Abstract
Guanidinoacetic acid (GAA) has been used in ruminant feeding, but it is
still unclear whether the exogenous addition of methyl donors, such as
methionine (Met), can enhance the effects of GAA. This study
investigated the effects of dietary GAA alone or combined with Met on
beef cattle growth performance and explored the underlying mechanisms
via blood analysis, liver metabolomics, and transcriptomics. Forty-five
Simmental bulls (453.43 ± 29.05 kg) were assigned to three groups for
140 days: CON (control), GAA (0.1% GAA), and GAM (0.1% GAA + 0.1% Met),
where each group consisted of 15 bulls. Compared with the CON group,
the average daily gain (ADG) and feed conversion efficiency (FCE) of
the two feed additive groups were significantly increased, and the
digestibility of neutral detergent fiber (NDF) was improved (p < 0.05).
Among the three treatment groups, the GAM group showed a higher rumen
total volatile fatty acids (TVFAs) content and digestibility of dry
matter (DM) and crude protein (CP) in the beef cattle. The serum
indices showed that the contents of indicators related to protein
metabolism, lipid metabolism, and creatine metabolism showed different
increases in the additive groups (p < 0.05). It is worth noting that
the antioxidant indexes in the serum and liver tissues of beef cattle
in the two additive groups were significantly improved (p < 0.05). The
liver metabolites related to protein metabolism (e.g., L-asparagine,
L-glutamic acid) and lipid metabolism (e.g., PC (17:0/0:0)) were
elevated in two additive groups, where Met further enhanced the amino
acid metabolism in GAM. In the two additive groups, transcriptomic
profiling identified significant changes in the expression of genes
associated with protein metabolism (including PIK3CD, AKT3, EIF4E, HDC,
and SDS) and lipid metabolism (such as CD36, SCD5, ABCA1, APOC2, GPD2,
and LPCAT2) in the hepatic tissues of cattle (p < 0.05). Overall, the
GAA and Met supplementation enhanced the growth performance by
improving the nutrient digestibility, serum protein and creatine
metabolisms, antioxidant capacity, and hepatic energy and protein and
lipid metabolisms. The inclusion of Met in the diet was shown to
enhance the nutrient digestibility and promote more efficient amino
acid metabolism within the liver of the beef cattle.
Keywords: guanidinoacetic acid, methionine, growth performance,
antioxidant capacity, protein and lipid metabolisms, beef cattle
1. Introduction
Guanidinoacetic acid (GAA), an amino acid derivative, serves as a vital
substrate in the biosynthesis of creatine within animals [[38]1].
Creatine, in turn, plays a crucial role as an energy-providing compound
for skeletal muscle during the growth and maturation phases of animals
[[39]2]. Maintaining adequate creatine levels is essential to support
optimal growth rates in animals [[40]3,[41]4]. However, the growth
phase is characterized by a high demand for creatine, which often
exceeds the capacity of endogenous synthesis. Consequently, exogenous
supplementation becomes necessary to meet the requirements for
accelerated growth [[42]5]. GAA has the advantages of low production
cost, high bioavailability, and high stability compared with creatine
[[43]6]. In recent years, its use as a growth-promoting additive has
been demonstrated in several studies to improve the growth performance
in livestock and poultry [[44]7,[45]8,[46]9,[47]10,[48]11], and its
functions are not limited to growth promotion; for example, Li et al.
[[49]12] found that GAA can improve the antioxidant capacity of the
rumen of meat sheep, and Yi et al. [[50]11] further confirmed that GAA
can enhance the antioxidant level of Angus cattle serum and optimize
nitrogen metabolism efficiency. It is worth noting that the premise for
GAA to exert its growth-promoting effect in ruminants is that the body
has sufficient methyl donors. Recent studies have suggested that methyl
donor restriction may restrict the maximum effect of GAA in beef cattle
[[51]11], which suggests that it is necessary to systematically analyze
the relevant mechanisms of GAA regulating beef cattle growth.
Methionine (Met) assumes the role of an indispensable amino acid,
exerting a critical influence on the growth of the animal organism and
making a substantial contribution to creatine biosynthesis within the
animal system, providing the indispensable methyl moiety for this
synthetic endeavor [[52]13]. It has been reported that supplementing
with Met can improve the growth performance of ruminants and positively
influence their nitrogen metabolism [[53]14,[54]15]. According to Zhang
et al. [[55]9], a mixture of 0.08% GAA and 0.06% Met improved both the
growth performance and meat quality in goats. Nevertheless, the study
lacked a direct comparison with GAA supplementation administered
independently. Currently, limited research has been conducted to
evaluate the effects of GAA supplementation, both independently and
alongside Met, on beef cattle growth performance. Determining whether
Met inclusion can further enhance the benefits of GAA in beef cattle is
particularly important.
The synthesis of creatine from GAA is a multi-tissue process. In
animals, GAA is synthesized in the kidneys and transported via the
bloodstream to the liver, where it serves as a precursor for creatine
production. Following synthesis, creatine is secreted by the liver into
circulation, enabling its delivery to various tissues [[56]1]. Thus,
preserving normal liver function is of utmost importance for the
efficient synthesis and metabolism of creatine in animals. Notably, it
has been estimated that the liver utilizes approximately 20% of the
body’s overall energy resources to sustain its diverse array of
metabolic processes, encompassing glucose metabolism, protein
metabolism, and lipid metabolism [[57]16]. As a key metabolic organ in
ruminants, the liver possesses the ability to modulate the metabolic
functions of the animal organism, especially protein metabolism, in
response to extrinsic stimuli, such as dietary modifications, which are
inextricably linked to the animal’s growth dynamics [[58]17].
Therefore, whether the exogenous addition of GAA and Met would cause
changes in the liver metabolic functions is also worth exploring in
depth. The primary objective of this study was to evaluate how GAA
influences beef cattle growth metrics and to determine whether
incorporating Met could enhance the outcomes of GAA supplementation.
This study was the first to systematically compare the effects of GAA
supplementation alone and with GAA + Met combined supplementation on
growth performance and liver metabolism in beef cattle, as well as
combine transcriptome and non-targeted metabolome analysis to reveal
its possible molecular regulatory mechanism. This not only expands the
theoretical basis for the application of GAA but also provides a new
scientific basis for improving the nutritional efficiency and
production performance of beef cattle.
2. Materials and Methods
This study obtained ethical approval from China Agricultural University
with the number AW81404202-1-4.
2.1. Experimental Material
The GAA employed was characterized by white, uncoated granules with an
efficacy content of GAA at or above 96%. Meanwhile, the utilized Met
comprised yellow, coated particles, featuring palm fat powder as the
coating agent, and had an effective Met content of no less than 60%.
The degradation rate of guanidine acetate and methionine in the rumen
and the release rate in the small intestine are shown in [59]Figure S1.
2.2. Experimental Design, Animals, and Diets
Forty-five Simmental bulls, weighing 453.43 ± 29.05 kg, were randomly
allocated to three treatment groups according to body weight, with each
group containing 15 bulls. In each treatment group, 15 bulls were
randomly assigned to three separate pens with 5 bulls in each pen. Each
pen was equipped with an automatic feed-weighing system, which can
identify the electronic ear tag number of each bull and record the feed
intake of each bull every day. This research included three groups: a
control group (CON) without any supplements; a GAA-supplemented group
(GAA) that received 1 g/kg of GAA in the dry matter (DM) diet; and a
combined supplementation group (GAM) that received both GAA and Met at
1 g/kg in the DM diet. The dosage levels were determined from earlier
studies [[60]11]. The trial spanned 140 days, with an initial 15-day
adaptation period, followed by 125 days of monitoring. The total mixed
ration (TMR) formulation for beef cattle growth was formulated
according to the NASEM [[61]18] ([62]Table S1). During the experimental
period, the cattle received the TMR diet twice daily at 08:00 and
16:00. GAA and Met were fed by premixing them with concentrate feed and
then thoroughly mixing the concentrate feed that contained additives
with roughage. All cattle received adequate feed and water throughout
the experiment.
2.3. Sample Collection
During this research, the feed specimens were gathered biweekly,
subjected to drying at 65 °C over a 48 h period, and subsequently
placed in plastic pouches for nutrient evaluation. During the final
three days, daily pre-feeding samples were also collected and processed
identically. After the experiment concluded, rectal fecal samples from
each bull were collected, placed in dry aluminum containers, and
stabilized with 10% tartaric acid before being dried at 65 °C to an
air-dry state (n = 15). All processed samples—both fecal and feed—were
kept at 4 °C in plastic bags for a later analysis of the apparent
digestibility.
