Abstract
Background
Hydroxytryptophan (5-HTP) can regulate the synthesis of
5-Hydroxytryptamine (5-HT) and melatonin (MT). In a previous metabolome
analysis, we found that 5-HTP is an effective ingredient in yeast
culture for regulating rumen fermentation. However, research on the
effect of this microbial product (5-HTP) as a functional feed additive
in sheep production is still not well explained. Therefore, this study
examined the effects of 5-HTP on sheep rumen function and growth
performance using in vitro and in vivo models.
Methods
A two-factor in vitro experiment involving different 5-HTP doses and
fermentation times was conducted. Then, in the in vivo experiment, 10
sheep were divided into a control group which was fed a basal diet, and
a 5-HTP group supplemented with 8 mg/kg 5-HTP for 60 days.
Results
The results showed that 5-HTP supplementation had a significant effect
on in vitro DMD, pH, NH[3]-N, acetic acid, propionic acid, and TVFA
concentrations. 5-HTP altered rumen bacteria composition and diversity
indices including Chao1, Shannon, and Simpson. Moreover, the in vivo
study on sheep confirmed that supplementing with 8 mg/kg of 5-HTP
improved rumen fermentation efficiency and microbial composition. This
led to enhanced sheep growth performance and increased involvement in
the tryptophan metabolic pathway, suggesting potential benefits.
Conclusion
Dietary 5-HTP (8 mg/kg DM) improves sheep growth performance by
enhancing ruminal functions, antioxidant capacity, and tryptophan
metabolism. This study can provide a foundation for the development of
5-HTP as a functional feed additive in ruminants’ production.
Keywords: 5-hydroxytryptophan, sheep, ruminal fermentation, microbiota,
growth performance, metabolites
1. Introduction
5-Hydroxytryptophan (5-HTP) can regulate the synthesis of
5-Hydroxytryptamine (5-HT) and melatonin (MT). 5-HT and its derivatives
have been recognized as potential indicators of Alzheimer’s disease
progression along the microbiota-gut-brain axis ([53]1). Melatonin, a
popular, commercially available drug, is derived from 5-HTP ([54]2) and
regulates 5-HT levels in the body. Decreased 5-HT levels can cause
insomnia. 5-HTP regulates 5-HT production, improves sleep in animals
([55]3), and relieves depression ([56]4). 5-HTP has antioxidant,
anti-inflammatory, and analgesic properties with higher hydroxyl
radical-scavenging effects than vitamin C ([57]5). It maintains
membrane fluidity during oxidative stress ([58]6) and alleviates
hyperglycaemia-induced oxidative stress ([59]7). Tryptophan (Trp), an
essential amino acid, is crucial for animal production and the
maintenance of immune function. Its metabolite, 5-HT, regulates the
microbial composition of the digestive tract and helps maintain the
immune function of the body ([60]8). Trp can affect animal feed intake
and ingestion as a raw material for tissue protein synthesis ([61]9).
Trp supplementation in the rumen of dairy cows can lead to an increased
milk yield, higher levels of blood growth hormones, improved
antioxidant capacity, and increased MT content ([62]10). Trp can
effectively reduce urinary nitrogen excretion and increase nitrogen
retention in the meat of growing lambs ([63]11). 5-HTP suppresses the
release of gastric hydrochloric acid ([64]12), increases
gastrointestinal motility ([65]13), and is rapidly absorbed by most
tissues ([66]14). Zhao et al. ([67]15) found that rumen-protected 5-HTP
supplementation increased blood 5-HTP and MT content in sheep during
the day and night, respectively, and increased MT synthesis in the
pineal gland and intestine. 5-HTP perfusion in the intestinal tract and
blood of sheep significantly increases MT levels, antioxidant capacity
in the mucosa, liver, muscle, adipose tissue, abdominal and tail fat,
and MT content in the liver and muscle ([68]16). Prenatal injection of
5-HTP reduced the casein content in dairy goat colostrum on the day of
parturition, suggesting that 5-HT can control milk protein synthesis
during the perinatal period ([69]17). 5-HTP supplementation enhances
milk yield, plasma growth hormone, prolactin, and insulin content in
lactating dairy cows ([70]18), whereas intragastric infusion increases
serum 5-HT content in Holstein steers ([71]19). In a previous
metabolome analysis, we found that 5-HTP is an effective ingredient in
yeast culture for regulating rumen fermentation ([72]20). However,
research on the effect of this microbial products (5-HTP) as a
functional feed additive in sheep production has not yet been well
explained. Therefore, in this study, the interactions between 5-HTP and
sheep was elucidated based on in vitro and in vivo models.
2. Material and methods
2.1. Animal ethics statement
All experimental procedures followed the Guidelines for the Care and
Use of Experimental Animals at Jilin Agricultural University
(JLAU-ACUC2022-003, Changchun, China).
2.2. Experimental design and animals
5-HTP was purchased from Shanghai Macklin Biochemical Co., Ltd. with a
purity of 99% and stored at 2-8°C. Before the start of the experiment,
the diets used for in vitro and in vivo experiments was tested for Trp
and 5-HTP content by Qingdao Kechuang Quality Inspection Company. The
results showed that the Trp content was 92.77 μg/g, and the 5-HTP
content was not detectable (<0.6 μg/g).
In the in vitro study, a two-factor experimental design was applied,
with 5-HTP doses (0, 2, 4, 8, and 10 mg/kg DM) and fermentation times
(0, 3, 6, 12, 24, and 48 h) as factors. Three rumen-cannulated
short-tailed Han sheep rams with an average body weight of 30 ± 2.5 kg,
were utilized as rumen fluid donors.
The in vitro results showed that 5-HTP supplementation had a
significant effect on in vitro DMD, ruminal pH, NH3-N, acetic acid,
propionic acid, and TVFA concentrations. Therefore, 8 mg/kg 5-HTP was
chosen in the in vivo experiments. A total of ten short-tailed Han
sheep rams with an average body weight of 20 ± 1.5 kg were used in a
univariate experimental design. The sheep were divided into the control
and 5-HTP groups, with five sheep in each group. The control group
received a basal diet only ([73] Supplementary Table S1 ), and the
5-HTP group was supplemented with 8 mg/kg DM 5-HTP. The sheep were
housed in individual pens with wire partitions and bamboo flooring
raised 40 cm above the ground. The sheep were given 15 days to adapt to
the basal diet before the beginning of the 60-day experimental period.
2.3. Rumen fermentation parameters in vitro
Rumen fluid was collected before morning feeding using a rigid PVC tube
from different points in the rumen. The fluid was then transferred to a
warmed (39°C) thermos flask that had been purged with CO[2] for 10 min.
The fluid was filtered through a four-layer cheesecloth. An ANKOM^RF
Gas Production System was used to measure gas production during
fermentation. Each sample (2.00 g) was placed in an 800-mesh nylon bag
and heat-sealed. The bag was placed in a 250-mL ANKOM bottle and 120 mL
of buffer-rumen solution was added according to the method described by
Menke ([74]21). The bottles were incubated in a shaker at 39°C and 80
rpm for fermentation. Samples were collected at 0, 3, 6, 12, 24, and 48
h for in vitro digestion and rumen fermentation analysis, and at 0, 12,
and 48 h for microbial composition and metabolite analysis. There were
12 replicates for each sampling time. The pH level was measured using a
SANXIN MP523-04 portable pH meter (Shanghai Sanxin Instrument Co.,
Ltd., Shanghai, China). Ammonia nitrogen (NH[3]-N) concentration was
determined using a colorimetric method ([75]22). A Shimadzu UV-1201 UV
colorimetric Spectrophotometer (Shimadzu, Tokyo, Japan) was used for
colorimetry. Volatile fatty acids (VFA) were measured using an Agilent
7890 B gas chromatography system (Agilent Technologies, Santa Clara,
CA, USA) ([76]23). Gas production was performed using an ANKOM^RF Gas
Production System automatically recorded by GPM software. The amount of
gas production was calculated according to the formula:
[MATH:
Vy=Vx× Pps
i×0.068004084 :MATH]
, where: Vy = 39°C gas production volume, mL; Vx = the gas volume in
the space above the culture medium in each sample bottle, mL; Ppsi =
GPM software automatically recorded 24 h cumulative pressure, psi. To
determine the dry matter degradation (DMD) rate, the nylon filter bag
was washed with cold water, air-dried for 24 h, and then oven-dried at
65°C until a constant weight was achieved. Thereafter, the DMD rate was
determined using the formula:
[MATH:
DMD rate(%)=A−(B−W×K)A×10
0 :MATH]
A = substrate weight before fermentation (dry matter basis)
B = sample + nylon bag weight after fermentation (dry matter basis)
W = nylon bag weight after fermentation (after drying at 105 °C)
K = nylon bag factor (weight after drying at 105 °C after
fermentation/weight before fermentation)
2.4. Microbial DNA extraction, PCR amplification, sequencing, and analysis in
vitro
Rumen fluid samples for high-throughput sequencing were sent to
Shanghai Personal Biotechnology Co., Ltd. (Shanghai, China). Nucleic
acids were extracted using the OMEGA Soil DNA Kit and DNA was
quantified using a Nanodrop. The V3-V4 region of the bacterial 16S rRNA
gene was selected for sequencing. PCR amplification of the bacterial
16S rDNA V3-V4 specific primer sequences, 338F
(5′-ACTCCTACGGGAGGCAGCA-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) was
performed using the NEB Q5 DNA high-fidelity polymerase.
