on the AMPKα1 protein and the cecal microbiota. A total of 144 one-day-old male Arbor Acres broilers were randomly assigned to two groups, with each group consisting of six replicates of twelve birds. The groups were fed diets supplemented with either 0 or 1,200 mg/kg of GML for a period of 14 d. The results showed that GML increased high-density lipoprotein cholesterol levels in the serum (P < 0.05) while reducing total cholesterol, triglyceride, low-density lipoprotein cholesterol, and aspartate aminotransferase levels (P < 0.05). GML also decreased liver lipid droplets and increased the mRNA levels of AMPKα1, CPT1, ApoB, and LXR (P < 0.05). Molecular docking results indicated that GML exhibited good binding affinity with AMPKα1. Root-mean-square deviation values for AMPKα1 and the AMPKα1/GML complex remained stable at 1 to 2 Å within the first 50 ns. The residues in the AMPKα1/GML complex exhibited root-mean-square fluctuation values of less than 2 Å, and the binding energy of the complex was -133.515 kJ/mol. Moreover, GML significantly increased the expression levels of GPR119 and AMPKα1 in the jejunum (P < 0.05). Notably, the genera CHKC1001, Coprobacter, and Ruminococcaceae_UCG_005 were significantly enriched in the GML group (P < 0.05). PICRUSt2 function prediction revealed that GML-induced alterations in the cecal microbiota primarily involved fatty acid degradation (P < 0.05). In conclusion, dietary supplementation with 1200 mg/kg GML enhanced lipid metabolism in young broilers.

Introduction

Glycerol monolaurate (GML), a derivative of lauric acid, has gained recognition in poultry nutrition primarily for its antimicrobial properties and its established safety in broilers at dosages up to 5 g/kg (Amer et al., 2020). Beyond its role as a feed additive, evidence from mice indicates that GML can regulate systemic lipid metabolism by modulating synthesis and degradation pathways (Zhao et al., 2022). Efficient lipid metabolism during the early post-hatch period is critical for broiler development, health, and economic productivity. However, the effects and underlying mechanisms of GML on lipid metabolism in broilers remain unclear. To address this gap, this study provides novel insights by investigating the integrative effects of GML in young broilers, connecting its potential impact on cecal microbiota with host metabolic responses in the liver and intestine. Consequently, we hypothesized that GML could improve lipid metabolism in broilers. To test this hypothesis, this study aimed to: 1) evaluate the effects of dietary GML on serum lipid profiles and hepatic lipid metabolism; 2) explore its impact on the cecal microbiota; and 3) investigate its potential role in modulating the jejunal expression of genes related to metabolic sensing and regulation in young broilers.

Materials and methods

Ethical statement

Animal experiment protocols were reviewed and approved by the Ethics Committee of Shandong Agricultural University (approval No. SDAUA-2022-50).

Birds, experimental design, and management

A total of 144 one-day-old male Arbor Acres broilers were randomly divided into two groups: a control group (CON) fed a basal diet and an experimental group (GML) given a basal diet supplemented with 1,200 mg/kg GML. Each group consisted of 72 birds, with six replicates of 12 birds each. All birds were housed in an environmentally controlled room at 60-70 % humidity with a 23 h light/1 h dark cycle. Temperature started at 33 °C for the first week and gradually reduced to 28 °C by the end of the second week. The 90 % pure GML was provided by Zhengtong Food Technology Co., Ltd. (Henan, China). Based on the accumulated data from our previous research, a GML dosage of 1,200 mg/kg of diet was used, as it has been shown to effectively improve intestinal health in broilers (Kong et al., 2022).

Sample collection

At the end of the experiment, one bird was randomly selected for sampling from each replicate. Blood was drawn from the wing veins, centrifuged at 3,000 g for 10 min at 4 °C to separate the serum, which was then stored at -20 °C for further analysis. The birds were euthanized by cervical dislocation after blood collection. About 1 cm segments of the liver and mid-jejunum were removed and fixed in 4 % paraformaldehyde. The remaining liver, jejunum, and cecum tissues were snap-frozen in liquid nitrogen and stored at -80 °C until analysis.

