Abstract
High-density aquaculture and nutritional imbalances may promote fatty
liver in genetically improved farmed tilapia (GIFT, Oreochromis
niloticus), thus reducing the gains achieved by breeding. In this
study, apple peel powder (APP) was used as a feed additive for GIFT. A
control group (fed on a diet without APP) and five groups fed on diets
supplemented with APP (at 0.05%, 0.1%, 0.2%, 0.4%, or 0.8% of the diet,
by weight) were established to investigate the effects of APP on GIFT
growth performance and physiological parameters, and on gene expression
as determined by transcriptomic analysis. Dietary supplementation with
APP at 0.2% promoted GIFT growth, reduced total cholesterol and
triacylglycerol levels in the serum and liver, and decreased alanine
aminotransferase and aspartate aminotransferase activities in the
serum. Gene expression profiles in the liver were compared among the
control, 0.2% APP, and 0.8% APP groups, and differentially expressed
genes among these groups were identified. Annotation analyses using
tools at the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes
databases showed that the differentially expressed genes were mainly
involved in the regulation of immunity and fat metabolism. The results
showed that excessive supplementation with APP in the diet
significantly inhibited the expression of insulin-like growth factor 2
and liver-type fatty acid-binding protein, and stimulated the
expression of fatty acid desaturase 2, heat shock protein 90 beta
family member 1, and nuclear factor kappa B. This resulted in
disordered lipid metabolism and increased pro-inflammatory reactions,
which in turn caused liver damage. Therefore, APP has good potential as
an environmentally friendly feed additive for GIFT at levels of
0.1%–0.2% in the diet, but excessive amounts can have adverse effects.
Introduction
The use of immunostimulants in aquafeeds not only improves the defense
responses of fish when they are exposed to pathogens, but also provides
an alternative to antibiotics and chemotherapeutics for treating fish
diseases [[38]1–[39]4]. The transformation of a raw material into a
foodstuff creates various waste streams, which can include edible food
mass that is lost, discarded, or degraded at different stages of the
food supply chain. Waste streams can include the peel, stems, cores,
and skin of fruits, and seeds, husks, bran, and straw from cereals.
Food waste has traditionally been viewed as an undesirable material to
be disposed of, at considerable expense, via landfill or incineration,
or used as animal feed. However, such wastes are now increasingly
considered to be a promising source of valuable nutraceuticals
[[40]5,[41]6].
Apple peel is a waste product generated during juice and canned fruit
production; however, it could be economically beneficial to use it as a
value-added food ingredient [[42]7,[43]8]. Given its high levels of
dietary fiber, apple peel can promote lipid metabolism and blood
glucose regulation. In previous studies, apple peel extract (APE) was
shown to have an inhibitory effect on insulin resistance-related
obesity and type II diabetes in mice fed on a high-fat diet [[44]9]. In
those mice, dietary supplementation with APE resulted in significantly
improved glucose tolerance and insulin sensitivity, reduced cytokine
levels in the early phase of pro-inflammation, and decreased oxidation
levels in adipose tissue [[45]9]. Li et al. [[46]10] found that
hyperlipidic mice fed on a diet supplemented with 4% apple dietary
fiber showed significant reductions in blood glucose and blood fat.
Increasing fishmeal prices have led to the development of high-fat
diets for farmed fish. A high-fat diet provides sufficient dietary
protein for tissue synthesis, increases dietary protein utilization
efficiency, and saves protein resources [[47]11]. However, high-fat
diets may cause imbalances between pro-inflammatory and
anti-inflammatory activities [[48]12]. Pro-inflammatory cytokines,
including interleukin (IL)-1β and tumor necrosis factor (TNF)-α, are
involved in the inhibition of hepatic fat metabolism in genetically
improved farmed tilapia (GIFT, Oreochromis niloticus) [[49]12]. Nuclear
factor κB (NF-κB) is an important transcription factor that is
activated during lipid metabolism disorder in grass carp
(Ctenopharyngodon idella) [[50]13] and during liver injury in Nile
tilapia [[51]14]. Activated NF-κB regulates the expression of several
pro-inflammatory and cytotoxic cytokines during inflammation.