Sequencing libraries were prepared using the Illumina TruSeq Nano DNA
LT preparation kit designed for high-throughput sequencing. Sequencing
data were primarily analyzed using the DADA2 method after the machine
was exited for steps such as primer removal, quality filtering,
denoising, splicing, and chimerism removal ([77]24). Alpha diversity
indices were calculated using QIIME2 (2019.4) and R language using the
ggplot2 package. Beta-diversity analysis was conducted by calculating
the differences between samples. The abundance values of metabolic
pathways were determined using the Kyoto Encyclopedia of Genes and
Genomes (KEGG) database, MetaCyc database, and three commonly used
metabolic pathway databases in COG data, followed by metabolic pathway
difference analysis.
2.5. Rumen metabolite analysis in vitro
2.5.1. Sample pretreatment
A sample (200 μL) was collected to which 800 μL of precooled extraction
solution (methanol and ribitol) was added, and vortexed for 30 seconds.
The samples were sonicated in an ice-water bath for 10 min. After
centrifugation at 12,000 rpm and 4°C for 15 min, 400 μL of the
supernatant was transferred into a 1.5 mL Eppendorf tube. The quality
control (QC) samples were combined with a 70 μL sample. The extract was
dried, and the dried metabolite was mixed with 40 μL of methoxyamine
reagent. Each sample received 50 μL of
bis-(trimethylsilyl)trifluoroacetamide, and the mixture was incubated
for 1.5 h at 70°C. Fatty acid methyl esters (FAMEs) were added to the
mixed samples and tested randomly.
2.5.2. GC-TOF-MS analysis
The Agilent 7890 gas chromatography-time-of-flight mass spectrometer
was equipped with an Agilent DB-5MS capillary column (30 m × 250 μm ×
0.25 μm, JampW Scientific, Folsom, CA, USA), GC-TOF-MS was applied
([78]25).
2.6. Growth performance of sheep
The dry matter intake (DMI, kg/day) and body weights (kg) were measured
before the morning feeding on days 0, 15, 30, 45, and 60. The average
daily gain (kg/d) and total body weight gain (kg) were calculated
accordingly.
2.7. Blood biochemical indices in sheep
Serum samples were collected from the jugular vein on days 0, 15, 30,
45, and 60, and then centrifuged at 3000 rpm and 4°C for 10 min. The
supernatant was stored at -20°C until analysis. Blood biochemical
indices were analyzed at the Beijing Huaying Institute of Biotechnology
(Beijing, China). Blood antioxidant indicators, including total
antioxidant capacity (T-AOC, HY-60021 kit), superoxide dismutase (SOD,
HY-60001 kit), glutathione peroxidase (GSH-PX, HY-60005 kit), and
catalase (CAT, HY-M0018 kit), and malondialdehyde (MDA, HY-60003 kit).
Blood hormones, such as insulin (INS, HY-D0001 kit) and growth hormones
(GH, HY-C0018 kit). The levels of 5-HT (HY-157 kit), 5-HTP (HY-10890
kit), and MT (HY-D0040 kit).
2.8. Blood metabolite analysis in sheep
2.8.1. Sample pretreatment
The sample (100 μL) was transferred into an Eppendorf tube with a 400
μL mixture of methanol and acetonitrile (1:1, V/V). Finally, the
mixture was vortexed for 30 s. The sample was sonicated for 10 min
while being immersed in an ice water bath and maintained at -40°C for
an hour. Subsequently, the sample was subjected to centrifugation at
4°C and 12,000 rpm for 15 min. The supernatant was transferred to an
injection bottle for testing. The supernatant was combined with quality
control samples and analyzed together.
2.8.2. LC-MS analytical conditions
The Vanquish ultra-high-performance liquid chromatograph (Thermo Fisher
Scientific) is equipped with a Waters ACQUITY UPLC BEH Amide (2.1 mm ×
100 mm, 1.7 μm) liquid chromatographic column for separating the target
compounds ([79]26). Phase A of the LC was aqueous and contained 25 mM
ammonium acetate and 25 mM ammonia, whereas phase B contained
acetonitrile. The sample disc temperature was 4°C, and the injection
volume was 2 μL. A Thermo Q Exactive HFX mass spectrometer was used to
collect primary and secondary mass spectral data. The parameters
included a sheath gas flow rate of 30 Arb, an auxiliary gas flow rate
of 25 Arb, a capillary temperature of 350°C, a full MS resolution of
120,000, an MS/MS resolution of 7,500, collision energy of 10/30/60 in
NCE mode, and a spray voltage of 3.6 kV (positive) or -3.2 kV
(negative).
2.9. Statistical analysis
Statistical analysis for all repeated measurements was performed using
SPSS software version 27 General Linear Model. The in vitro variables
were examined using two-way ANOVA and significance levels were
evaluated using Duncan’s multiple-range test. The in vivo data were
analyzed using the independent sample t-test and presented as mean ±
SEM. A significant difference was defined as P < 0.05, and a highly
significant difference was defined as P < 0.01. Additionally, we used
the ChromaTOF software, ProteoWizard software, and a self-written R
program package (kernel: XCMS) ([80]26).
3. Results
3.1. Rumen fermentation parameters in vitro
The pH, ammonia nitrogen (NH[3]-N), DMD, and gas production results are
presented in [81]Table 1 . The pH of the 5-HTP group decreased
significantly during the fermentation period (P < 0.01). The NH[3]-N
concentration was influenced by both 5-HTP dose (P < 0.05) and
fermentation time (P < 0.01). At 12 h, the DMD rates were higher in the
high-dose groups (8 mg/kg and 10 mg/kg). Additionally, in the 8 mg/kg
group, DMD was greater at 24 and 48 h compared to the 10 mg/kg group (P
< 0.05). The 5-HTP supplement had a significant effect on gas
production (P < 0.05), with higher levels observed in the 8 mg/kg group
at 12, 24, and 48 h. Furthermore, it also significantly affected acetic
acid (P < 0.05) and total volatile fatty acid (TVFA) production (P <
0.01, [82]Table 2 ). The TVFA remained higher in the 8 mg/kg group at
12, 24, and 48 h, whereas it was lower in the 4 mg/kg group at 24 and
48 h, indicating a significant interaction effect (P < 0.01).
Table 1.
Effects of 5-HTP supplementation on rumen pH, NH[3]-N concentration
(mg/dL), DMD (%, DM), and gas production (mL) in vitro.
Item Time 5-HTP group (mg/kg DM) SEM P-value
0 2 4 8 10 Dose Time D×T
pH value 3h 6.63 6.63 6.63 6.61 6.65 0.01 0.865 <0.01 0.844
6h 6.54 6.51 6.51 6.51 6.57 0.01
12h 6.37 6.39 6.38 6.40 6.31 0.02
24h 6.22 6.18 6.20 6.20 6.22 0.02
48h 6.01 6.02 6.02 6.02 6.10 0.02
NH[3]-N 3h 18.95^ab 22.04^a 22.00^a 16.27^b 14.11^b 0.89 < 0.05 <0.01
<0.01
6h 24.40^a 24.68^a 25.73^a 16.91^b 14.70^b 1.08
12h 36.06^a 33.95^a 37.73^a 34.58^a 21.13^b 1.46
24h 55.84^ab 57.79^a 48.93^b 55.83^ab 57.46^a 1.22
48h 67.42 65.06 64.91 69.04 71.67 1.23
DMD 3h 17.76 17.25 17.91 18.47 18.71 0.62 0.280 <0.01 0.353
6h 23.13^ab 25.85^a 23.25^ab 23.36^ab 20.78^b 0.60
12h 31.23 30.71 30.54 30.84 31.45 0.61
24h 37.53^ab 38.90^ab 37.65^ab 40.90^a 36.50^b 0.57
48h 49.70^a 46.63^ab 49.00^ab 47.36^ab 44.71^b 0.65
Gas production 3h 49.14 50.99 53.80 51.99 50.87 1.92 <0.05 <0.01 0.051
6h 95.10^ab 90.89^ab 106.73^a 81.96^b 87.33^ab 3.53
12h 155.69 159.31 151.40 166.33 153.44 5.22
24h 226.22^ab 234.82^ab 193.68^b 252.46^a 196.23^b 6.94
48h 291.52 288.75 280.39 317.11 276.59 7.06
[83]Open in a new tab
^a,bDifferent superscripts in the same raw implies their mean values
are significantly different (P ≤ 0.05). Where: D×T- dose and
fermentation time interaction; DMD - dry matter degradation rate.