The initial (IBW) and final body weights (FBW) were measured by
weighing the cattle before morning feeding at the experiment’s
commencement and conclusion. The average daily gain (ADG) was
subsequently derived from these weight data (n = 15). An automated
feed-weighing system was employed to track each bull’s daily dry matter
intake (DMI) (n = 15). Furthermore, the feed conversion efficiency
(FCE) was determined by computing the ratio of the ADG to the DMI (n =
15).
Upon completion of the trial, rumen fluid was extracted from each bull
through oral intubation and filtered using four layers of gauze. The
filtered fluid was divided into 15 mL and 50 mL centrifuge tubes, with
the latter used for pH assessments (n = 15). All rumen fluid samples
were promptly stored in an ultra-low-temperature freezer at −80 °C.
Blood samples were collected from the tail vein using vacuum tubes for
further analysis (n = 15). After clotting for 30 min at the ambient
temperature, the blood was spun at 3000 rpm for 10 min to obtain the
serum, which was then kept at −20 °C for further testing. After the
experiment, 6 beef cattle were randomly selected from each treatment
group and transported to a commercial slaughterhouse for humane
slaughter. Liver tissue samples were immediately collected and stored
in liquid nitrogen cryotubes (n = 6). After sampling, the samples were
transferred to a −80 °C ultra-low temperature freezer for a subsequent
analysis.
2.4. Parameters of Rumen Fermentation
The rumen fluid pH was assessed using an Orion Star™ A211 benchtop pH
meter (Thermo Fisher Scientific, Waltham, MA, USA). The pH meter was
calibrated with phosphate buffer solutions of pH 4.00 and 7.00 before
use. Measurements were taken at a controlled temperature of 25 °C, and
temperature compensation was employed to maintain the precision of the
pH readings. The 15 mL centrifuge tubes that contained rumen fluid were
subjected to centrifugation at 10,000 revolutions per minute for 10
min, thereby yielding the supernatant. The concentration of
ammonia-nitrogen (NH[3]-N) within this supernatant was quantified
following the phenol-sodium hypochlorite colorimetric protocol, with
measurements taken using a UV1102 spectrophotometer provided by the
Techcomp Group (Beijing, China) [[63]19]. The profile of volatile fatty
acids (VFAs) in the rumen fluid was analyzed with a GC-6800 gas
chromatograph manufactured by the Beibin Tianpu Company (Beijing,
China), in accordance with the method described by Broderick and Kang
[[64]20].
2.5. Nutrient Digestibility
The estimation of apparent nutrient digestibility was executed
following the established protocol of the acid-insoluble ash method
[[65]21]. The calculation of digestibility of specific nutrients was
obtained from the following equation:
[MATH:
Di
={1−[(Fi×<
mi>TA)/(
Ti×FA)]}×100%
:MATH]
[MATH:
Di
:MATH]
represents the apparent digestibility of a given nutrient;
[MATH:
Fi
:MATH]
denotes the concentration of said nutrient in the fecal matter;
[MATH:
FA
:MATH]
refers to the content of acid-insoluble ash in the feces;
[MATH:
Ti
:MATH]
indicates the nutrient content within the experimental diet; and
[MATH:
TA
:MATH]
specifies the level of acid-insoluble ash present in the test ration.
2.6. Chemical Analysis and Calculation
To determine the DM content of the air-dried TMR and fecal samples,
they were oven-dried at 105 °C for 4 h in accordance with AOAC [[66]22]
method 930.15. The crude protein (CP) levels in these samples were
measured using the combustion technique with a RapidNIII
Nitrogen/Protein Analyzer, in accordance with method 999.03 [[67]22].
The neutral detergent fiber (NDF) content was measured with an ANKOM
A200i semi-automatic fiber analyzer, according to the method described
by Van Soest et al. [[68]23]. For the ash content analysis, a muffle
furnace was utilized according to method 975.03 from the AOAC [[69]22].
Calcium (Ca) and phosphorus (P) concentrations were determined using
inductively coupled plasma spectroscopy following wet ashing, in
accordance with AOAC [[70]22] methods 985.01 A, B, and C. The wet
ashing procedure was conducted as described in method 975.03 B(b). The
metabolizable energy (ME), net energy for maintenance (NEm), and net
energy for gain (NEg) were calculated based on the equations outlined
by the NASEM [[71]18].
2.7. Serum Indexes
Serum biomarkers, including the total protein (TP), globulin (GLB),
albumin (ALB), glucose (GLU), urea nitrogen (UREA), triglycerides
(TGs), cholesterol (TC), low-density lipoprotein cholesterol (LDL-C),
and high-density lipoprotein cholesterol (HDL-C), were measured using a
Hitachi 7600 autoanalyzer, following the manufacturer’s instructions
from the Beijing Lidman Biochemical Co., Ltd. (Beijing, China). The
enzyme activities of aspartate aminotransferase (AST) and alanine
aminotransferase (ALT) were determined according to the International
Federation of Clinical Chemistry and Laboratory Medicine guidelines
[[72]24], while the alkaline phosphatase (ALP) activity was assessed
using the method described by Hitz et al. [[73]25]. Additionally, the
hormone-sensitive lipase (HSL), acetyl-CoA carboxylase (ACC), and fatty
acid synthase (FAS) levels were quantified with a Multiskan MK3
microplate reader by employing assay kits from the Nanjing Jiancheng
Bioengineering Institute (Nanjing, China), as per the provided
protocols.
The levels of GAA and creatine were analyzed using an Agilent HPLC1200
chromatographic system (Agilent, Santa Clara, CA, USA), following the
methodology described by Owens and Bergen [[74]26]. For the
quantification of creatine kinase (CK), creatinine, and adenosine
triphosphate (ATP), a Hitachi 7600 automatic biochemistry analyzer
(Hitachi, Japan) was employed, adhering to the protocols provided by
the Beijing Lidman Biochemistry Co., Ltd. (Beijing, China).
Additionally, the serum concentrations of guanidinoacetic
acid-N-methyltransferase (GAMT) and arginine–glycine amidinotransferase
(AGAT) were assessed using a Multiskan MK3 microplate reader (Thermo
Fisher Scientific, USA), following the guidelines detailed in the kits
supplied by the Beijing Kangjia Hongyuan Biotechnology Co., Ltd.
(Beijing, China).
2.8. Antioxidant Indexes in Serum and Liver Tissue
The concentrations of antioxidant indicators in the serum (n = 15) and
liver tissue (n = 6), including the total antioxidant capacity (T-AOC),
superoxide dismutase (SOD), catalase (CAT), malondialdehyde (MDA),
glutathione (GSH), and glutathione peroxidase (GSH-Px), were measured
using a Unico 7200 spectrophotometer (Shanghai Unico Co., Ltd.,
Shanghai, China). The analysis was performed according to the
instructions of the kit provided by the Nanjing Jiancheng
Bioengineering Institute (Nanjing, China) and the methods established
in previous studies [[75]11,[76]27].
2.9. Metabolite Detection and Data Analysis
Liver tissue (50 mg) (n = 6) was placed in 2 mL centrifuge tubes with a
6 mm grinding bead. Metabolites were extracted using 400 μL of a 4:1
methanol–water solution, including an internal standard of
L-2-chlorophenylalanine at 0.02 mg/mL. The extracted samples were
analyzed on a Thermo Fisher Scientific UHPLC-Q Exactive HF-X system for
UHPLC-MS/MS, following the conditions outlined in previous work
[[77]28,[78]29].
Progenesis QI (Waters Corporation, Milford, MA, USA) was utilized to
preprocess the LC-MS raw data, which involved a baseline correction,
peak detection, retention time alignment, and peak matching; this
ultimately generated a matrix with retention times, mass-to-charge
ratios, and intensity values. The dataset underwent a multivariate
analysis, including a principal component analysis (PCA) and orthogonal
partial least squares discriminant analysis (OPLS-DA), via the ropls
package (version 1.6.2) in R to reveal significant patterns. The model
reliability was confirmed through a 7-fold cross-validation, and the
metabolites with VIP > 1 and p < 0.05 were considered significant.
These were annotated and mapped to metabolic pathways using the Kyoto
Encyclopedia of Genes and Genomes (KEGG) database to highlight the
pathways impacted by the metabolite profile shifts.