Previous studies have shown that the components of red delicious apple
peel include triterpenoids, flavonoids, organic acids, and plant
sterols [[52]15], and about 80% of total polyphenols are concentrated
in the peel of apple fruits [[53]16]. Studies on mammals have shown
that triterpenoids and polyphenols can reduce the production of
pro-inflammatory cytokines by inhibiting transcription factors and
signaling pathways [[54]17,[55]18]. Mueller et al. [[56]17] found that
triterpenoids in apple peel exerted anti-inflammatory effects by
modulating the expression of the gene encoding IFN-γ-inducible
protein-10 in T84 cells; this protein plays an important role in
inflammatory bowel disease. The administration of tea polyphenols at a
dose greater than 50 mg/kg ameliorated the effects of type II diabetes
mellitus in rats, accompanied by lower levels of total cholesterol
(TC), triglyceride (TG), free fatty acids (FFA), and
low-density-lipoprotein cholesterol (LDL-C) in the blood and reduced
levels of inflammatory factors (TNF-α, IL-1β, and IL-6) [[57]18]. The
ability of these compounds to inhibit inflammatory factors and affect
regulatory signaling pathways suggests that they have the potential to
treat and prevent fatty liver inflammation. Therefore, the main focus
of this study was to determine whether apple peel can be used as a feed
additive to regulate fish lipid metabolism and alleviate inflammatory
damage.
GIFT is a freshwater farmed fish with high economic and nutritional
value. The liver is an important organ in fish metabolism. Once it is
damaged or diseased, metabolic disorders and low disease resistance can
develop, which may lead to other secondary diseases [[58]19]. In
high-density intensive GIFT aquaculture, feed nutrition is not
balanced, especially with the recent trend towards high-fat diets
[[59]20]. A high-fat diet can accelerate fish growth, but long-term
consumption of such diets can lead to metabolic disorders, fat
accumulation, fatty liver, and ultimately death due to liver necrosis
or hemorrhage. This can seriously reduce the gains achieved by breeding
[[60]20]. Therefore, the development of environmentally friendly feed
additives that protect liver function and promote tilapia growth is
important for research and industry. For example, supplementation with
100 mg/kg silymarin or 2% chitosan in the diet can increase the growth
and feed coefficient of tilapia [[61]21, [62]22]. Against this
background, the main purposes of this study were: (i) to investigate
the effect of APP on the fat metabolism and fat deposition in the liver
in GIFT; (ii) to determine how this diet affects signal-regulated
pathways in the liver by transcriptomic analyses, with a focus on fat
metabolism and inflammatory responses; and (iii) to screen for
differentially expressed genes between GIFT fed on diets without APP
and those with various levels of APP and verify their expression levels
by qRT-PCR. The results of this study shed light on the molecular
mechanisms of the effect of APP on liver function and fat metabolism
and inflammatory responses in GIFT. These results also provide
theoretical support for the use of APP as an additive in aquatic feed.
Materials and methods
Ethics approval
The study protocols and design were approved by the Ethics Committee at
the Freshwater Fisheries Research Centre of the Chinese Academy of
Fishery Sciences (Wuxi, China). The GIFT were maintained in
well-aerated water and treated with 100 mg/L tricaine methanesulfonate
(Sigma, St Louis, MO, USA) for rapid deep anesthesia. All samples were
extracted based on the Guide for the Care and Use of Laboratory Animals
in China.
Experimental diets
The experimental diets included a control (no APP) and five
supplemented with APP at different concentrations (0.05%, 0.1%, 0.2%,
0.4%, and 0.8% by weight) ([63]Table 1). For this, commercially
available APP was provided from Beijing Yujing Biotechnology Co., Ltd.
(Beijing, China). All ingredients in the diets were powdered and
thoroughly mixed together in a food mixer for about 15 min, after which
APP was added to different levels. Each diet was mixed for about 40 min
until well homogenized, and then tap water was added to produce a firm
dough. The dough was passed through a pelleting machine with 1-mm
diameter; and the extruded dough was broken and sieved while fresh to
obtain pellets of a convenient size. Each diet was dried at ambient
temperature for 3 days and then stored at −20°C in labeled
plastic-lined bags until use.