Serum biochemical assays

Serum total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and aspartate aminotransferase (AST) levels were analyzed using an automated biochemistry analyzer (Hitachi 7170, Hitachi, Tokyo, Japan).

Liver tissue slice morphology

The liver tissues were embedded as frozen sections and subsequently cut into 5 µm thick slices using a microtome (Leica CM1950, Wetzlar, Germany). The sections were fixed in 4 % paraformaldehyde for 10 min, followed by a wash with distilled water. After an additional wash with 60 % isopropanol, the sections were stained with Oil Red O for 30 min, rinsed with distilled water, and then briefly stained with hematoxylin. The sections were washed again with distilled water and preserved in glycerin. Images of the stained sections were captured at 100 × magnification using a DM IL microscope (Leica, Wetzlar, Germany). For hematoxylin and eosin (H&E) staining, liver tissues were fixed in a 4 % paraformaldehyde solution for 24 h, dehydrated, embedded in paraffin, sectioned to 4 µm, and stained with H&E. The stained sections were examined using a Nikon Eclipse 80i microscope (Nikon, Tokyo, Japan) and images were taken at 100 × magnification.

Lipid metabolism-related genes expression

Total RNA was extracted using TRIzol reagent (Invitrogen, Waltham, MA, USA). One microgram of total RNA was reverse transcribed using a reverse transcription kit (AG11728, Accurate Biotechnology (Hunan) Co., Ltd., Changsha, China). qRT-PCR was performed in triplicate with appropriate primers and SYBR Green Premix Ex Taq (AG11718, Accurate Biotechnology) on a QuantStudio-5 Real-Time PCR System (Thermo Fisher Scientific, Waltham, MA, USA). Target genes were normalized to that of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), and relative expression was calculated using the 2^-ΔΔCt method.

Molecular docking

The structure of the chicken AMPKα1 protein was obtained from the AlphaFold Protein Structure Database. The small molecule GML was obtained from the PubChem database. Water molecules were removed from the AMPKα1 protein using PyMOL 3.1.0. The molecular docking of GML with the AMPKα1 protein was performed using AutoDock Vina 1.1.2 with default settings. The results of the docking experiment were subsequently analyzed and visualized with PyMOL 3.1.0.

Molecular dynamics simulation

Molecular dynamics (MD) simulations were conducted using GROMACS 2020.6 to assess the stability of the optimal complex formed between GML and the AMPKα1 protein. The AMPKα1 protein was described using the CHARMM36 force field, whereas the GML ligand was represented by the GAFF force field. The protein-ligand complex was positioned within a dodecahedral simulation box and solvated with TIP3P water. Following energy minimization, the system underwent a two-step equilibration process utilizing NVT and NPT ensembles. The MD simulations were performed over a duration of 50 ns under constant pressure and periodic boundary conditions. Root-mean-square deviation (RMSD) and root-mean-square fluctuation (RMSF) values were calculated and visualized using QtGrace software. The binding free energy of the protein-ligand complex was determined using the molecular mechanics Poisson-Boltzmann surface area method, with an analysis focused on the final 10 ns of the simulation trajectories.

16S rRNA sequencing and analysis

Microbial DNA was extracted using the HiPure Stool DNA Kit (Magen, China), following the manufacturer’s instructions. The V3-V4 region of the 16S rRNA gene were amplified using primers 338F and 806R. PCR products were quality-checked using a 2 % agarose gel, purified with AMPure XP Beads (Beckman, USA), and quantified with Qubit 3.0. Libraries were prepared using the Illumina DNA Prep Kit (Illumina, USA) and sequenced on the NovaSeq 6000 platform. Raw sequencing data have been deposited in the NCBI SRA database (Accession PRJNA1172368). These raw files were converted to FASTQ format and analyzed with QIIME2, where paired sequences were quality-filtered, trimmed, merged, and denoised using DADA2 (version 3.11) to create a feature table. Taxonomic classification was performed using the QIIME2 feature classifier plugin trained on the Silva 16S rRNA database, with further filtering to remove contaminating mitochondrial sequences. Beta diversity was visualized using Principal Coordinates Analysis (PCoA) plots of weighted UniFrac distances, and differences among groups were assessed with Analysis of Similarities (ANOSIM). Linear discriminant analysis of effect sizes (LEfSe) identified significantly different bacterial taxa, while functional prediction analysis of the gut microbiota was conducted with PICRUSt2 based on KEGG level III pathways.