2.10. Transcriptomic Profiling
The transcriptome of 18 liver tissue samples from cattle was profiled
using the Illumina NovaSeq 6000 platform. The RNA was extracted from
the samples, and its concentration and purity were quantified using a
Nanodrop2000 spectrophotometer. The integrity was confirmed by agarose
gel electrophoresis, and the RIN values were measured with an Agilent
2100 Bioanalyzer to ensure the sequencing quality. Libraries were
prepared using the Illumina TruSeq™ RNA Sample Prep Kit. Paired-end
reads were quality-checked with the fastp tool [[79]30], and the
cleaned reads were aligned to the reference genome using HISAT2, which
employs an orientation-specific algorithm for precise alignment
[[80]31]. The transcript assembly was performed with StringTie, a tool
designed for the reference-guided reconstruction of transcripts
[[81]32]. The gene expression differences between experimental groups
were assessed using DESeq2, a statistical method for identifying
significant changes in gene expression [[82]33]. The genes that showed
a fold change > 1.5 or <0.67 and a p-value < 0.05 were deemed
differentially expressed. For a functional interpretation, an
enrichment analysis of the differentially expressed genes was carried
out against the KEGG pathway database to pinpoint overrepresented
metabolic pathways. The pathway significance was determined using KOBAS
software (3.0 version) by applying the Benjamini–Hochberg correction
method to adjust the p-values, with a threshold set at 0.05 [[83]34].
2.11. Data Statistics and Analysis
Statistical evaluations of growth performance, rumen fermentation
parameters, nutrient digestibility, and serum-related indices were
conducted using the Mixed procedure within SAS software (version 9.4,
SAS Institute Inc., Cary, NC, USA). For this analysis, the fixed effect
in the model was the additive treatment (a), while the random effect
was attributed to the pen (P). The statistical model used is described
as follows:
[MATH:
Yij=μ+ai+Pj+e
ij :MATH]
Within this given equation,
[MATH:
Yij :MATH]
signifies the observed value for a specific metric of bulls consuming
the i-th additive within the j-th enclosure. The symbol
[MATH: μ :MATH]
corresponds to the grand mean,
[MATH:
ai
:MATH]
denotes the influence that the i-th additive had on the observed value,
and
[MATH:
Pj
:MATH]
reflects the impact from the j-th enclosure on this value.
[MATH:
eij :MATH]
is indicative of the random residual associated with each observation.
To investigate the group-wise variations, we utilized Duncan’s post hoc
multiple comparisons test. Differences between groups were considered
significant if the p-value was within the range of 0.01 to 0.05, and
highly significant when the p-value was below 0.01. At the same time,
a, b, and c were used to mark the significant differences between the
treatment groups. A trend toward significance, though not statistically
confirmed, was indicated by p-values that ranged from 0.05 to 0.1.
Spearman correlation analysis was performed in R (version 3.6.3) to
assess the relationship between the key differentially expressed genes
and metabolites. In the graphical outputs, the significance levels are
denoted as follows: * for p-values between 0.01 and 0.05, ** for
p-values between 0.001 and 0.01, and *** for p-values less than 0.001.
The error bars in the graphs represent the standard error of the mean
(SEM).
3. Results
3.1. Growth Performance, Ruminal Fermentation Parameters, and Nutrient
Digestibility
[84]Table 1 presents the impact of the GAA and Met on the growth
performance, rumen fermentation, and nutrient digestibility in the beef
cattle. The IBW and DMI showed no notable variations across the three
groups (p > 0.05). In contrast, the groups supplemented with the GAA
and GAM demonstrated a marked increase in the ADG and FCE relative to
the control group (p < 0.05). Additionally, a trend toward an increased
FBW was noted in the two feed additive groups, though it did not reach
statistical significance (p = 0.075).
Table 1.
Effect of dietary addition of guanidinoacetic acid and methionine on
growth performance in beef cattle.
Items ^1 Treatment Groups SEM p-Value
CON GAA GAM
IBW (kg) 453.96 452.43 453.87 4.43 0.988
FBW (kg) 594.00 614.14 627.87 6.18 0.075
ADG (kg) 1.00 ^b 1.16 ^a 1.24 ^a 0.03 0.002
DMI (kg) 11.20 11.42 11.43 0.13 0.735
FCE 0.09 ^b 0.10 ^a 0.11 ^a 0.003 0.004
[85]Open in a new tab
^1 IBW: initial body weight; FBW: final body weight; ADG: average daily
gain; DMI: daily dry matter intake; FCE: feed conversion efficiency. a
and b were used to mark the significant differences between the
treatment groups. n = 15.
Regarding ruminal fermentation parameters ([86]Table 2), the GAM group
exhibited significantly higher TVFAs and pentanoate concentrations
compared with the GAA and CON groups (p < 0.05). In contrast, no
notable differences were observed in the rumen pH or NH[3]-N levels
between the treatment groups.
Table 2.
Effect of dietary addition of guanidinoacetic acid and methionine on
ruminal fermentation parameters in beef cattle.
Items ^1 Treatment Groups SEM p-Value
CON GAA GAM
pH 6.57 6.44 6.42 0.035 0.153
NH[3]-N (mg/100 mL) 10.75 9.32 9.53 0.516 0.506
TVFAs (mmol/L) 79.92 ^b 92.51 ^ab 101.18 ^a 3.38 0.023
Acetate % 70.78 71.17 70.87 0.002 0.647
Propionate % 16.61 16.29 16.31 0.002 0.800
Isobutyrate % 0.96 0.91 0.91 0.001 0.707
Butyrate % 9.71 9.73 9.97 0.002 0.857
Isopentanoate % 1.49 1.39 1.37 0.001 0.778
Pentanoate % 0.45 ^b 0.50 ^ab 0.57 ^a 0.0002 0.013
Acetate/propionate 4.28 4.38 4.36 0.059 0.781
[87]Open in a new tab
^1 NH[3]-N: ammonia-nitrogen; TVFAs: total volatile fatty acids. a and
b were used to mark the significant differences between the treatment
groups. n = 15.
Regarding the nutrient digestibility ([88]Table 3), the GAM group
showed a notable improvement in the digestion of DM and CP compared
with the control (p < 0.05). Additionally, both the GAA and GAM groups
demonstrated markedly enhanced NDF digestibility compared with the
control (p < 0.01).
Table 3.
Effect of dietary addition of guanidinoacetic acid and methionine on
nutrient digestibility in beef cattle.
Items ^1 Treatment Groups SEM p-Value
CON GAA GAM
DM % 60.90 ^b 64.44 ^ab 66.57 ^a 0.009 0.034
CP % 52.20 ^b 56.09 ^ab 60.29 ^a 0.012 0.011
NDF % 52.12 ^b 60.06 ^a 63.36 ^a 0.016 0.010
[89]Open in a new tab
^1 DM: dry matter; CP: crude protein; NDF: neutral detergent fiber. a
and b were used to mark the significant differences between the
treatment groups. n = 15.
3.2. Serum Biochemistry, Antioxidant, and Creatine Metabolism Indices
The effects of the GAA and Met supplementation on the serum biochemical
profiles of the beef cattle are summarized in [90]Table 4. Both the GAA
and GAM groups exhibited significantly higher TP, GLB, and HSL levels
than the CON group (p < 0.01). Furthermore, the ALB and FAS
concentrations were significantly higher in the GAM group than in the
control (p < 0.05).
Table 4.
Effects of guanidinoacetic acid and methionine on serum biochemical
indices in beef cattle.