Table 1. Ingredients and composition of basal diet.
Ingredients (%) 0 (Control) 0.05 0.1 0.2 0.4 0.8
Fish meal 8 8 8 8 8 8
Wheat middling 15 15 15 15 15 15
Corn starch 16.8 16.8 16.8 16.8 16.8 16.8
Soybean oil 5 5 5 5 5 5
Soybean meal 15 15 15 15 15 15
Cottonseed meal 18 18 18 18 18 18
Rapeseed meal 18 18 18 18 18 18
Vitamin premix[64]^1 0.5 0.5 0.5 0.5 0.5 0.5
Mineral premix[65]^2 0.5 0.5 0.5 0.5 0.5 0.5
Choline chloride 0.5 0.5 0.5 0.5 0.5 0.5
Vit C phosphate ester 0.2 0.2 0.2 0.2 0.2 0.2
Ca (H[2]PO[4])[2] 1.5 1.5 1.5 1.5 1.5 1.5
Cellulose 1 0.95 0.9 0.8 0.6 0.2
Total 100 100 100 100 100 100
Proximate composition (%, DM)
Crude protein 28.7 28.2 28.5 28.7 28.5 28.8
Crude lipid 7.3 7.2 7.3 7.4 7.5 7.3
[66]Open in a new tab
^1Vitamin premix (mg/kg dry diet): V[A], 10; V[D], 0.05; V[E], 400;
V[K], 40; V[B1], 50; V[B2], 200; V[B3], 500; V[B6], 50; V[B7], 5;
V[B11], 15; V[B12], 0.1; V[C], 1000; Inositol, 2000; Choline, 5000.
^2Mineral premix (mg/kg dry diet): FeSO[4].7H[2]O, 372; CuSO[4].5H[2]O,
25; ZnSO[4].7H[2]O, 120; MnSO[4].H[2]O, 5; MgSO[4], 2475; NaCl, 1875;
KH[2]PO[4], 1000; Ca (H[2]PO[4])[2], 2500.
Experimental facility and fish rearing
A total of 540 healthy GIFT fingerlings with an average body weight of
2.57 ± 0.03 g were obtained from the Tilapia Breeding Center,
Freshwater Fisheries Research Centre, Wuxi, China. Fingerlings were
acclimated for 1 week under a natural photoperiod with continuous
aeration and a water recirculating system. During this period, the fish
were fed three times with a commercial diet (crude protein 31.5%; crude
fat 7.5%). Subsequently, they were randomly divided into six groups.
Each group was fed on the experimental diet until apparent satiation
three times a day (08:00, 12:00, and 16:00) for 8 weeks. Each group had
three replicates or plastic tanks (30 fish per tank, 0.9 × 0.9× 1.0 m).
Water temperature (29.0°C ± 0.5°C) and pH (pH = 7.4) were kept constant
during the experimental period. Water quality was checked once a week.
The ammonia, nitrate, and nitrite levels were all <0.1 mg/L, and
dissolved oxygen was maintained at 5.94 ± 0.26 mg/L.
Sample collection and fish growth performance
At 24 h after the last experimental feeding, the body weight of all of
the fish in each tank was measured. For each group, nine fish (three
fish per tank) were weighed and dissected, and their liver and viscera
were removed and separately weighed. Fish growth was assessed in terms
of weight gain (WG), specific growth rate (SGR), hepatosomatic index
(HSI), and viscerosomatic index (VSI). Feed utilization was analyzed
using feed conversion ratio (FCR). Throughout the experiment, the
amount of feed consumed and mortality in each replicate were noted.
These parameters were calculated as follows:
[MATH: WG(g)=W2−
W1 :MATH]
[MATH: SGR(%day−1)=[Ln(W2)−Ln(W1)/t]×100 :MATH]
[MATH: HSI(%)=[Liverweight(g)/W2(g)]×100 :MATH]
[MATH: VSI(%)=[Visceralweight(g)/W2(g)]×100 :MATH]
[MATH: FCR=Feedintake(g)/WG(g) :MATH]
[MATH:
Surviva
l(%)=[Numberofsurvivingfish/initialnumberoffish]×100
:MATH]
where W[2] is final weight (g), W[1] is initial weight (g), and t is
the feeding trial period (days).