Table 2.
Effects of 5-HTP supplementation on volatile fatty acids concentration
(mmol/L) in vitro.
Item Time 5-HTP group (mg/kg DM) SEM P-value
0 2 4 8 10 Dose Time D×T
Acetic acid 3h 19.32 19.91 19.34 21.16 20.35 0.77 <0.05 <0.01 0.731
6h 24.84 27.61 25.54 25.77 25.17 0.83
12h 32.41 32.34 32.60 39.13 35.65 1.06
24h 38.21^b 42.59^ab 38.61^b 48.93^a 46.73^ab 1.38
48h 57.50 56.18 52.09 58.24 57.28 1.47
Propionic acid 3h 8.83 9.53 10.71 9.73 8.38 0.40 0.235 <0.01 0.692
6h 12.06 13.85 13.93 12.19 11.77 0.53
12h 18.94 19.94 18.29 21.78 18.11 0.82
24h 25.21 25.21 23.94 30.45 28.59 0.96
48h 33.08 31.70 30.38 35.03 33.98 1.07
Butyric acid 3h 4.84 4.95 5.12 5.83 6.37 0.30 0.462 <0.01 0.915
6h 6.37 6.78 7.75 7.03 7.82 0.36
12h 10.09 10.25 8.93 12.37 11.01 0.57
24h 12.63 12.83 13.85 15.92 13.20 0.73
48h 17.08 18.35 21.00 17.61 17.97 0.98
TVFA 3h 35.72 37.23 40.42 39.99 39.99 1.31 <0.01 <0.01 <0.01
6h 46.97 51.06 59.70 49.67 50.45 1.98
12h 67.16 66.90 65.98 75.97 68.19 2.07
24h 84.80^b 85.32^b 70.76^c 100.45^a 99.80^a 2.36
48h 121.37^a 117.91^a 99.64^b 128.36^a 123.21^a 2.99
A/P 3h 2.46 2.25 2.11 2.37 2.78 0.15 0.137 <0.01 0.962
6h 2.26 2.09 1.95 2.40 2.77 0.14
12h 1.93 1.71 1.82 2.26 2.11 0.11
24h 1.57 1.72 1.58 1.74 1.75 0.06
48h 1.81 1.71 1.71 1.77 1.83 0.05
[84]Open in a new tab
^a,bDifferent superscripts in the same raw implies their mean values
are significantly different (P ≤ 0.05).Where: D×T- dose and
fermentation time interaction; TVFA- Total volatile fatty acids; A/P-
acetic to propionic acid ratio.
3.2. Rumen microbial community composition in vitro
An average of 40,591 high-quality sequences per sample was obtained
from the 1,786,014 valid sequences. 5-HTP significantly altered the
relative abundances of Bacteroidetes, Firmicutes, Proteobacteria,
Actinobacteria, and Verrucomicrobia (P < 0.01; [85]Supplementary Table
S2 ). This interaction had a greater impact on the abundances of
Bacteroidetes, Firmicutes (P < 0.01), and Verrucomicrobia (P < 0.05).
Proteobacteria in the high-dose groups (8 mg/kg and 10 mg/kg) were more
abundant at 12 and 48 h (P < 0.05, [86]Figure 1A ). Prevotella,
Succinivibrio, Selenomonas, and Succiniclasticum were the predominant
genera ([87] Supplementary Table S2 ). 5-HTP significantly affected the
relative abundance of the Butyrivibrio genus (P < 0.05). The
interaction effects also had a significant impact on the relative
abundances of Succiniclasticum and Sharpea (P < 0.01). Additionally,
the low-dose 5-HTP groups (2 mg/kg and 4 mg/kg) were able to decrease
the abundance of Vibrio succinogenes, whereas the high-dose 5-HTP
groups (8 mg/kg and 10 mg/kg) were able to increase their abundance.
Figure 1.
[88]Figure 1
[89]Open in a new tab
Ruminal bacteria phyla abundance (A) and alpha diversity indices (B)
under 5-HTP supplementation at different fermentation times in vitro.
* indicates a significant difference in mean between groups (P < 0.05).
3.3. Rumen bacteria alpha diversity in vitro
Different doses of 5-HTP significantly affected the Chao1, Shannon, and
Simpson indices at various fermentation times (P < 0.05, [90]Figure 1B
).
3.4. Beta diversity of rumen microbial communities in vitro
In the beta diversity cluster analysis, the abundance of the dominant
genus, Prevotella, was similar in the low-dose 5-HTP groups (2 mg/kg
and 4 mg/kg) at 12 h ([91] Figure 2A ). Additionally, its abundance was
similar in the high-dose 5-HTP groups (8 mg/kg and 10 mg/kg) at 12 h.
However, the abundance of Succinivibrio in the high-dose 5-HTP groups
(8 mg/kg and 10 mg/kg) was significantly higher at 12 h. Furthermore,
at 12 h, the amount of Prevotella in the high-dose 5-HTP groups (8
mg/kg and 10 mg/kg) was lower than that in the low-dose 5-HTP groups (2
mg/kg and 4 mg/kg), indicating that the high-dose 5-HTP groups (8 mg/kg
and 10 mg/kg) increased the amount of Succinivibrio and reduced the
amount of Prevotella. At 48 h, the high-dose 5-HTP groups (8 mg/kg and
10 mg/kg) showed significantly increased Succinivibrio abundance,
suggesting that the addition of 5-HTP successfully increased
Succinivibrio abundance ([92] Figure 2B ).
Figure 2.
[93]Figure 2
[94]Open in a new tab
Hierarchical clustering analysis of bacterial genera at 12 (A) and 48 h
(B), metabolic pathway statistics (C) under 5-HTP supplementation at
different fermentation times in vitro.
3.5. Rumen microbial metabolic pathway analysis in vitro
The KEGG enrichment pathways of 5-HTP supplementation, which mimicked
rumen fermentation microorganisms in vitro are shown in [95]Figure 2C .
These pathways fall into seven level-1 categories: biosynthesis,
degradation/utilization/absorption, disinfection, precursor metabolites
and energy production, glycan pathways, polymer modifications, and
metabolic clusters. Among these, the biosynthetic pathway was the
dominant metabolic pathway.
3.6. Rumen metabolite in vitro
The OPLS-DA model was used to compare and analyze rumen metabolites,
and its suitability was evaluated through a permutation test. As
indicated in [96]Figures 3A, C, E, G , 5-HTP had distinct effects on
rumen metabolites compared with the 0 mg/kg 5-HTP group at 12 h.
Similarly, at 48 h, there was a significant disparity between the
groups ([97] Figures 3I, K, M, O ). These results collectively suggest
that 5-HTP has significant effects on rumen metabolites. Furthermore,
the 200 permutation test models in each group did not overfit,
confirming the reliability of the models and experimental results ([98]
Figures 3B, D, F, H, J, L, N, P ).
Figure 3.
[99]Figure 3
[100]Open in a new tab
OPLS-DA score and permutations of metabolites under 5-HTP
supplementation at different fermentation times in vitro (A) OPLS-DA
score between A12.0T and A12.2T; (B) Permutations between A12.0T and
A12.2T; (C) OPLS-DA score between A12.0T and A12.4T; (D) Permutations
between A12.0T and A12.4T; (E) OPLS-DA score between A12.0T and A12.8T;
(F) Permutations between A12.0T and A12.8T; (G) OPLS-DA score between
A12.0T and A12.10T; (H) Permutations between A12.0T and A12.10T; (I)
OPLS-DA score between A48.0T and A48.2T; (J) Permutations between
A48.0T and A48.2T; (K) OPLS-DA score between A48.0T and A48.4T; (L)
Permutations between A48.0T and A48.4T; (M) OPLS-DA score between
A48.0T and A48.8T; (N) Permutations between A48.0T and A48.8T; (O)
OPLS-DA score between A48.0T and A48.10T; (P) Permutations between
A48.0T and A48.10T) A total of 10 sets of experiments, each group of 6
parallel samples, the total number of samples n=60.) Among them,
A12.0T, A12.2T, A12.4T, A12.8T, and A12.10T indicated fermentation for
12 h, and 0, 2, 4, 8, and 10 mg/kg 5-HTP additives were added,
respectively. A48.0T, A48.2T, A48.4T, A48.8T, and A48.10T indicated
fermentation for 48 h, and 0, 2, 4, 8, and 10 mg/kg 5-HTP additives
were added, respectively.