Items ^1 Treatment Groups SEM p-Value
CON GAA GAM
TP (g/L) 71.41 ^b 76.58 ^a 78.53 ^a 0.82 <0.001
ALB (g/L) 30.75 ^b 31.68 ^ab 32.29 ^a 0.22 0.013
GLB (g/L) 40.66 ^b 44.90 ^a 46.23 ^a 0.71 0.002
UREA (mmol/L) 1.99 ^b 2.18 ^ab 2.37 ^a 0.06 0.021
GLU (mmol/L) 3.81 3.56 3.78 0.11 0.632
TC (mmol/L) 3.44 3.19 3.44 0.10 0.504
TGs (mmol/L) 0.17 0.17 0.20 0.01 0.187
HDL-C (mmol/L) 2.01 1.89 2.03 0.05 0.442
LDL-C (mmol/L) 1.11 0.93 1.13 0.06 0.267
ALT (U/L) 35.09 30.71 42.13 2.22 0.101
AST (U/L) 101.01 98.84 101.19 2.85 0.936
ALP (U/L) 150.76 139.36 160.81 6.67 0.428
ACC (ng/mL) 1.81 2.07 2.18 0.07 0.114
HSL (ng/mL) 10.52 ^b 14.11 ^a 14.59 ^a 0.34 <0.001
FAS (ng/mL) 8.13 ^b 8.57 ^ab 9.30 ^a 0.20 0.043
[91]Open in a new tab
^1 TP: total protein, ALB: albumin, GLB: globulin, UREA: urea nitrogen,
GLU: glucose, TC: cholesterol, TGs: triglycerides, HDL-C: high-density
lipoprotein cholesterol, LDL-C: low-density lipoprotein cholesterol,
ALT: alanine aminotransferase, AST: aspartate aminotransferase, ALP:
alkaline phosphatase, ACC: acetyl-CoA carboxylase, HSL:
hormone-sensitive esterase, FAS: fatty acid synthase. a and b were used
to mark the significant differences between the treatment groups. n =
15.
[92]Table 5 details the effects on the serum creatine metabolism,
revealing that the GAA group had notably elevated GAA levels compared
with the control (p = 0.027). In contrast, the GAM group demonstrated
significantly increased AGAT and GAMT concentrations relative to both
the control and GAA groups (p < 0.01). Moreover, for AGAT and GAMT, the
GAM group exhibited the highest levels, followed by the GAA group,
which was still significantly elevated over the CON group (p < 0.01).
Table 5.
Effect of guanidinoacetic acid and methionine on serum creatine
metabolism indexes in beef cattle.
Items ^1 Treatment Groups SEM p-Value
CON GAA GAM
GAA (mg/L) 44.64 ^b 74.35 ^a 61.70 ^ab 4.54 0.027
AGAT (U/L) 22.62 ^c 27.11 ^b 30.48 ^a 0.80 <0.001
GAMT (U/L) 270.59 ^c 332.53 ^b 370.15 ^a 8.97 <0.001
Creatine (mg/L) 3.27 3.25 3.65 0.23 0.733
CK (U/L) 381.99 316.04 337.10 25.22 0.577
ATP (mg/L) 8.98 10.23 11.28 0.57 0.256
CREA (μmol/L) 140.69 145.01 147.85 3.29 0.680
[93]Open in a new tab
^1 GAA: guanidinoacetic acid, AGAT: arginine–glycine
amidinotransferase, GAMT: guanidinoacetic acid-N-methyltransferase, CK:
creatine kinase, ATP: adenosine triphosphate, CREA: creatinine. a, b
and c were used to mark the significant differences between the
treatment groups. n = 15.
[94]Table 6 outlines the effects of GAA and Met supplementation on the
serum and liver tissue antioxidant parameters in beef cattle. Relative
to the control, the serum and liver tissue of beef cattle in the GAA
and GAM groups showed significant increases in the T-AOC, SOD, GSH, and
CAT levels (p < 0.05). In contrast, the MDA concentrations were
markedly reduced in these groups (p < 0.01).
Table 6.
Effects of guanidinoacetic acid and methionine on serum and liver
tissue antioxidant indices in beef cattle.
Items ^1 Treatment Groups SEM p-Value
CON GAA GAM
Serum antioxidant indices
T-AOC (mmol/L) 0.42 ^b 0.48 ^a 0.47 ^a 0.01 <0.001
SOD (U/mL) 147.88 ^b 163.32 ^a 161.12 ^a 1.49 <0.001
GSH (μmol/L) 15.11 ^b 17.54 ^a 17.66 ^a 0.32 <0.001
GSH-Px (U/mL) 134.03 149.42 155.55 4.44 0.124
CAT (U/mL) 2.54 ^b 4.27 ^a 3.88 ^a 0.15 <0.001
MDA (nmol/mL) 4.96 ^a 3.94 ^b 3.95 ^b 0.13 <0.001
Liver tissue antioxidant indices
T-AOC (mmol/g) 0.55 ^b 0.74 ^a 0.78 ^a 0.04 0.014
SOD (U/mg) 223.89 ^b 315.95 ^a 310.09 ^a 15.20 0.011
GSH (µmol/g) 17.12 ^b 18.96 ^a 21.78 ^a 0.67 0.007
GSH-Px (U/mg) 136.69 153.29 161.03 5.95 0.244
CAT (U/mg) 2.57 ^b 4.73 ^a 4.08 ^a 0.34 0.020
MDA (nmol/mg) 5.66 ^a 3.73 ^b 3.71 ^b 0.07 0.007
[95]Open in a new tab
^1 T-AOC: total antioxidant capacity, SOD: superoxide dismutase, GSH:
glutathione, GSH-Px: glutathione peroxidase, CAT: catalase, MDA:
malondialdehyde. a and b were used to mark the significant differences
between the treatment groups.
3.3. Metabolite Identification and Sample Relationship Analysis of the Liver
Based on the completion of the raw data preprocessing, the outcomes of
the identification statistics pertaining to the total ion count and the
number of metabolites are tabulated in [96]Table S2. Using the combined
positive and negative ion analysis, 6190 mass spectral peaks were
extracted, and 1251 metabolites were finally identified by the search
library through the primary and secondary mass spectral data.
As shown in [97]Figure S2, the three treatment groups were well
clustered within the group and clearly differentiated between the
groups, thus substantiating the reliability of the data.
3.4. Differential Metabolite Analysis of the Liver
A comprehensive analysis identified a total of 389 metabolites with
differential expressions, as detailed in [98]Table S3. The distribution
and significance of these changes are illustrated through volcano plots
in [99]Figure 1. Comparing the CON group with the GAA group, we
observed 234 differentially expressed metabolites: 156 were found to be
upregulated, while 78 showed downregulation ([100]Figure 1A). When
comparing the CON group against the GAM group, there were 205
differential metabolites identified, with 148 showing increased
expression and 37 decreased ([101]Figure 1B). Lastly, the contrast
between the GAA and GAM groups highlighted 133 unique metabolites,
comprising 72 that were upregulated and 61 that were downregulated
([102]Figure 1C).
Figure 1.
[103]Figure 1
[104]Open in a new tab
Impacts of guanidinoacetic acid and methionine on liver metabolomics in
beef cattle. n = 6. (A–C) Volcano plots illustrating differential
metabolites across treatment groups; (D–F) KEGG pathways enriched by
differential metabolites. * for p-values between 0.01 and 0.05, ** for
p-values between 0.001 and 0.01, and *** for p-values less than 0.001.
3.5. KEGG Enrichment Analysis of Differential Metabolites in Liver
[105]Figure 1 illustrates the KEGG functional pathways enriched by
differentially expressed metabolites between the treatment groups. In
the CON vs. GAA comparison, the key metabolic pathways affected
included purine metabolism, tryptophan metabolism, nucleotide
metabolism, oxidative phosphorylation, cysteine and methionine
metabolisms, and cofactor biosynthesis ([106]Figure 1D). For the CON
vs. GAM comparison, the altered metabolites were primarily linked to
purine metabolism; arginine and proline metabolisms; cysteine and
methionine metabolisms; alanine, aspartate, and glutamate metabolisms;
protein digestion and absorption; and aminoacyl-tRNA biosynthesis
([107]Figure 1E). Meanwhile, in the GAA vs. GAM comparison, the
enriched pathways included pantothenate and CoA biosynthesis,
riboflavin metabolism, linoleic acid metabolism, glycolate and
dicarboxylate metabolisms, tryptophan metabolism, and beta-alanine
metabolism ([108]Figure 1F).
3.6. Key Differential Metabolites in the Liver
[109]Table 7 presents the significant differential metabolites between
the treatment groups, with log[2]^FC values above zero indicating
increased metabolite levels and values below zero reflecting decreased
levels. In the GAA group compared with CON, the liver samples exhibited
notable elevations in Inosine, LysoPC (20:2(11Z,14Z)/0:0),
S-adenosylhomocysteine, PC (17:0/0:0), L-cystine, and ADP, while
Choline, 5-hydroxykynurenine, 6-hydroxymelatonin, and NADH were
significantly reduced. Relative to CON, the GAM group showed
significantly higher concentrations of Inosine, ADP,
S-adenosylhomocysteine, L-cystine, Creatine, L-asparagine, L-glutamine,
Aspartic acid, L-glutamic acid, LysoPC (20:5(5Z,8Z,11Z,14Z,17Z)/0:0),
NAD, and PC (17:0/0:0), whereas the L-serine levels were markedly
lower. Additionally, when comparing GAM with GAA, the GAM group
demonstrated significantly increased levels of L-kynurenine,
Pantothenic acid, N′-formylkynurenine, Carnosine, Stearidonic acid, and
Linolenelaidic acid.