Blood and hepatic parameters
The blood of GIFT was analyzed to determine hematological and
biochemical parameters. At 24 h after the last feeding, blood was
collected from the caudal vein of four anesthetized fish per tank. Each
blood sample was transferred into an Eppendorf tube, left to clot at
4°C, and then centrifuged at 3500 g and 4°C for 10 min. The collected
serum was then stored at −20°C until further biochemical analysis
(within 10 h). Serum glucose (GLU), TC, and TG levels and serum alanine
aminotransferase (ALT) and aspartate aminotransferase (AST) activities
were quantified by an electrochemiluminescence method using a Mindray
biochemical auto analyzer (BS-400), with kits supplied by Mindray
Biomedical Electronics Co., Ltd. (Shenzhen, China) [[67]23]. The
hepatic TG, TC, and FFA levels were measured using detection kits
purchased from Nanjing Jiancheng Biological Engineering Research
Institute (Nanjing, China) [[68]24].
Liver samples for high-throughput sequencing
On the basis of data on growth and related biochemical indicators, an
appropriate APP group (APP_A), a high-dose APP group (APP_H), and a
control group (C) were further analyzed. Five fish (45 fish in total)
were taken from each tank and their liver tissues were dissected. The
liver tissue of each fish was divided into two parts, which were
immediately frozen in liquid nitrogen and stored at −80°C until use.
One part was used for transcriptome sequencing and the other was used
for experiments to confirm the transcript levels of differentially
expressed (DE) genes identified from the sequencing data.
Analysis of transcriptome libraries
RNA extraction and transcriptome sequencing
The stored liver samples were used for transcriptome sequencing. Total
RNA was extracted using Trizol reagent (Invitrogen, CA, USA) following
the manufacturer’s protocol, and RNA quantity and purity were analyzed
using a Bioanalyzer 2100 and RNA 6000 Nano LabChip Kit (Agilent, CA,
USA) with RNA Integrity Number >7.0 and 28S/18S ≥1.5. The RNA samples
with good integrity and purity for each group were mixed, and five fish
per tank were combined as a treatment group to construct each mRNA
library. About 10 μg total RNA from each mixed group was used to
prepare libraries. Nine mRNA libraries were constructed, namely,
APP_A1, APP_A2, APP_A3, APP_H1, APP_H2, APP_H3, C1, C2, and C3. The
experimental procedures, including those for library preparation and
sequencing, were the standard procedures provided by Illumina [[69]25,
[70]26]. Each library was qualified and sequenced using the Illumina
Hiseq4000 platform. The sequences were double-ended 2 × 150 bp (PE150)
reads.
Assembly and annotation of transcripts
Invalid reads (including joint, repetitive, and low-sampling reads)
were filtered from the sequence data to obtain clean reads, which were
used for subsequent analyses. The data processing steps to obtain clean
reads were as follows: 1) remove reads containing adaptors; 2) remove
reads with N >5%; and 3) remove low-quality reads (those with more than
20% of bases with a mass value Q≤10). The short-read assembly software
Trinity 2.4.0 (Campton, NH, USA)
([71]http://trinityrnaseq.sourceforge.net/) was used for de novo
transcriptome reconstruction. The raw sequence data have been submitted
to NCBI’s Gene Expression Omnibus and are accessible under the GEO
series accession number [72]GSE127810
([73]https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE127810).
Reads from the APP_A, APP_H, and C libraries were aligned to the
Oreochromis niloticus reference genome
([74]http://asia.ensembl.org/Oreochromisniloticus/Info/Index/dna/)
using the TopHat 2 package, which initially removes a portion of the
reads based on quality information accompanying each read and then maps
the reads to the reference genome [[75]27]. TopHat, which allows
multiple alignments per read (up to 20 by default) and a maximum of two
mismatches when mapping the reads to the reference, was used to build a
database of potential splice junctions and confirm them by comparing
previously unmapped reads against the database of putative junctions.