3.7. Differential metabolites screening and analysis in vitro
Differential metabolites were identified using the OPLS-DA model and
screened based on variable importance projection (VIP) values > 1 and P
< 0.05. [101]Supplementary Table S3 presents details on the
differential metabolites identified in each group. We identified
significant differences in metabolites using volcano plots ([102]
Figure 4 ). Red represents significantly upregulated metabolites, blue
represents significantly downregulated metabolites, and gray represents
no significant differences. The colors distinguish the level of
metabolite richness within a row, with red denoting high metabolite
richness and blue denoting low metabolite richness. A total of seven
differential metabolites were identified between A12.0T and A12.2T.
Among these, 4’, 7-dihydroxy flavanone 1, tetracosanoic acid and
hexadecane contents were higher in rumen fluid metabolites supplemented
with 2 mg/kg 5-HTP group ([103] Figure 5A ). The A12.0T and A12.4T
groups had 32 distinct metabolites (P < 0.05) ([104] Figure 5B ). Of
these, octanal 2 and 3-hydroxy pyruvate were lower in rumen fluid
metabolites with 4 mg/kg 5-HTP, whereas other metabolite amounts were
higher. Between the A12.0T and A12.8T groups, 29 different metabolites
(P < 0.05) were selected ([105] Figure 5C ). The 0 mg/kg 5-HTP group
contained high amounts of octanal 2, 3-hydroxy pyruvate, and
methylmalonic acid. A total of 27 unique metabolites (P < 0.05) were
selected between the A12.0 T and A12.10 T groups, most of them
abundantly present in rumen fluid supplemented with 10 mg/kg 5-HTP
([106] Figure 5D ). Seven differential metabolites were identified in
the A48.0T and A48.2T groups ([107] Figure 5E ). These seven
differential metabolites were present in lower amounts in the 2 mg/kg
5-HTP supplemented group after 48 h (P < 0.05). In the A48.0T and
A12.4T groups, 33 differential metabolites (P < 0.05) were identified
([108] Figure 5F ). Specifically, 1-methyl hydantoin 1;
1,3-cyclohexanedione 1; and lipoic acid were more abundant in the 4
mg/kg 5-HTP group. Twenty-seven differential metabolites were
identified in the A48.0T and A48.8T groups ([109] Figure 5G ). Among
these, 2-oxovaleric acid, panthenol 2, lipoic acid, and 3-hexanedioic
acid were highly abundant in the 8 mg/kg 5-HTP group. In total, 27
differential metabolites (P < 0.05) were identified between A48.0T and
A48.10T groups ([110] Figure 5H ). Among these, metabolites such as
2-hexanoic acid, N-acetyl-L-leucine 1, and N, N-dimethylarginine were
found to be low in the 0 mg/kg 5-HTP group, whereas the other
metabolites were low in the 10 mg/kg 5-HTP group. These results
indicated that different doses of 5-HTP led to significant changes in
rumen metabolite content. Further analysis, based on a fold difference
of more than 2 or less than 0.5 and a P-value of less than 0.01,
revealed 15 different metabolites, including three alcohols, nine
organic acids, one carbohydrate, one nucleoside, and one aldehyde. In
the high-dose 5-HTP groups (8 mg/kg and 10 mg/kg), three differential
metabolites: uridine 2, lignoceric acid, and N-methyltryptophan were
identified, while the low-dose 5-HTP groups (2 mg/kg and 4 mg/kg)
showed 6 separate metabolites, including panthenol 2, lipoic acid,
β-sitosterol, gluconic acid, N,N-dimethylarginine, and
cholesterol-2,2,3,4,4,6-d6. Norvaline, cycloleucine 2, octanal 2, and
methylmalonic acid were the four common differential metabolites of
5-HTP in both the low- and high-dose groups.
Figure 4.
[111]Figure 4
[112]Open in a new tab
Volcano plot of differential metabolites under 5-HTP supplementation at
different fermentation times in vitro (A) A12.0T and A12.2T intergroup
volcanoes; B: A12.0T and A12.4T intergroup volcanoes; (C) A12.0T and
A12.8T intergroup volcanoes; (D) A12.0T and A12.10T intergroup
volcanoes; (E) A48.0T and A48.2T intergroup volcanoes; (F) A48.0T and
A48.4T intergroup volcanoes; (G) A48.0T and A48.8T intergroup volcano
plot; (H) A48.0T and A48.10T intergroup volcano plot).
Figure 5.
[113]Figure 5
[114]Open in a new tab
Heatmap analysis of differential metabolites under 5-HTP
supplementation at different fermentation times in vitro (A) heat map
of differential metabolites between A12.0T and A12.2T; B: A12.0T and
A12.4T; (C) A12.0T and A12.8T; (D) A12.0T and A12.10T; (E) A48.0T and
A48.2T; (F) A48.0T and A48.4T; (G) A48.0T and A48.8T; (H) A48.0T and
A48.10T). A total of 10 sets of experiments, each group of 6 parallel
samples, the total number of samples n = 60. Among them, A12.0T,
A12.2T, A12.4T, A12.8T, and A12.10T indicated fermentation for 12 h,
and 0, 2, 4, 8, and 10 mg/kg 5-HTP supplemented, respectively. A48.0T,
A48.2T, A48.4T, A48.8T, and A48.10T indicated fermentation for 48 h,
and 0, 2, 4, 8 and 10 mg/kg 5-HTP supplemented, respectively.
3.8. Differential metabolite pathway enrichment analysis in vitro
Differential metabolites were analyzed using KEGG metabolic pathway
analysis ([115] Figure 6 ; [116]Supplementary Table S4 ). A total of 87
metabolic pathways were enriched, and 36 metabolites were annotated.
[117]Figure 6A indicated 9 metabolic pathways that were rich in
different metabolites between the A12.0T and A12.2T groups.
[118]Figure 6B shows that 20 metabolic pathways were mainly enriched
for differential metabolites between the A12.0T and A12.4T groups, with
11 annotated metabolites involving multiple pathways. Twenty metabolic
pathways, mainly enriched in differential metabolites between the
A12.0T and A12.8T groups are shown in [119]Figure 6C , involving 12
annotated metabolites of multiple pathways. [120]Figure 6D shows that
19 metabolic pathways were enriched in the differential metabolites
between the A12.0T and A12.10T groups. [121]Figure 6E shows 4 metabolic
pathways that were primarily enriched in the differential metabolites
between the A48.0T and A48.2T groups, with two annotated metabolites
involved in multiple pathways. As shown in [122]Figure 6F , 17
metabolic pathways were enriched in the differential metabolites
between the A48.0T and A48.4T groups, with six annotated metabolites
involving multiple pathways. [123]Figure 6G shows 20 metabolic pathways
that were mainly enriched in differential metabolites between the
A48.0T and A48.8T groups, with nine annotated metabolites involving
multiple pathways. Finally, [124]Figure 6H shows 20 metabolic pathways,
mostly composed of different metabolites between the A48.0T and A48.10T
groups, and nine annotated metabolites involved in multiple pathways.
Figure 6.
[125]Figure 6
[126]Open in a new tab
Differential metabolite KEGG enrichment analysis under 5-HTP
supplementation at different fermentation times in vitro (A) A12.0T and
A12.2T differential metabolite pathway enrichment plot; (B) A12.0T and
A12.4T; (C) A12.0T and A12.8T; (D) A12.0T and A12.10T group; (E) A48.0T
and A48.2T group; (F) A48.0T and A48.4T groups; (G) A48.0T and A48.8T
groups; (H) A48.0T and A48.10T groups). A total of 10 sets of
experiments, each group of 6 parallel samples, the total number of
samples n = 60.) Among them, A12.0T, A12.2T, A12.4T, A12.8T and A12.10T
indicated fermentation for 12 h, and 0, 2, 4, 8 and 10 mg/kg 5-HTP
supplemented, respectively. A48.0T, A48.2T, A48.4T, A48.8T, and A48.10T
indicated fermentation for 48 h, and 0, 2, 4, 8 and 10 mg/kg 5-HTP
supplemented, respectively.
The low-dose 5-HTP groups (2 mg/kg and 4 mg/kg) were screened for two
metabolic pathways: chemical carcinogenesis receptor activation and
pyrimidine metabolism. In the high-dose 5-HTP groups (8 mg/kg and 10
mg/kg), 9 metabolic pathways were screened, including biosynthesis of
unsaturated fatty acids, methane metabolism, cutin, suberin, wax
biosynthesis, carbon metabolism, glyoxylate and dicarboxylate
metabolism, microbial metabolism in different environments, propionate
metabolism, starch and sucrose metabolism, and the phosphotransferase
system (starch and sucrose metabolism).