Table 7.
Key differential metabolites between groups.
Metabolite VIP FC p Type
CON vs. GAA
Inosine 2.060 1.074 0.006 Up
ADP 1.511 1.038 0.007 Up
S-adenosylhomocysteine 1.033 1.023 0.021 Up
L-cystine 1.834 1.066 0.007 Up
Choline 1.060 0.983 0.019 Down
5-hydroxykynurenine 2.018 0.925 0.005 Down
6-hydroxymelatonin 1.215 0.964 0.036 Down
LysoPC (20:2(11Z,14Z)/0:0) 2.105 1.081 0.040 Up
PC (17:0/0:0) 1.640 1.039 0.001 Up
NADH 1.373 0.9594 0.028 Down
CON vs. GAM
Inosine 1.744 1.067 0.024 Up
ADP 1.752 1.049 0.003 Up
S-adenosylhomocysteine 1.304 1.030 0.008 Up
L-cystine 1.699 1.062 0.032 Up
Creatine 1.136 1.023 0.041 Up
L-asparagine 1.009 1.021 0.027 Up
Aspartic acid 1.254 1.026 0.024 Up
L-glutamine 1.590 1.037 0.001 Up
L-glutamic Acid 1.070 1.019 0.041 Up
L-serine 1.041 0.977 0.014 Down
LysoPC(20:5(5Z,8Z,11Z,14Z,17Z)/0:0) 2.074 1.085 0.005 Up
PC(17:0/0:0) 1.452 1.031 0.004 Up
NAD 1.085 1.024 0.045 Up
GAA vs. GAM
L-kynurenine 4.532 1.214 0.002 Up
Pantothenic acid 1.057 1.011 0.028 Up
N′-formylkynurenine 3.154 1.140 0.021 Up
Carnosine 1.736 1.030 0.039 Up
Stearidonic acid 1.384 1.020 0.021 Up
Linolenelaidic acid 2.495 1.091 0.048 Up
[110]Open in a new tab
CON vs. GAA: FC (GAA/CON); CON vs. GAM: FC (GAM/CON); GAA vs. GAM: FC
(GAM/GAA); FC > 1 indicates upregulation of metabolites and FC < 1
indicates downregulation of metabolites. n = 6. VIP means variable
importance in projection; FC means fold change.
3.7. Analysis of Gene Expression Level and Sample Relationship in Liver
TPM was employed as a metric for the gene expression levels, with the
quantification process carried out using the RSEM software (1.3.3
version). As depicted in [111]Figure S3, the overall gene expression
profiles in the livers of beef cattle were comparable across the three
experimental groups. The two-dimensional PCA plot portrays the results
of assessing the three treatment groups in relation to the mean values
of their respective subgroups, revealing a considerable disparity
between the three groups and a clear demarcation between them. The
three-dimensional PCA plot further highlighted this distinction,
showcasing a clearer separation between the CON group and the two feed
additive groups, thereby confirming the robustness of the data
([112]Figure S3).
3.8. Comparative Gene Expression Analysis in Liver Tissues
The distribution of the DEGs across the groups is illustrated using
volcano plots in [113]Figure 2. As depicted in [114]Figure 2A, a
comparison between the liver tissues of beef cattle from the CON and
GAA groups revealed a total of 1370 DEGs, with 886 genes showing
increased expressions and 484 genes exhibiting decreased expressions in
the GAA group. In the comparison between the CON and GAM groups, as
depicted in [115]Figure 2B, a total of 1925 DEGs were identified,
including 1156 upregulated and 769 downregulated genes in the GAM
group. Meanwhile, the contrast between the CON group and GAM group, as
shown in [116]Figure 2C, revealed 428 DEGs, where 187 genes exhibited
upregulation and 241 showed downregulation in the GAM group relative to
the GAA group.
Figure 2.
[117]Figure 2
[118]Open in a new tab
KEGG enrichment pathways and related differentially expressed genes
between treatment groups. n = 6. (A–C) Volcano diagrams of
differentially expressed genes between groups; (D–F) KEGG enrichment
maps of differentially expressed genes between groups; (G–I) key
differentially expressed genes between groups. Log[2]^FC > 0 indicates
significant upregulation of genes, while log[2]^FC < 0 indicates
significant downregulation of genes.
3.9. KEGG Enrichment Analysis of Differentially Expressed Genes in Liver
The KEGG pathway enrichment analysis of the DEGs, as illustrated in
[119]Figure 2, identified specific metabolic pathways linked to the
liver tissue in the beef cattle. In the CON vs. GAA comparison, the key
pathways included PPAR signaling, cholesterol metabolism, PI3K–Akt
signaling, and histidine metabolism ([120]Figure 2D). When comparing
the CON and GAM groups, the enriched pathways encompassed cholesterol
metabolism; PI3K–Akt signaling; phenylalanine metabolism; arginine and
proline metabolisms; glycine, serine, and threonine metabolism;
glycerophospholipid metabolism; and PPAR signaling ([121]Figure 2E).
Meanwhile, the GAA vs. GAM contrast highlighted pathways involved in
unsaturated fatty acid biosynthesis; arginine and proline metabolisms;
glycine, serine, and threonine metabolisms; PPAR signaling; and
cholesterol metabolism ([122]Figure 2F).
3.10. Key Differentially Expressed Genes in the Liver
As illustrated in [123]Figure 2, the KEGG enrichment analysis of both
the DEGs and metabolites highlighted several critical pathways. The key
genes associated with PPAR signaling; cholesterol metabolism; PI3K–Akt
signaling; histidine metabolism; arginine and proline metabolisms;
glycerophospholipid metabolism; and glycine, serine, and threonine
metabolisms were identified. The GAA group showed significantly higher
expressions of key liver tissue genes, such as CD36, SCD5, ABCA1,
APOC2, AKT3, NOS3, and HDC, compared with the CON group ([124]Figure
2G). Liver tissues from the GAM group exhibited significantly elevated
expressions of genes, such as PIK3CD, AKT3, NOS3, EIF4E, CD36, NCEH1,
GPD2, LPCAT2, SCD5, and SDS, compared with the CON group ([125]Figure
2H). Furthermore, when comparing the GAM group with the GAA group, the
liver tissues from the former showed significantly higher expression
levels of ARG2, CKMT1A, SDS, and SCD ([126]Figure 2I).
3.11. Correlation Between Key Differential Metabolites and Key Differentially
Expressed Genes in Liver
[127]Figure 3 illustrates the results of a correlation analysis that
investigated the relationships between the key differential metabolites
and the DEGs. Notably, AKT3 exhibited significant positive correlations
with several lipid metabolism-related metabolites, including PC
(17:0/0:0), LysoPC (20:2(11Z,14Z)/0:0), and LysoPC
(20:5(5Z,8Z,11Z,14Z,17Z)/0:0), as well as protein-metabolism-related
compounds, such as Creatine, L-glutamic acid, and L-glutamine.
Similarly, genes like GPD2, NCEH1, CD36, SCD5, and LPCAT2 mirrored this
trend, where they showed significant positive correlations with the
same metabolites as AKT3. Moreover, NOS3 displayed significant positive
associations specifically with LysoPC (20:5(5Z,8Z,11Z,14Z,17Z)/0:0),
S-adenosylhomocysteine, PC (17:0/0:0), and L-glutamine.
Figure 3.
[128]Figure 3
[129]Open in a new tab
Heat map of the correlations between differentially expressed genes and
differential metabolites. * for p-values between 0.01 and 0.05, ** for
p-values between 0.001 and 0.01, and *** for p-values less than 0.001.
n = 6.
4. Discussion
In this study, incorporating GAA into the diet of the beef cattle was
found to significantly boost the growth performance, a result that
corroborates previous findings [[130]11,[131]17,[132]35]. Li et al.
[[133]35] found that the ADG in Angus bulls significantly improved with
increasing GAA supplementation of 0.3, 0.6, and 0.9 g/kg dry matter.