Enrichment analysis of differentially expressed genes
In transcriptome RNA-seq data, the gene expression level is represented
by fragments per kilobase of exon model per million mapped reads (FPKM)
values [[76]28]. The Cuffdiff command of Cufflinks 2.2.1 software
([77]http://cufflinks.cbcb.umd.edu/index.html) was used to identify the
DE genes among libraries [[78]29]. In this study, the false discovery
rate (FDR) was calculated using corrected P-values. The DE genes
between samples were selected based on |log2foldchange|≥1 and corrected
P<0.05. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes
(KEGG) enrichment analyses were performed to determine the functions of
the DE genes and the metabolic pathways associated with them,
respectively.
Gene Ontology analysis of differentially expressed genes
Gene Ontology is an internationally standardized gene function
classification system that provides a dynamically updated and
controlled vocabulary to fully describe the properties of genes and
gene products in organisms. There are three ontological groups:
molecular functions, cellular components, and biological processes. The
basic GO unit is a “term,” and each term corresponds to an “attribute.”
Significant enrichment analysis of GO function first maps all
significant DE genes to the terms in the GO database
([79]http://www.geneontology.org/), then calculates the number of genes
per term, and then applies a hypergeometric test to find GO entries
that are significantly enriched in DE genes compared with the entire
genomic background. The calculation is as follows:
[MATH: P=1‐∑i=0m−1<
mrow>(Mi)(N−Mm−i)(Nn) :MATH]
where N is the total number of genes with GO annotations, n is the
number of DE genes in N, M is the number of genes annotated as a
particular GO term, and m is the number of DE genes annotated as a
particular GO term.
KEGG enrichment analysis of DE genes
Different gene products coordinate with each other in vivo to perform
biological functions; hence, pathway-based analyses can shed light on
the biological functions of genes. The tools at the KEGG database
([80]http://www.genome.jp/kegg/pathway.html) can be used to identify
pathways significantly enriched with DE genes. Hypergeometric testing
is used to identify pathways significantly enriched with DE genes
compared with the entire genome background. The calculation is as
follows:
[MATH: P=1‐∑i=0m−1<
mrow>(Mi)(N−Mm−i)(Nn) :MATH]
Here, N is the total number of genes with KEGG annotations, n is the
number of DE genes in N, M is the number of genes annotated with a
particular pathway, and m is the number of DE genes annotated with a
particular pathway.
Verification of DE genes by qRT-PCR
All primers for screened DE genes ([81]Table 2) were synthesized by the
Shanghai Jikang Biotechnology Co., Ltd. (Shanghai, China). Another
liver sample, obtained as described in section 2.5, was selected for
RNA extraction. The RT reaction and qRT-PCR were carried out in
accordance with the instructions of PrimeScript RT Reagent Kit Perfect
Real Time (TaKaRa, Dalian, China) and SYBR^® Premix Ex Taq (TaKaRa)
kits, respectively, using the ABI 7900HT Fast Real-Time PCR System. The
internal reference was 18S rRNA. The PCR mixture (50 μL) consisted of
19 μL autoclaved deionized water, 25 μL SYBR Green PCR Master Mix (2×),
2 μL forward and reverse primers (10 mol/L), and 4 μL cDNA working
solution. The cycling conditions were as follows: 95°C for 5 min, 95°C
for 15 s, and 60°C for 60 s (40 cycles), with a final dissociation step
at 95°C for 15 s, 60°C for 15 s, and 95°C for 15 s [[82]19]. Three
replicate wells were used for each reaction. All test samples contained
a negative control without a template to rule out false positive
results.
Table 2. Sequences of primers used for qRT-PCR.