Statistical analysis

All data were analyzed and visualized using GraphPad Prism 8.0.2 software (GraphPad, CA, USA). Statistical significance was assessed using a two-tailed unpaired Student's t-test, with results presented as means accompanied by standard errors of the mean (SEM). P < 0.05 were considered statistically significant.

Results and discussion

Growth performance, serum lipid concentration, and hepatic lipid accumulation

No significant differences were observed in average daily feed intake, average daily gain, or feed conversion ratio between the dietary treatment groups during the experimental period (P > 0.05, data not shown). Fig. 1 presents the effects of GML on serum lipid concentrations and liver lipid accumulation. Dietary GML significantly increased serum HDL-C levels (P < 0.05) and reduced serum TC, TG, and LDL-C levels (P < 0.05) (Fig. 1A). Oil red staining revealed a significant reduction in lipid droplets in the GML group compared to the control group (Fig. 1B). GML did not significantly affect liver toxicity, as determined by serum AST levels (Fig. 1A) and HE staining results (Fig. 1C). These results are consistent with the work of Xu et al. (2024), who reported that GML decreased serum TC levels and increased HDL-C levels in common carp fed high-lipid diets. The liver is the main site of de novo lipogenesis and the primary location of fat accumulation in broilers. Lipid metabolism is modulated by balancing the activity between lipid synthesis and degradation, both of which are influenced by exogenous factors such as diet and environment. In this study, dietary GML increased the expression of AMPKα1, CPT1, ApoB, and LXR in the liver (P < 0.05). Moreover, GML suppressed HMG-CoA reductase (HMGCR) expression (P < 0.05), the rate-limiting enzyme in cholesterol biosynthesis (Fig. 1D). Consistent with the current results, Liu et al. (2024) reported that GML augmented the expression of triglyceride and fatty acid decomposition-related genes and lowered the levels of plasma triglycerides. Collectively, these results suggest that GML inhibits serum lipid concentration and hepatic lipid accumulation in broilers.

Fig. 1.

Effects of GML on serum lipid concentration and hepatic lipid accumulation in young broilers (n = 6). (A) Serum AST, TC, TG, HDLC, and LDLC levels. (B) Oil Red O staining of liver sections. (C) H&E staining of liver sections. (D) mRNA expression of lipid metabolism related genes in the liver. (E) Molecular docking of GML and AMPKα1 protein. (F) RMSD and RMSF (G) Binding energy. Values are means, with standard errors represented by error bars. *P < 0.05, **P < 0.01, and ***P < 0.001, two-tailed unpaired Student’s t-test.

AMPK is a key regulator of hepatic lipid metabolism. It promotes lipid catabolism and inhibits lipid synthesis by regulating the activity of CPT1, LXR, and HMGCR (Pokhrel et al., 2021). As expected, GML administration significantly increased the expression level of AMPKα1 in the liver. The molecular docking model predicted a stable interaction between GML and AMPKα1, characterized by a favorable estimated binding free energy of -22.983 kJ/mol and stabilized by key interactions, including two hydrogen bonds with the HIS-85 and LEU-288 residues (Fig. 1E), indicating a potentially high-affinity binding. MD simulation results showed that the RMSD values of AMPKα1 and AMPKα1/GML were stable at 1-2 Å in 0-50 ns (Fig. 1F). Most of the residues in the AMPKα1/GML complex had RMSF less than 2 Å (Fig. 1F). The binding energy of the complex, calculated by the MM/PBSA method, was -133.515 kJ/mol (Fig. 1G). These results indicated that the AMPKα1 protein has a high affinity for GML. The specific binding between the AMPKα1 protein and GML remained highly stable throughout the MD run. Based on these results, GML may reduce hepatic lipid accumulation in broilers by regulating the expression of genes involved in lipid metabolism, potentially through AMPKα1 activation.