Meanwhile, Yi et al. [[134]11] noted that the ADG in Angus steers
improved with GAA supplementation at 0.8 g/kg and 1.6 g/kg, but they
also observed that beyond a certain concentration, further increases in
GAA did not lead to additional improvements in the ADG. The possibility
arises that this phenomenon stems from elevated GAA supplementation
triggering an increased methyl demand in the body, rendering the methyl
yield from dietary breakdown inadequate to accommodate the augmented
GAA provision. In this study, the IBW remained consistent across all
treatment groups, while the GAM group exhibited the highest FBW, ADG,
and FCE, surpassing the GAA group by 2.24%, 6.9%, and 10%,
respectively. These results indicate that adding Met further improved
the growth performance of the beef cattle. However, unlike the findings
of Liu et al. [[135]17], GAA supplementation in this study did not lead
to an increased feed intake. Furthermore, Li et al. [[136]36] reported
that GAA addition significantly raised the DMI of Jinjiang bulls, which
is also discordant with the findings in this study. This discrepancy
might be attributed to variations in the breed and dietary composition
between the studied beef cattle populations.
Rumen fermentation parameters reflect rumen health, and in this study,
the rumen pH showed no significant variation between the groups,
remaining stable at a healthy level. This suggests that neither the GAA
nor Met negatively affected the ruminal health. Pertinent literature
has revealed that GAA supplementation can lead to increased ruminal
TVFA concentrations in beef cattle [[137]17,[138]35], a finding that
aligns with the outcomes of our investigation. Since TVFAs originate
from the degradation of nutrients by rumen microorganisms, elevated
TVFAs may imply altered digestibility [[139]37]. Furthermore, the
significantly elevated concentration of valeric acid in the rumen
implies that the addition of GAA and Met potentially modulated the
ruminal fermentation environment and influenced the breakdown of
nutrients by rumen microbial populations. This observation was
supported by the results of the apparent nutrient digestibility
assessment. Our study revealed a significant increase in the NDF
digestibility in the GAA and GAM groups relative to the CON group.
Moreover, the DM and CP digestibilities in the GAM group exceeded those
of the CON group, consistent with prior research
[[140]11,[141]12,[142]17,[143]35]. The increase in nutrient
digestibility also explains the significantly higher ADG in the absence
of a difference in the DMI. This suggests that including GAA and Met in
the diet could positively impact nutrient digestion in beef cattle.
The TP, including ALB and GLB, is an important indicator for detecting
the synthetic function of the liver [[144]38]. ALB plays a vital role
in preserving blood osmolarity and ensuring nutrient provision
[[145]39], while GLB plays an immunological role in animals [[146]40].
In this study, GAA supplementation led to elevated serum concentrations
of TP and GLB, with the ALB levels notably higher in the GAM group than
in the CON group. These findings are consistent with those documented
by Li et al. [[147]36]. In this study, TP, ALB, and GLB all experienced
alterations within the standard concentration range, whereas ALT, AST,
and ALP are pivotal markers for determining the normalcy or otherwise
of liver function [[148]41]. The observation that these latter enzymes
did not display significant disparities between the three treatment
groups substantiates that the increases in the TP, ALB, and GLB were
not a consequence of abnormal liver function. UREA is a product of
protein metabolism [[149]42], which was increased in the serum of the
GAM group. Collectively, these findings imply that the inclusion of GAA
and Met may have moderately enhanced the liver’s protein-synthesizing
function, thereby fostering improved protein metabolism within the
organism. HSL, which is associated with lipolysis metabolism [[150]43],
was significantly elevated in the sera of both the GAA and GAM groups.
Similarly, FAS, which is linked to fatty acid synthesis [[151]44], also
showed a significant increase in the serum of the GAM group. The
possible reason for this phenomenon is the bidirectional regulation of
energy metabolism. Specifically, the addition of GAA and Met may
increase the body’s energy supply, which may stimulate adipose tissue
to store fatty acids (FAS increase); in addition, GAA and Met may
improve the body’s energy utilization, which increases HSL and promotes
fat decomposition. Together, these observations suggest that GAA and
Met supplementation may have an effect on the lipid metabolism in beef
cattle. However, the serum lipid indices (TC, TG, HDL-C, and LDL-C)
failed to reveal significant discrepancies between the three treatment
groups, potentially due to the organism’s inherent regulatory
mechanisms governing lipid metabolism [[152]45].
In this study, the serum GAA levels were significantly higher in the
GAA group compared with the CON group, with a similar pattern observed
in the GAM group. These results align with previous findings reported
by Yi et al. [[153]11]. The results suggest that not all dietary GAA
was degraded by rumen microorganisms; instead, a portion successfully
entered the bloodstream, allowing it to fulfill its intended function.
The lesser increase in the serum GAA concentration observed in the beef
cattle from the GAM group may be attributed to the heightened
utilization of GAA by the body resulting from Met supplementation. The
concentrations of AGAT and GAMT, which are key rate-limiting enzymes
involved in GAA synthesis and creatine metabolism [[154]46], were
significantly higher in both the GAA and GAM groups compared with the
control. This implies that the GAA supplementation stimulated creatine
metabolism and augmented the demand for GAA within the animals’ bodies.
In this study, no significant differences were observed in the serum
creatine, creatine kinase, or ATP levels across the three groups. This
could have been due to the elevated demand for creatine in the muscle
tissues of the beef cattle, aligning with the higher ADG recorded.
Another possible reason for this consistency is that the addition of
GAA improves the body’s energy utilization, which leads to no
significant increase in ATP in the blood. In addition, the animal’s own
regulatory effect may also be the reason why there were no significant
differences in the above three indicators [[155]47].
Creatine is known to possess the capacity to neutralize oxygen free
radicals [[156]48]; hence, GAA supplementation may exert an indirect
antioxidative effect. Previous research has demonstrated the beneficial
effects of GAA on enhancing the antioxidant status in animals. For
example, Li et al. [[157]12] observed that supplementing diets with GAA
increased the antioxidant capacity in both the rumens and sera of
lambs. Consistent with these findings, Yi et al. [[158]11] reported
increased CAT concentrations and reduced MDA levels in the sera of
Angus steers following GAA supplementation. These results align with
the observations from the present research. T-AOC represents the
overall levels of antioxidants, enzymes, and other components involved
in oxidative defense within an animal’s body. It embodies the
comprehensive antioxidant level derived from diverse antioxidant
substances and antioxidant enzymes present in the animal system
[[159]49]. Typically, T-AOC remains within a physiological range and
can be influenced by diet, exercise, and metabolic conditions. In our
study, despite the animals being healthy, the supplementation with GAA
and Met significantly increased the T-AOC levels in both the serum and
liver tissues. This suggests that GAA supplementation not only provides
metabolic benefits but also enhances antioxidant defense mechanisms.
One possible explanation for this significant increase in T-AOC is the
upregulation of antioxidant enzyme activity, particularly SOD and CAT,
which play distinct roles in mitigating oxidative stress. SOD converts
superoxide anion radicals (O[2]⁻) into hydrogen peroxide and oxygen,
while CAT further decomposes hydrogen peroxide into water and oxygen
[[160]50,[161]51]. The elevated activities of these enzymes in both
serum and liver tissues indicate an enhanced endogenous antioxidant
response. Notably, the increase in CAT activity suggests a potential
metabolic adaptation to counteract oxidative stress associated with
increased metabolic rates due to GAA supplementation. This supports the
notion that while GAA promotes growth, it may also lead to increased
metabolic activity, potentially inducing mild oxidative stress, which
is then neutralized through an upregulated antioxidant defense system.
Moreover, the reduction in MDA, a byproduct of lipid peroxidation
[[162]52], further supports the hypothesis that GAA supplementation
improves the body’s ability to manage oxidative stress. The observed
increase in GSH levels in serum and liver tissues, without a
corresponding significant increase in the GSH-Px activity, may be
attributed to the increased consumption of GSH-Px in response to
oxidative stress, resulting in a higher GSH turnover [[163]53]. This
reflects a compensatory mechanism where the body maintains redox
homeostasis through increased antioxidant production rather than solely
relying on enzymatic activity. A substantial proportion of nutrients
assimilated by the stomach and intestines are conveyed via the
bloodstream to the liver, where they undergo metabolic transformations
[[164]54] before being distributed to various tissues and organs
throughout the body via the circulatory system. The consistency of the
changes in the above antioxidant indicators in serum and liver tissues
leads to the view that changes in liver metabolic function may affect
the corresponding metabolic indicators in the blood [[165]55]. In
addition, this study also observed significant changes in the levels of
serum indicators related to protein metabolism and lipid metabolism to
varying degrees. Hence, the metabolomic analysis of liver tissues in
this study could facilitate the exploration of the effects of GAA
supplementation on liver metabolic functions, while transcriptomic
analysis could elucidate the precise mechanisms underlying metabolic
function changes at the gene expression level.