3.9. Rumen metabolite panel and microbial correlation analysis in vitro
Pearson’s correlation coefficients and correlation heat maps were used
to examine the relationships between various metabolites and bacterial
genera ([127] Figure 7A ). The results showed positive correlations
between different metabolites and bacterial genera, including
2’-deoxyadenosine with Prevotella, 1-hydroxy-2-naphthoic acid, with
Succinivibrio, Selenomonas with Ruminococcus, Succiniclasticum with
Oscillospira, 1-monopalmitin with Butyrivibrio, and Sharpea,
1-hydroxylamine, 2-methylnaphthyl acid, and 1-monopalmitin.
Additionally, there was a positive correlation between
3-cyclohexanedione 1, 2,3-Dihydroxypyridine, and 1-methylhydantoin1,
while 2-butyne-1,4-diol positively correlated with 1,3-cyclohexanedione
1, 1-methylhydantoin1, and 2,3-dihydroxypyridine. Despite these
correlations, most differentially expressed metabolites were negatively
correlated with the Prevotella genus.
Figure 7.
[128]Figure 7
[129]Open in a new tab
Rumen differential metabolite correlated heat map with bacteria at
genus-level (A) and Spearman-related heat map of rumen differential
metabolites and ASV (B) under 5-HTP supplementation at different
fermentation times in vitro. The abscissa represents the differential
metabolite, the ordinate represents the relative abundance of ASV of
top 30 (the left side represents the species with the highest
classification of this ASV), the “*” and “**” signs in the square
represent the P ≤ 0.05, and P ≤ 0.01, respectively.
Spearman’s correlation coefficient was used to investigate the
relationship between differential rumen metabolites and their
correlation with ASV ([130] Figure 7B ). This analysis sought to
comprehend the interaction between metabolites and microorganisms,
specifically focusing on the impact of metabolites on bacterial
composition and the mechanism of changes in flora in complex diseases.
Correlation coefficients were computed based on the top 30 bacteria and
differential metabolites in relation to the relative abundance of ASV
using the psych package in R. The findings revealed a positive
correlation between rumen differential metabolites and ASV and vice
versa.
3.10. Growth performance of sheep
[131]Table 3 shows the effects of 5-HTP on body weight, average daily
gain (ADG), and DMI. The 5-HTP group consumed 0.01 kg more dry matter
than the control group during days 0-60 (P > 0.05). On day 30, the
sheep in the 5-HTP group weighed 2.4 kg more on average compared to the
control group (P < 0.05). In the 60-day experiment, the 5-HTP group
gained an average of 17.7 kg, slightly more than the control group’s
16.5 kg. The 5-HTP group consistently had higher daily weight gain
values at each stage, but the differences were not statistically
significant (P > 0.05).
Table 3.
Effects of 5-HTP on dry matter intake, body weight gain, and average
daily gain in sheep.
Item Days Control 5-HTP group t P-value
Dry matter intake (kg/d) 0 1.09 ± 0.01 1.10 ± 0.00 1.00 0.37
15 1.37 ± 0.01 1.38 ± 0.00 1.00 0.37
30 1.61 ± 0.01 1.63 ± 0.00 1.16 0.30
45 1.9 ± 0.00 1.9 ± 0.00 0.00 1.00
60 1.45 ± 0.01 1.46 ± 0.00 1.00 0.19
Body weight (kg) 0 19.50 ± 0.63 20.70 ± 0.46 -1.53 0.17
15 23.6 ± 0.64 25.00 ± 0.35 1.91 0.09
30 27.7 ± 0.64^b 30.10 ± 0.51^a 2.92 <0.05
45 32.1 ± 1.01 33.70 ± 0.56 1.34 0.22
60 36 ± 1.00 38.40 ± 1.16 1.57 0.16
Average daily gain (kg/d) 0-15 0.27 ± 0.01 0.29 ± 0.01 -0.89 0.40
15-30 0.27 ± 0.03 0.34 ± 0.02 -2.02 0.08
30-45 0.29 ± 0.04 0.24 ± 0.01 1.17 0.28
45-60 0.26 ± 0.02 0.31 ± 0.04 -1.10 0.30
0-60 0.28 ± 0.01 0.30 ± 0.01 1.60 0.15
Total body weight gain (kg) 60 16.5 ± 0.45 17.70 ± 0.8 -1.31 0.23
[132]Open in a new tab
^a,bDifferent superscripts in the same raw implies their mean values
are significantly different (P ≤ 0.05).
3.11. Sheep blood indices
[133]Table 4 shows that the plasma INS level in the 5-HTP group was
higher than that in the control at 60 days (P < 0.05). There were no
significant differences in the T-AOC, MDA, SOD, GSH-PX, or CAT between
the two groups (P > 0.05). The control group showed significantly
higher total protein levels on days 15, 30, 45 (P < 0.05), and 60 (P <
0.01). On day 15, the 5-HTP group showed significantly higher albumin
levels (P < 0.05). Globulin levels were higher in the control group on
days 15, 30 (P < 0.05), and 60 (P < 0.01). Low-density lipoprotein
levels were higher in the control group on day 30 (P < 0.05). On day
15, the urea concentration in the 5-HTP group was higher than that in
the control group (P < 0.05, [134]Table 5 ).
Table 4.
Effects of 5-HTP on blood antioxidant levels in sheep.
Item Day Control group 5-HTP group t P-value
Antioxidant indices
T-AOC (U/mL) 0 7.86 ± 0.31 7.68 ± 0.21 0.47 0.65
15 8.53 ± 0.31 8.31 ± 0.12 0.68 0.52
30 9.13 ± 0.25 9.66 ± 0.21 -1.64 0.14
45 10.59 ± 0.49 10.89 ± 0.49 -0.44 0.67
60 10.50 ± 0.48 10.06 ± 0.85 0.45 0.66
MDA (nmol/mL) 0 6.50 ± 0.45 6.42 ± 0.18 0.17 0.87
15 5.21 ± 0.14 5.16 ± 0.30 0.162 0.88
30 3.83 ± 0.29 4.68 ± 0.37 -1.78 0.11
45 3.12 ± 0.37 2.90 ± 0.27 0.49 0.63
60 3.27 ± 0.11 3.76 ± 0.31 -1.52 0.19
SOD (U/mL) 0 44.63 ± 4.50 46.34 ± 2.58 -0.33 0.75
15 53.94 ± 3.40 51.41 ± 1.88 0.65 0.53
30 61.75 ± 1.74 61.17 ± 0.45 0.32 0.76
45 76.27 ± 2.69 68.53 ± 7.01 1.03 0.33
60 68.26 ± 2.06 64.17 ± 3.08 1.10 0.30
GSH-PX (U/mL) 0 281.83 ± 15.62 322.98 ± 21.39 -1.55 0.16
15 330.79 ± 22.15 329.52 ± 22.86 0.04 0.97
30 382.69 ± 30.58 422.76 ± 23.16 -1.05 0.33
45 500.60 ± 15.85 525.67 ± 20.16 -0.98 0.36
60 426.99 ± 7.08 468.10 ± 17.88 -2.14 0.07
CAT (U/mL) 0 29.71 ± 1.23 31.63 ± 1.27 -1.09 0.31
15 31.82 ± 1.88 34.32 ± 1.79 -0.97 0.36
30 36.69 ± 1.09 36.16 ± 0.35 0.47 0.66
45 46.89 ± 4.61 52.95 ± 7.40 -0.70 0.51
60 39.42 ± 1.81 42.00 ± 2.37 -0.87 0.41
Blood hormone
INS (μIU/mL) 0 13.86 ± 0.20 14.67 ± 0.50 -1.39 0.20
15 13.66 ± 0.56 13.14 ± 0.31 0.80 0.45
30 12.08 ± 0.71 13.88 ± 1.15 -1.32 0.22
45 16.16 ± 0.85 15.51 ± 0.61 0.62 0.56
60 12.35 ± 0.35^b 15.59 ± 1.06^a -2.90 <0.05
GH (ng/mL) 0 4.40 ± 0.19 4.41 ± 0.26 0.02 0.98
15 4.59 ± 0.16 5.55 ± 0.59 1.56 0.16
30 5.61 ± 0.32 5.78 ± 0.29 0.41 0.69
45 6.81 ± 0.56 7.54 ± 0.34 1.13 0.29
60 6.22 ± 0.24 6.71 ± 0.28 1.33 0.22
[135]Open in a new tab
^a,bDifferent superscripts in the same raw implies their mean values
are significantly different (P ≤ 0.05). T-AOC, total antioxidant
capacity; MDA, malondialdehyde; SOD, superoxide dismutase; GSH-PX,
glutathione peroxidase; CAT, catalase; INS, insulin; GH, growth
hormone.
Table 5.
Effects of 5-HTP on blood biochemical indices in sheep.