Jejunal gene expression and cecal microbiota

As shown in Fig. 2A, GML significantly increased the expression of the GPR119 and AMPKα1 genes compared to the CON group (P < 0.05). GPR119 is primarily expressed in the distal small intestine and plays a role in lipid metabolism (Lee et al., 2020). In this study, the GML-induced upregulation of GPR119 expression suggests that GML may reach the posterior intestine of broilers to regulate lipid metabolism. Gut microbiota is involved in the host's intestinal lipid absorption and the regulation of lipid metabolism in other metabolic organs (Wang et al., 2022). 16S rRNA gene sequencing results revealed 1,818 OTUs in the CON group and 1,963 OTUs in the GML group were plotted by Veen plot (Fig. 2B). Beta diversity assessment indicated that GML drives changes in cecal microbial community structure (Fig. 2C). ANOSIM analysis confirmed that the dissimilarity between groups was greater than the dissimilarity within groups (ANOSIM: R = 0.511, P = 0.008) (Fig. 2D). The genera CHKC1001, Coprobacter, and Ruminococcaceae_UCG_005 were the three most significantly enriched genera in the GML group (Fig. 2E). CHKCI001 is a strain of beneficial intestinal bacteria that exhibits a significant negative correlation with FCR (Zheng et al., 2022). Ruminococcaceae_UCG_005 and Coprobacter are recognized for their ability to produce short-chain fatty acids, which serve as essential energy sources for enterocytes and can modulate host metabolism (Li et al., 2022). PICRUST2 functional prediction revealed that GML-induced changes in the cecal microbiota were mainly involved in fatty acid degradation (P = 0.005), benzoate degradation (P = 0.008), and glycine, serine and threonine metabolism (P = 0.012), etc. (Fig. 2F). These results showed a potential interaction between the gut microbiota and lipid degradation, which is consistent with the observed changes in the liver. Taken together, these findings suggest that dietary GML affects microbial community structure, which may be one of several potential mechanisms by which GML reduces hepatic lipid accumulation.

Fig. 2.

Effects of GML on intestinal gene expression and cecal microbiota (n = 6). (A) Gene expression of GPR119 and AMPKα1in the jejunum. (B) Veen diagram at the OTUs level. (C) PCoA plot based on weighted UniFrac distance. (D) ANOISM boxplot. (E) LDA score distribution histogram. (F) Top 10 enriched KEGG function. Values are means, with standard errors represented by error bars. *P < 0.05 by two-tailed unpaired Student’s t-test.

In conclusion, this study demonstrates that dietary GML supplementation modulates plasma lipid profiles, hepatic lipid metabolism gene expression, and cecal microbiota composition in broilers. The upregulation of jejunal GPR119 and AMPKα1 mRNA suggests a potential novel mechanism involving these metabolic pathways. These findings indicate that GML may function beyond an antimicrobial agent, possibly as a metabolic modulator. Future work should validate these interactions in vitro, investigate causal links between microbial shifts and host signaling, and evaluate long-term production outcomes.

CRediT authorship contribution statement

Xinran Zhang: Validation, Investigation. Xue Pan: Validation, Investigation. Linglian Kong: Writing – review & editing, Writing – original draft, Visualization, Supervision, Methodology, Investigation, Data curation, Conceptualization. Zhigang Song: Resources, Project administration, Funding acquisition, Conceptualization.

Disclosures

No conflict of interest exists in the submission of this manuscript. All authors have approved the manuscript for submission.