Relative to the CON group, the concentrations of Inosine, ADP,
S-adenosylhomocysteine, L-cysteine, and PC (17:0/0:0) were elevated in
both the GAA group and GAM group. Inosine is a key intermediate in
purine metabolism and also participates in nucleotide metabolism and
energy metabolism [[166]56]; ADP is also involved in the above
metabolism and is also a marker of oxidative phosphorylation in the
organism [[167]57]. The increased levels observed in both the GAA and
GAM groups indicate that GAA supplementation enhances energy metabolism
in beef cattle, providing abundant substrates for the synthesis of
amino acids, sugars, nucleic acids, and fatty acids.
S-adenosylhomocysteine (SAH), a crucial metabolite in creatine
synthesis, is generated during the conversion of S-adenosylmethionine
to creatine with GAA [[168]58]. Elevated SAH levels indicate increased
creatine production in the hepatic tissues of both the GAA and GAM
groups; in addition, SAH is metabolized to homocysteine, which reacts
with betaine to be able to produce methionine, while choline is a
precursor substance of betaine [[169]59]. The lower Choline levels
observed in the GAA group, relative to the control, may indicate a
higher requirement for betaine, indirectly suggesting that GAA
supplementation enhanced the hepatic creatine metabolism. Furthermore,
hepatic creatine levels in the GAM group were markedly elevated
relative to the control, indicating that Met supplementation further
enhanced the creatine synthesis in the liver. This suggests that the
addition of Met further enhanced the creatine synthesis in the liver of
the beef cattle. These changes corresponded to the changes in serum
indicators of creatine metabolism. PC (17:0/0:0), LysoPC
(20:2(11Z,14Z)/0:0), and LysoPC (20:5(5Z,8Z,11Z,14Z,17Z)/0:0) were all
enriched in the glycerophospholipid metabolic pathway, which has the
roles of constructing cell membranes, participating in lipid
metabolism, and regulating the cholesterol metabolism in animals
[[170]60]. The differing degrees of increase in the content of these
three substances in the GAA group and GAM group indicate that the GAA
supplementation stimulated the glycerophospholipid metabolic pathway,
and the augmentation of this pathway suggests potential enhancement of
lipid metabolism within the livers of the beef cattle. This finding
also provides an explanation for the increased serum lipase content
observed.
Previous research has demonstrated the impact of GAA supplementation on
amino acid metabolism in animals [[171]10], which aligns with the
results observed in the current investigation. In the hepatic tissues
of the GAA group, the concentrations of 5-hydroxykynurenine and
6-hydroxymelatonin, which are both associated with the tryptophan
metabolic pathway, were significantly reduced relative to the control.
Tryptophan, an essential amino acid, is primarily used by the host for
protein synthesis [[172]61]. The decreased levels of its related
metabolites suggest that GAA supplementation suppresses tryptophan
catabolism, thereby supporting improved protein synthesis. L-cystine,
which is known for supporting hepatic detoxification [[173]62],
significantly increased in both the GAA and GAM groups, suggesting that
GAA supplementation boosts the liver detoxification capacity. Notably,
Met supplementation significantly elevated the Aspartic acid,
L-asparagine, L-glutamic acid, and L-glutamine levels while reducing
L-serine in the liver of the GAM group cattle. These amino acids are
integral to processes such as protein digestion and absorption. These
alterations indicate increased activity in essential metabolic pathways
related to protein synthesis, such as aminoacyl-tRNA biosynthesis;
arginine and proline metabolisms; cysteine and methionine metabolisms;
glycine, serine, and threonine metabolisms; and alanine, aspartate, and
glutamate metabolisms. The rise in amino acid metabolites in the GAM
group suggests that Met supplementation enhanced the hepatic amino acid
metabolism. This reinforces the idea that beef cattle in the GAM group
exhibited enhanced protein synthesis capacity, aligning with their
greater daily weight gain.
NADH is known as the reduced coenzyme I and is involved in glycolysis
and cellular respiration [[174]63], while NADPH is known as the reduced
coenzyme II and plays energy supply, signal transduction, and
antioxidant roles in cells [[175]64]. Although NADPH is widely
considered to be the main reducing equivalent involved in the
antioxidant defense system (especially through its role in the
glutathione reductase and thioredoxin systems), recent studies have
also emphasized that NADH has certain antioxidant properties [[176]65].
NADH can directly scavenge some reactive oxygen species (ROS) through
its inherent reducing ability and can indirectly promote antioxidant
regeneration, although to a lesser extent than NADPH; in addition,
fluctuations in NADH/NAD⁺ levels can reflect the cellular redox status
and metabolic activities, especially those within mitochondria
[[177]63]. Therefore, the significant decrease in NADH levels observed
in the GAA group and the significant increase in the level of its
oxidized counterpart NAD+ in the GAM group in this study not only
reflect changes in the energy metabolism but also partially contribute
to redox regulation in liver tissue. Unlike NADH, NADPH is primarily
produced through the pentose phosphate pathway (PPP), a key metabolic
pathway that runs in parallel with glycolysis. The PPP plays a crucial
role in cellular antioxidant defense by providing NADPH, which is
essential for maintaining the reduced state of glutathione and
supporting other antioxidant systems [[178]64]. Although NADPH was not
specifically detected in our metabolomics analysis, its indirect role
in redox homeostasis is well recognized. The enhanced antioxidant
enzyme activities observed in the GAA and GAM groups may also reflect
upstream activation of the metabolic pathways, including the PPP, which
deserves further investigation in future studies. Additionally, hepatic
concentrations of Pantothenic Acid and Carnosine, which are critical
for Pantothenate and CoA biosynthesis and beta-Alanine metabolism,
respectively, were markedly elevated in the GAM group relative to the
GAA group. Pantothenic Acid is known to contribute to cellular energy
metabolism, substance synthesis, and regulation [[179]66], whereas
Carnosine is intimately tied to skeletal muscle energy metabolism and
protein synthesis [[180]67]. Furthermore, L-Kynurenine and
N′-Formylkynurenine, which are associated with tryptophan metabolism,
as well as Stearidonic acid and Linolenelaidic acid, which are linked
to α-linolenic acid metabolism, showed significant increases in the
hepatic tissues of the GAM group. The changes in these metabolites
suggest that protein and lipid metabolisms were more active in the
livers of beef cattle in the GAM group than in the GAA group. This
finding corresponds to the observed higher FBW and ADG in the GAM
group.
To explore the mechanisms underlying the observed metabolite changes, a
transcriptomic analysis of liver tissues was conducted. The PI3K–AKT
signaling pathway, which is known to regulate energy metabolism and
protein synthesis in animals [[181]68,[182]69], was identified as a key
contributor. In this pathway, the AKT3 gene was significantly
upregulated in the liver of beef cattle from both the GAA group and GAM
group, while the PIK3CD gene showed significant upregulation,
specifically in the GAM group. This result indicates that the PI3K–AKT
pathway was activated in both the GAA and GAM groups, suggesting that
GAA supplementation promoted improved energy and protein metabolism in
the hepatic tissues of beef cattle. This was flanked by the results
showing that AKT3 had significant positive correlations with Creatine,
L-glutamic acid, and L-glutamine. NOS3 is a downstream target gene of
the PI3K–AKT pathway that is responsible for the transcriptional
regulation of eNOS production. eNOS, in turn, catalyzes the conversion
of L-arginine and reactive oxygen species (O[2]) into L-citrulline and
nitric oxide (NO), a process that aids in the elimination of reactive
oxygen species from the body [[183]70]. At the same time, NO helps to
dilate blood vessels so that more blood flows through the liver
[[184]71], which can bring more nutrients to the liver for conversion
and metabolism. The significant upregulation of NOS3 in the liver
tissues of beef cattle from both the GAA group and GAM group indicates
that GAA supplementation can elevate NOS3 expression by activating the
PI3K–AKT pathway, thereby contributing to the improvement of the
liver’s antioxidant capacity and the enhancement of the overall
nutrient metabolism in beef cattle. The positive correlations between
NOS3 and phospholipids, creatine metabolism-related metabolites, and
L-glutamine were also confirmed. The gene EIF4E, which plays a key role
downstream in the PI3K–AKT signaling pathway and is essential for
regulating protein synthesis [[185]72], was significantly upregulated
in the GAM group compared with the control group. These findings imply
that the simultaneous administration of GAA and Met could improve
hepatic protein synthesis in beef cattle. Moreover, this study observed
notable changes in genes associated with amino acid metabolism. For
example, HDC was notably elevated in the GAA group, where it
contributed to histidine metabolism by converting histidine into
histamine [[186]73]. In contrast, SDS, which is involved in serine
metabolism by facilitating the conversion of serine to pyruvate
[[187]74], exhibited significant upregulation, specifically in the GAM
group. The gene expression patterns suggest that GAA supplementation
enhances amino acid metabolism in the liver, and the addition of Met
may further increase the protein synthesis efficiency.