Item Day Control group 5-HTP group t P-value
TP (g/L) 0 64.60 ± 1.57 71.36 ± 2.69 -2.17 0.06
15 76.00 ± 2.06^a 67.87 ± 1.86^b 2.93 <0.05
30 80.13 ± 3.16^a 64.38 ± 4.45^b 2.89 <0.05
45 90.36 ± 4.47^a 76.87 ± 1.85^b 2.79 <0.05
60 76.80 ± 1.34^A 65.05 ± 2.04^B 4.81 <0.01
ALB (g/L) 0 24.01 ± 1.91 25.02 ± 1.01 -0.47 0.65
15 24.91 ± 1.37^b 27.19 ± 0.82^a 2.93 <0.05
30 26.66 ± 1.22 26.15 ± 1.11 0.31 0.76
45 26.80 ± 1.50 24.57 ± 1.91 0.92 0.39
60 26.90 ± 2.09 30.15 ± 0.66 -1.49 0.18
GLB (g/L) 0 40.60 ± 1.98 46.34 ± 3.17 -1.54 0.16
15 51.09 ± 2.49^a 40.67 ± 1.32^b 3.69 <0.05
30 53.47 ± 2.30^a 38.23 ± 4.59^b 2.97 <0.05
45 63.57 ± 4.12 52.30 ± 3.44 2.10 0.07
60 49.90 ± 1.80^A 34.90 ± 2.44^B 4.95 <0.01
TC (mmol/L) 0 1.26 ± 0.21 0.96 ± 0.92 1.29 0.23
15 1.05 ± 0.15 1.14 ± 0.13 -0.45 0.66
30 1.30 ± 0.09 1.20 ± 0.07 0.82 0.44
45 1.80 ± 0.31 1.12 ± 0.41 1.31 0.23
60 1.49 ± 0.08 1.42 ± 0.14 0.39 0.71
TG (mmol/L) 0 0.35 ± 0.01 0.33 ± 0.04 0.28 0.79
15 0.38 ± 0.07 0.32 ± 0.05 0.77 0.47
30 0.37 ± 0.05 0.22 ± 0.04 2.36 0.05
45 0.82 ± 0.09 0.50 ± 0.15 1.80 0.11
60 0.37 ± 0.03 0.39 ± 0.06 -0.27 0.79
HDL (mmol/L) 0 0.71 ± 0.13 0.60 ± 0.09 0.71 0.50
15 0.62 ± 0.07 0.67 ± 0.05 -0.53 0.61
30 0.71 ± 0.04 0.61 ± 0.06 1.31 0.23
45 0.96 ± 0.05 0.85 ± 0.09 1.08 0.31
60 0.84 ± 0.06 0.68 ± 0.06 1.81 0.12
LDL (mmol/L) 0 0.30 ± 0.07 0.33 ± 0.03 -0.36 0.73
15 0.77 ± 0.19 0.62 ± 0.11 0.68 0.52
30 0.82 ± 0.06^a 0.61 ± 0.03^b 3.50 <0.05
45 1.00 ± 0.10 0.87 ± 0.04 1.14 0.30
60 0.56 ± 0.04 0.64 ± 0.12 -0.62 0.56
GLU (mmol/L) 0 3.85 ± 0.37 3.28 ± 0.18 1.39 0.22
15 3.02 ± 0.35 3.49 ± 0.22 -1.13 0.29
30 3.25 ± 0.24 3.22 ± 0.14 0.11 0.92
45 4.18 ± 0.35 4.00 ± 0.15 0.45 0.67
60 5.19 ± 0.10 4.18 ± 0.41 2.39 0.07
UREA (mmol/L) 0 6.39 ± 0.52 4.92 ± 0.55 1.93 0.09
15 3.05 ± 0.31^b 4.85 ± 0.43^a -3.39 <0.05
30 4.05 ± 0.76 4.01 ± 0.53 0.05 0.97
45 4.33 ± 0.69 5.55 ± 0.79 -1.16 0.28
60 6.54 ± 1.04 4.05 ± 0.32 2.28 0.05
NEFA (mmol/L) 0 0.09 ± 0.01 0.15 ± 0.03 -1.98 0.08
15 0.11 ± 0.04 0.11 ± 0.01 0.09 0.93
30 0.19 ± 0.03 0.14 ± 0.04 0.88 0.40
45 0.59 ± 0.09 0.46 ± 0.12 0.90 0.40
60 0.16 ± 0.07 0.27 ± 0.06 -1.16 0.30
[136]Open in a new tab
^a,bDifferent superscripts in the same raw implies their mean values
are significantly different (P ≤ 0.05). ^A,BDifferent superscripts in
the same raw implies their mean values are significantly different (P ≤
0.01). TP, total protein; ALB, albumin; GLB, globulin; TC, total
cholesterol; TG, triglyceride; HDL, high-density lipoprotein; LDL,
low-density lipoprotein; GLU, glucose; NEFA, non-esterified fatty
acids.
3.12. Blood 5-HTP, 5-HT, MT content in sheep
[137]Table 6 shows the initial increase and subsequent decline in the
blood levels of 5-HTP, 5-HT, and MT. The concentrations increased
slowly during the first 15 days, peaked in both groups on the 45^th
day, and then decreased on the 60^th day. There were no significant
differences in the concentration of 5-HTP, 5-HT, or MT between the two
groups (P > 0.05). However, the levels of 5-HTP and 5-HT were higher in
the 5-HTP group compared to the control group on days 15, 30, and 60.
Additionally, sheep supplemented with 8 mg/kg 5-HTP showed higher MT
levels on days 15-60 compared to the control group.
Table 6.
Effects of 5-HTP on blood 5-HTP, 5-HT, MT content in sheep.
Item Day Control group 5-HTP group t P-value
5-HTP (ng/mL) 0d 166.99 ± 10.81 156.64 ± 6.73 0.81 0.44
15d 165.05 ± 4.17 172.09 ± 4.95 -1.09 0.31
30d 208.82 ± 5.02 211.74 ± 4.74 -0.42 0.68
45d 254.25 ± 13.62 252.55 ± 11.31 0.10 0.93
60d 243.41 ± 11.79 249.04 ± 8.07 -0.39 0.70
5-HT (ng/mL) 0d 115.98 ± 6.43 113.31 ± 2.30 0.39 0.71
15d 114.23 ± 4.10 114.90 ± 3.51 -0.12 0.90
30d 128.14 ± 3.62 132.84 ± 14.94 -0.31 0.77
45d 197.28 ± 7.68 196.58 ± 5.80 0.07 0.94
60d 172.88 ± 10.41 181.87 ± 4.21 -0.80 0.45
MT (pg/mL) 0d 33.92 ± 1.36 32.78 ± 1.88 0.49 0.64
15d 39.43 ± 2.39 40.63 ± 1.55 -0.42 0.69
30d 41.71 ± 1.37 42.70 ± 0.63 -0.66 0.54
45d 48.92 ± 1.80 53.05 ± 3.15 -1.14 0.29
60d 43.39 ± 2.93 47.67 ± 1.87 -1.23 0.25
[138]Open in a new tab
5-HTTP, hydroxytryptophan; 5-HT, hydroxytryptamine; MT, melatonin.
3.13. Blood metabolites in sheep
The samples were classified and identified using an orthogonal partial
least-squares discriminant analysis (OPLS-DA) model. The scatter plot
of the OPLS-DA score for each sample indicates that the comparison
between the two groups was highly significant. All samples fell within
the 95% confidence interval and there were noticeable differences among
the four groups (A30 vs. A0, A60 vs. A0, A30 vs. B30, and A60 vs. B60)
based on the scores of the main components shown in [139]Figures 8A, C,
E, G . Differences among the groups were also observed based on the
score of the orthogonal component on the ordinate (t [1]) o) ([140]
Figures 8B, D, F, H ). To assess overfitting, a permutation test was
conducted on the sequencing data of the OPLS-DA model. The results of
the 200 substitution test models in each group indicated no
overfitting, suggesting that the above models and experimental results
were accurate.
Figure 8.
[141]Figure 8
[142]Open in a new tab
OPLS-DA score and replacement test plot of blood metabolite in sheep
(A) OPLS-DA score plot between A0 and A30 groups; (B) Test chart of
intergroup displacement between A0 and A30; (C) OPLS-DA score plot
between A0 and A60 groups; (D) A0 and A60 intergroup displacement test
chart; (E) OPLS-DA score plot between A30 and B30 groups; (F) A30 and
B30 intergroup displacement test chart; (G) OPLS-DA score plot between
A60 and B60 groups; (H) A60 and B60 intergroup displacement test
chart); volcanic plot of differential metabolite screening of sheep
blood (I) A0 and A30 intergroup volcanic plot; (J) A0 and A60
intergroup volcano map; (K) A30 and B30 inter-group volcano map; (L)
A60 and B60 inter-group volcano map) and Horizontal clustering plot of
differential metabolites in sheep (M) A0 and A30 hierarchical
clustering plot; (N) A0 and A60 groups; (O) A30 and B30; (P) A60 and
B60).
3.14. Screening and analysis of significant differential metabolites in sheep
The OPLS-DA model used multivariate analysis to combine variable
importance projection (VIP) values > 1 with Student’s t-test (P < 0.05)
for each metabolite between two groups to initially screen for
differential metabolites ([143]27). Therefore, 84, 94, 66, and 20
differential metabolites were screened for the A0 and A30, A0 and A60,
A30 and B30, and A60 and B60 treatments, respectively. Volcano plots
displayed various metabolites, with red indicating significant
upregulation, blue indicating significant downregulation, and gray
indicating no significant differences ([144] Figures 8I, J, K, L ).
Hierarchical clustering analysis presented in a clustered heatmap
revealed significant differential metabolites in the blood, with red
representing high metabolite richness and blue representing low
metabolite richness. The 5-HTP group exhibited higher levels of
nutritional cholic acid, flavonol A, and 5-HEPE than the control group
([145] Figure 8M ). Additionally, the abundance of trimethylamine
N-oxide, 3-hydroxyisovalylcarnitine, and fragransol B in the 5-HTP
group was higher than that in the control group ([146] Figure 8N ).
Furthermore, the abundance of 3-indadiene, acetonitrile, L-valine, and
L-norleucine in the 5-HTP group was higher ([147] Figure 8O ). Finally,
the levels of the differential metabolites (R-Pelletierine,
homoarecoline, L-Methionine, creatinine, and hydroxyprolyl-leucine)
between A60 and B60 were higher in the 5-HTP group than in the control
group ([148] Figure 8P ).
3.15. Significant differential metabolite pathway enrichment analysis in
sheep
We used the KEGG pathway database ([149]28, [150]29) (Figure
[151]www.kegg.jp/kegg/pathway.html) to annotate the differential
metabolites for corresponding metabolic pathways. Differential
metabolite pathway analysis maps of the different groups have been
presented in [152]Figures 9A–D . There were significant differences in
the metabolites between the A0 and A30 groups, resulting in 18 KEGG
functional clusters at the secondary functional classification level.
The dominant clusters were the digestive system and amino acid
metabolites. Twenty-two KEGG functional clusters were obtained between
the A0 and A60 groups, with a cancer overview and dominant amino acid
metabolism. A total of 24 KEGG functional clusters were obtained
between the A30 and B30 groups, with dominant amino acid metabolism.
Thirteen KEGG functional clusters with dominant amino acid metabolism
and an overview of cancer were obtained between the A60 and B60 groups.
Global and overview maps of the KEGG secondary pathways were dominant
among all four pairs of groups. Further metabolic pathway analysis is
needed to identify critical pathways with strong connections to
metabolite differences, as KEGG annotation analysis only identifies
pathways involving all differential metabolites ([153]30). As shown in
[154]Figure 9 , there were significantly different metabolites between
groups A0 and A30 ([155] Figure 9E ), which were mainly enriched in the
cofactor biosynthesis, tryptophan amino acid metabolism, amino acid
synthesis, and plant secondary metabolite synthesis pathways.
Significantly differential metabolites between the A0 and A60 groups
([156] Figure 9F ) were mainly enriched in the biosynthesis of amino
acids, protein digestion and absorption, mineral absorption, and
cofactor biosynthesis in cancer. Protein digestion and absorption,
amino acid biosynthesis, plant secondary metabolite production, and
mineral absorption were the key areas with significantly different
metabolites between the A30 and B30 groups ([157] Figure 9G ).
Significantly different metabolites in the A60 and B60 groups ([158]
Figure 9H ) were mainly enriched for aminoacyl-tRNA biosynthesis,
mineral absorption, 2-oxocarboxylic acid metabolism, and protein
digestion.
Figure 9.
[159]Figure 9
[160]Open in a new tab
KEGG enrichment analysis of blood metabolite in sheep (A) A0 and A30
intergroup pathway type analysis diagram; (B) Analysis of pathway types
between A0 and A60 groups; (C) A30 and B30; (D) between A60 and B60)
and KEGG enrichment analysis plot of different compounds between
different groups € KEGG enrichment analysis plot between A0 and A30
groups; (F) A0 and A60 groups; (G) A30 and B30 groups; (H) A60 and B60
groups).
4. Discussion
4.1. Effects of 5-HTP supplementation on rumen fermentation parameters in
vitro
The rumen pH remained within the normal range of 6.0 to 6.8. The
addition of 5-HTP did not cause a significant change in the pH level (P
> 0.05). However, the pH levels decreased in both groups as
fermentation progressed, likely due to carbohydrate fermentation by
microorganisms. This is consistent with the finding that VFA
accumulation in fermentation flasks leads to a decrease in pH
([161]31). The optimal level of NH[3]-N for microbial growth is between
0.35-29 mg/dL ([162]32), with higher concentrations beneficial for
cellulolytic bacteria growth and DM degradation. In our study, the
NH[3]-N concentrations ranged from 14.11 to 71.67 mg/dL, with a
significant increase (P < 0.05) after 12 h. As fermentation time
increased, the pH of the rumen fluid decreased, hindering the growth of
structural carbohydrate-decomposing bacteria and increasing the
production of NH[3]-N. The pH decrease was significantly influenced by
the 5-HTP dose (P < 0.05) and the interaction (P < 0.01). The low-dose
5-HTP groups (2 mg/kg and 4 mg/kg) had higher NH[3]-N concentrations
before 24 h, whereas the high-dose groups (8 mg/kg and 10 mg/kg) had
higher concentrations after 24 h. Rumen microorganisms ferment
carbohydrates to produce acetic, propionic, and butyric acids,
providing 70-80% of the energy needs and 95% of the total fatty acid
content of ruminants ([163]33). In our study, acetic acid was the
primary component that dominated the TVFA content. Both acetic and
propionic acids exhibited similar trends, with higher acid production
in the high-dose groups (8 mg/kg and 10 mg/kg). This is consistent with
the observed decrease in pH and increase in NH[3]-N concentration. High
doses of 5-HTP (8 mg/kg and 10 mg/kg) can enhance in vitro VFA
fermentation and improve rumen fermentation efficiency. Specifically,
the 8 mg/kg group had higher levels of TVFA, propionic acid, and acetic
acid compared to the 10 mg/kg group. The DMD rate is also an important
metric for evaluating feed value, reflecting the digestion ability of
ruminants ([164]34). The group that received 8 mg/kg of 5-HTP showed a
higher DMD rate at 24 h, indicating increased microbial activity and
improved fermentation. Ruminants produce a significant amount of gas
during feed fermentation by rumen microorganisms, which reflects the
fermentation status of the feed ([165]35). Our study found that 5-HTP
had a significant effect on gas production (P < 0.05). The group that
received 8 mg/kg of 5-HTP showed higher gas production at 12, 24, and
48 h and a higher DMD rate at 24 h. These suggest that 5-HTP can
enhance carbohydrate digestion, increase DMD rate, and organic acid
production.
4.2. Effects of 5-HTP on rumen microbial community composition in vitro
The low-dose 5-HTP groups (2 mg/kg and 4 mg/kg) showed higher alpha
diversity in the rumen microbial community, likely because of the
increased VFA concentration during fermentation. This results in a
decrease in pH and inhibits acid-labile microbial metabolic activity.
Conversely, the high-dose groups (8 mg/kg and 10 mg/kg) had higher
total acid content in the rumen fluid than the low-dose 5-HTP groups (2
mg/kg and 4 mg/kg), potentially leading to a decrease in microbial
community diversity. The dominant phyla in this study were
Bacteroidetes, Firmicutes, Proteobacteria, Actinobacteria, and
Verrucomicrobia, with relative abundances ranging from 19.29% to
77.70%, 12.82% to 49.55%, 0.98% to 47.38%, 0.44% to 6.51%, and 0.02% to
3.67%, respectively. These phyla, particularly Verrucomicrobia, are
important for maintaining intestinal homeostasis and metabolic
activity. Zhang and Wang ([166]36) showed that the two phyla with the
highest relative abundances were Bacteroidetes and Firmicutes.
Bacteroidetes efficiently decompose carbohydrates in the
gastrointestinal tract ([167]37), primarily starch, proteins, and
polysaccharides ([168]38), with numerous polysaccharide utilization
sites for various enzymes to efficiently degrade polysaccharides
([169]39). Firmicutes are capable of breaking down fibers, including
Ruminococcus, Butyrivibrio, and Pseudobyrivibrio species ([170]40).
Proteobacteria are Gram-negative bacteria, and Vibrio succinogenes
belong to the phylum Proteobacteria. The high-dose 5-HTP groups (8
mg/kg and 10 mg/kg) showed a significant increase in the relative
abundance of Proteobacteria at 12 and 48 h compared to the low-dose
5-HTP groups (2 mg/kg and 4 mg/kg). This suggests that the high-dose
groups (8 mg/kg and 10 mg/kg) were more favorable for the growth and
reproduction of Proteobacteria. Prevotella, Succinovibrio, Lunella, and
Succinobacter were the dominant genera, with relative abundances of
9.55-51.06%, 0.63-45.88%, 0.58-17.64%, and 0.73-5.74%, respectively.