Significant enrichment of both the PPAR signaling pathway and
cholesterol metabolism was observed in the GAA and GAM groups. Central
to the PPAR pathway are genes like CD36 and SCD5. CD36 acts as a key
regulator of fatty acid sensing and plays a pivotal role in modulating
lipid metabolism [[188]75], while SCD5 is essential as a rate-limiting
enzyme for monounsaturated fatty acid production. Specifically, SCD5
facilitates the conversion of stearoyl coenzyme A (C18:0) and palmitoyl
coenzyme A (C16:0) into oleic acid (C18:1) and palmitoleic acid
(C16:1), respectively [[189]76]. In the current research, both CD36 and
SCD5 exhibited significant upregulation in the GAA and GAM groups,
suggesting heightened lipid metabolic activity. These genes were also
associated with specific lipid-related metabolites, including LysoPC
(20:2(11Z,14Z)/0:0) and LysoPC (20:5(5Z,8Z,11Z,14Z,17Z)/0:0). These
metabolites exhibited a significant positive correlation with one
another. These findings collectively suggest that GAA supplementation
effectively regulates hepatic lipid metabolism. In terms of cholesterol
metabolism, ABCA1 and APOC2 were notably upregulated in the GAA group,
whereas NCEH1 showed significant upregulation in the GAM group.
Additionally, genes involved in glycerophospholipid metabolism, such as
GPD2 and LPCAT2, were significantly upregulated in the GAM group. These
gene expression changes further support the regulatory role of GAA
supplementation on lipid metabolism in beef cattle livers.
Additionally, the expression of SCD, a gene linked to the PPAR pathway,
was notably higher in the GAM group compared with the GAA group,
highlighting the added effect of Met supplementation. Analogously, ARG2
and CKMT1A, genes associated with arginine and proline metabolism,
along with SDS, a gene involved in serine metabolism, all displayed
significant upregulation in the GAM group. These gene expression
alterations collectively suggest that Met supplementation can further
potentiate lipid metabolism and amino acid metabolism in the livers of
beef cattle. Furthermore, additional transcriptomic and metabolomic
analyses of the longissimus lumborum (LL) muscle revealed that dietary
GAA supplementation improved the meat quality, antioxidant capacity,
and modulated nutritional and fatty acid profiles. The addition of RPM
further enhanced the antioxidant capacity and altered the fatty acid
composition. These findings were associated with significant changes in
genes and metabolites in amino acid and lipid metabolic pathways
[[190]27]. Thus, GAA and RPM not only affect liver metabolism but also
have meaningful effects on muscle metabolism, supporting improved
growth performance and meat quality. Furthermore, given that beef is
ultimately intended for human consumption, it is important to evaluate
not only the effects of dietary interventions on animal performance and
metabolism but also their potential impacts on the meat quality and
food safety. Although the amount of methionine supplementation in this
study was within the nutritional recommendations and physiological
suitability for ruminants, the long-term consequences of such
interventions—particularly the accumulation of amino acids or related
metabolites in edible tissues—need careful consideration. Although no
adverse effects on the liver function were observed in the current
trial and improvements in the antioxidant capacity and growth
performance were evident, further studies are needed to assess the
nutritional safety of methionine-enriched meat products for human
consumption. Future research should combine comprehensive food safety
assessments with nutritional assessments relevant to humans to ensure
that dietary supplementation strategies for livestock not only benefit
production efficiency but also comply with public health
considerations.
5. Conclusions
In summary, incorporating GAA into the diet enhanced the growth
performance, nutrient digestibility, and serum protein and creatine
metabolisms of beef cattle, while also boosting their antioxidant
capacity. Furthermore, the inclusion of Met further augmented the
nutrient digestibility. Furthermore, it was found that incorporating
GAA into the diet led to the upregulation of metabolites involved in
energy and protein and lipid metabolisms within the liver tissues. The
Met supplementation, on the other hand, moderately enhanced the amino
acid metabolism in the livers of the beef cattle. The changes observed
in these metabolites were closely linked to the increased expression of
genes that regulate protein and lipid metabolic processes. Therefore,
the results suggest that combining GAA with methyl donors like Met
could be beneficial for the rearing of beef cattle. This study provides
valuable insights for optimizing the use of GAA and Met in beef cattle
production, highlighting their potential to improve the metabolic
efficiency and overall animal performance during the rearing process.
Abbreviations
The following abbreviations are used in this manuscript:
GAA Guanidinoacetic acid
Met Methionine
ADG Average daily gain
FCE Feed conversion efficiency
NDF Neutral detergent fiber
TVFAs Total volatile fatty acids
DM Dry matter
CP Crude protein
TMR Total mixed ration
IBW Initial body weight
FBW Final body weight
DMI Dry matter intake
NH3-N Ammonia-nitrogen
VFAs Volatile fatty acids
Calcium Ca
Phosphorus P
ME Metabolizable energy
NEm Net energy for maintenance
NEg Net energy for gain
TP Total protein
GLB Globulin
ALB Albumin
GLU Glucose
UREA Urea nitrogen
TGs Triglycerides
TC Cholesterol
LDL-C Low-density lipoprotein cholesterol
HDL-C High-density lipoprotein cholesterol
ALT Alanine aminotransferase
AST Aspartate aminotransferase
ALP Alkaline phosphatase
HSL Hormone-sensitive lipase
ACC Acetyl-CoA carboxylase
FAS Fatty acid synthase
CK Creatine kinase
ATP Adenosine triphosphate
GAMT Guanidinoacetic acid-N-methyltransferase
AGAT Arginine–glycine amidinotransferase
T-AOC Total antioxidant capacity
SOD Superoxide dismutase
CAT Catalase
MDA Malondialdehyde
GSH Glutathione
GSH-Px Glutathione peroxidase
PCA Principal component analysis
OPLS-DA Orthogonal partial least squares discriminant analysis
KEGG Kyoto Encyclopedia of Genes and Genomes
[191]Open in a new tab
Supplementary Materials
The following supporting information can be downloaded from
[192]https://www.mdpi.com/article/10.3390/antiox14050559/s1. Table S1:
Diet formula and nutritional composition during the trial period; Table
S2: Liver metabolome total ion count and metabolite count statistics;
Table S3: Liver metabolite details; Figure S1: Rumen degradation rate
and intestinal release rate of guanidinoacetic acid and methionine;
Figure S2: Sample relationship analysis plot for the liver metabolome;
Figure S3: Gene expression distribution, with two-dimensional and
three-dimensional principal component analysis plots of the liver
transcriptome.
[193]antioxidants-14-00559-s001.zip^ (923.1KB, zip)
Author Contributions
Conceptualization, Z.Z. and S.Y.; methodology, S.Y.; validation, Z.Z.,
H.W. and Q.M.; formal analysis, S.Y.; investigation, S.Y., J.W., B.Y.,
X.Y. and A.A.; resources, Z.Z., H.W. and Q.M.; data curation, S.Y.;
writing—original draft preparation, S.Y.; writing—review and editing,
Z.Z. and S.Y.; visualization, S.Y.; supervision, Z.Z.; project
administration, Z.Z.; funding acquisition, Z.Z. All authors have read
and agreed to the published version of the manuscript.
Institutional Review Board Statement
This study obtained ethical approval from China Agricultural University
with the number AW81404202-1-4.
Informed Consent Statement
Not applicable.
Data Availability Statement
Data will be provided upon reasonable request.
Conflicts of Interest
The authors declare no conflicts of interest.
Funding Statement
This work was supported by the National Key R&D Program of China
(Project No. 2023YFD1301302) and the Government Purchase Service of
China (Grant Nos. 16200158 and 16190050).
Footnotes
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References