The Prevotella genus is primarily responsible for the breakdown of
xylan and pectin but not cellulose. Provotella secretes xylanase and
carboxymethyl cellulase. The main components of Provotella breakdown
products include acetic acid, succinic acid, and propionic acid. Vibrio
succinogenes breaks down fructan and protein in forage, resulting in
the production of fermentation products such as acetic, succinic,
formic, and lactic acids. This process promotes protein synthesis
([171]41). This study demonstrated that the high-dose 5-HTP groups (8
mg/kg and 10 mg/kg) showed significant increase in the abundance of
Vibrio succinogenes at 12 h and 24 h (P < 0.05). This finding was
consistent with previous research showing a higher production of VFA in
the high-dose groups (8 mg/kg and 10 mg/kg). Furthermore, a positive
correlation was observed between acetic acid production and Vibrio
succinogenes in the high-dose 5-HTP groups (8 mg/kg and 10 mg/kg). Beta
diversity analysis revealed that the community composition of 5-HTP
supplemented at 2 and 4 mg/kg and 8 and 10 mg/kg was similar,
indicating that 5-HTP supplementation affected microbial community
composition and VFA production.
4.3. Effects of 5-HTP on rumen metabolite in vitro
In our study, 15 significantly differential metabolites were found,
including three alcohols, nine organic acids, one carbohydrate, one
nucleoside, and one aldehyde. The results showed that 5-HTP
supplementation increased the levels of four metabolites: norvaline,
cycloleucine 2, methylmalonic acid, and octanal 2. Additionally, the
high-dose groups (8 mg/kg and 10 mg/kg) exhibited down-regulation of
uridine 2, lignin acid, and N-methyltryptophan, while seven other
metabolites (panthenol 2, lipoic acid, β-sitosterol, gluconic acid 1,
N-dimethylarginine, cholesterol, and lyxose 2) showed both
down-regulation and up-regulation in low-dose 5-HTP groups (2 mg/kg and
4 mg/kg). The study also analyzed 11 metabolic pathways associated with
the differential metabolites, including unsaturated fatty acid
biosynthesis and methane metabolism. Overall, 15 differential
metabolites were identified as potential chemical markers for future
studies on the effects of 5-HTP on ruminal function.
4.4. Correlation analysis between rumen metabolome and microorganisms in
vitro
Pearson’s correlation analysis revealed a positive correlation between
2’-deoxyadenosine and Prevotella, 1-hydroxy-2-naphthoic acid and
Succinivibrio, and 1-mono palmitin, 2’-deoxyadenosine 1, and Sharpea.
Additionally, ASV Spearman correlation analysis showed that
2-butyne-1,4-diol, 1,3-cyclohexanedione, 1,2,3-dihydropyridine,
1-methylhydantoin, 1,1-hydroxy-2-naphthoic acid, and 2,3-dimethyl
succinic acid were positively correlated with Succinivibrio and
Selenomonas. Both Pearson and ASV Spearman correlation analyses
indicated a positive correlation between 1-Hydroxy-2-naphthoic acid and
Succinivibrio, suggesting that the addition of 5-HTP may increase the
abundance of this metabolite in the rumen, leading to increased
Succinivibrio abundance.
4.5. Effects of 5-HTP on nutrient digestion and growth performance in sheep
There was no significant difference in DMI between the two groups over
60 days (P > 0.05). However, the 5-HTP group gained an average weight
of 1.2 kg more than the control group at day 60. The 5-HTP group also
showed a significantly higher body weight on day 30 (P < 0.05) and had
a higher average daily gain than the control group at all growth
stages.
4.6. Effects of 5-HTP on blood parameters in sheep
Blood biochemical indices in animals indicate their health ([172]42),
nutritional levels, and metabolic functions ([173]43). Total protein in
plasma, composed of albumin and globulin, transports nutrients,
maintains colloid osmotic pressure, and regulates immunity ([174]44).
Albumin, synthesized in the liver, protects globulins, stabilizes blood
pressure, and enhances immunity and resistance ([175]45). 5-HTP reduced
the overall protein and globulin levels in the plasma (P < 0.05),
possibly due to the increased activity of rumen fibro-degraders and the
inhibition of proteolytics. This suggests that 5-HTP stimulation
results in decreased protein absorption and metabolism. The 5-HTP group
showed a higher albumin concentration on day 15 (P < 0.05), indicating
a normal body state, but it did not significantly affect the blood
antioxidant capacity of sheep (P > 0.05). GH levels were also higher in
the 5-HTP group, indicating greater weight gain. Additionally, INS
concentrations were higher in the 5-HTP group on day 60 (P < 0.05),
emphasizing the importance of GH in regulating animal growth and
metabolism. Similarly, Zeng et al. ([176]18) reported that 5-HTP
supplementation in dairy cows increased plasma GH concentrations.
Feeding sheep with 5-HTP can stimulate the synthesis of 5-HT, which in
turn leads to the secretion of GH in the hypothalamus. This increased
secretion of GH results in a higher blood glucose concentration,
requiring the 5-HTP group to produce more INS to maintain normal body
levels. During the 60-day experimental period, the blood levels of
5-HTP, 5-HT, and MT initially increased and then gradually decreased.
The 5-HTP group showed higher levels, indicating a peak in MT synthesis
before day 45, followed by a gradual decline.
4.7. Effects of 5-HTP on blood metabolite in sheep
Differential metabolites were identified using VIP and P-values. A
total of 43 compounds were selected based on their FC and P values.
These metabolites include S-methylmethionine, 5-HTP, Flaulol A,
5-Methoxyvidan, 5-HEPE, cholic acid, nutriacholic acid, Agrocybin,
2-Methylhippuric acid, DL-tyrosine, L-methionine, and
phosphatidylcholine. We conducted a pathway enrichment analysis and
selected 8 metabolic pathways, including tryptophan metabolism, after
bubble map collation. The presence of 5-HTP in the differential
metabolites indicates that some fed 5-HTP is not completely metabolized
in the rumen and enters the sheep’s bloodstream to be involved in
tryptophan metabolic pathways.
5. Conclusion
Dietary supplementation of 5-HTP (8 mg/kg DM) improved sheep growth
performance by enhancing ruminal functions, antioxidant capacity, and
tryptophan metabolism in both in vitro and in vivo models. This study
shows that 5-HTP has a positive impact on sheep rumen function and
growth performance, suggesting its potential as a functional feed
additive in ruminants.
Data availability statement
The NCBI Sequence Read Archive (SRA) database contains the raw sequence
reads for all samples described in the study (No.PRJNA1014763).
Ethics statement
The animal study was approved by the Institutional Animal Care
Committee of Jilin Agricultural University (JLAUACUC2022-003) for the
management of experimental animals. The studies were conducted in
accordance with the local legislation and institutional requirements.
Written informed consent was obtained from the owners for the
participation of their animals in this study. The study was conducted
in accordance with the local legislation and institutional
requirements.
Author contributions
ZS: Conceptualization, Supervision, Writing – review & editing. NA:
Methodology, Data curation, Software, Writing – original draft. LC:
Methodology, Formal analysis, Software, Writing – original draft. YX:
Methodology, Writing – original draft. LZ: Methodology, Writing –
original draft. GY: Methodology, Writing – original draft. SW:
Methodology, Writing – original draft. ZW: Writing – original draft.
JD: Methodology, Writing – original draft. WZhan: Writing – original
draft. WZhao: Methodology, Writing – original draft. GQ:
Conceptualization, Supervision, Writing – review & editing. XZ:
Conceptualization, Supervision, Writing – review & editing. RZ:
Conceptualization, Writing – review & editing. YZ: Conceptualization,
Supervision, Writing – review & editing. TW: Conceptualization,
Supervision, Writing – review & editing.
Funding Statement
The author(s) declare financial support was received for the research,
authorship, and/or publication of this article. The present work was
funded by the Scientific and Technological Developing Scheme of Jilin
Province (grant number 20230202075NC) and the National Natural Science
Foundation of China (grant number 32102574).
Conflict of interest
ZS, WZhan, WZhao, TW, and YZ are employed by Changchun Borui Science
and Technology Co., Ltd., China.
The remaining authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be
construed as a potential conflict of interest.
Publisher’s note
All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated
organizations, or those of the publisher, the editors and the
reviewers. Any product that may be evaluated in this article, or claim
that may be made by its manufacturer, is not guaranteed or endorsed by
the publisher.
Supplementary material
The Supplementary Material for this article can be found online at:
[177]https://www.frontiersin.org/articles/10.3389/fimmu.2024.1398310/fu
ll#supplementary-material
[178]Table_1.docx^ (53.2KB, docx)
References