Name Primer sequence (5′–3′)
LPL F: 5′- ATCAGCACTACCCGACCTCT-3′
R: 5′- GCGCTCCCAGACTATAACCC-3′
IGF-2 F: 5′- CGCCTAACTCACCTGCAATC-3′
R: 5′- TGTCCGTATCTTTGCTGGGT-3′
FABP2 F: 5′-TTCGAAGACATCCACGCAGT-3′
R: 5′-AGTTTTGGGAGGCTGTCACT-3′
TLR2 F: 5′- CGCACAGATAAGGCAGACAC-3′
R: 5′- CCTAGTCCCAGAGCTGCTTT-3′
HSP90b1 F: 5′- AGACTACCTGGAGCTGGAGA-3′
R: 5′- TCAACCGTCTCAGTCTTGCT-3′
FADS2 F: 5′- GCAGGAATGATCAGTGGCTG-3′
R: 5′- CTCCGTAGCATCCTCTCCAG-3′
NF-kB F: 5′- AACCCCATCTACGACAGCAA-3′
R: 5′- TCCCAGCATCCATCCTCATC-3′
18S rRNA F: 5′-GGCCGTTCTTAGTTGGTGGA-3′
R: 5′-TTGCTCAATCTCGTGTGGCT-3′
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LPL: lipoprotein lipase; IGF-2: insulin-like growth factor 2; FABP2:
liver-type fatty acid-binding protein; TLR2: toll-like receptor 2;
HSP90b1: heat shock protein 90 beta family member 1; FADS2: fatty acid
desaturase 2; NF-kB: nuclear factor kappa B
Hematoxylin–eosin staining and oil red O staining of frozen sections
Hematoxylin–eosin staining [[84]20]
Three fish were randomly selected from each tank, their liver tissue
was removed and then fixed with 4% paraformaldehyde for 24 h. After
washing with tap water, the liver tissue was subjected to gradient
alcohol dehydration, cleared with xylene, and then embedded in paraffin
embedding. Slices (5 μm) were cut using an RM-2145 (Leica, Nussloch,
Germany) rotary microtome. After hematoxylin–eosin (HE) staining,
sections were observed under a Leica UB203I optical microscope and
photographed.
Oil red O staining
Oil red O staining was conducted as described elsewhere [[85]20].
Briefly, liver tissues were fixed with 4% paraformaldehyde for 4 days,
washed twice with phosphate buffer, washed twice with
phosphate-buffered solution, immersed in 30% sucrose (prepared in
phosphate buffer) at 4°C overnight, embedded in OCT (ice cutting
embedding agent), and cut into 8-μm sections with using a Leica CM1950
cryostat. The sections were heated at 60°C for 30 min, stained for 10 s
with hematoxylin staining solution, washed for 1 min tap water, dried,
rinsed in 50% ethanol, stained with oil red O ethanol dye solution for
8 min, washed with 50% ethanol and then tap water, and then sealed with
glycerin gelatin.
Data analysis
The relative expression level of each gene in each APP dietary
supplementation treatment vs. the control was determined by the 2^−ΔΔCT
method. The results are expressed as mean ± standard deviation (SD).
First, the data were tested for a normal distribution and homogeneity
of variance; then, an appropriate analysis was selected depending on
the results. The relationship between SGR and dietary APP levels was
analyzed using a two-slope broken-line model. The significance level
was set at P < 0.05.
Results
Growth performance and feed utilization efficiency
The WG and SGR were significantly lower in 0.4%–0.8% APP groups than in
the control group and the 0.05%–0.2% APP groups (P <0.05) ([86]Table
3); however, there was no significant difference in WG or SGR between
the control group and the 0.05%–0.2% APP groups. The FCR was higher in
the 0.8% APP group and in the control than in the 0.2% APP group. The
broken-line regression model of SGR indicated that 0.17% APP was the
optimal amount for GIFT to achieve optimal growth ([87]Fig 1). The HSI
and VSI were significantly lower in the 0.2%, 0.4%, and 0.8% APP groups
than in the control group. However, there were no significant
differences in HSI and VSI among the control and the 0.05% and 0.1% APP
groups (P > 0.05). Dietary supplementation with 0%–0.8% APP did not
significantly affect survival.
Table 3. Growth performance and feed utilization of GIFT (Oreochromis
niloticus) fed on diets supplemented with apple peel powder for 8 weeks.
Parameters Dietary apple peel powder level (%)
0 0.05 0.1 0.2 0.4 0.8
WG 41.12±2.45^b 48.38±2.39^ab 51.94±2.86^a 54.65±2.92^a 42.43±2.87^b
31.46±4.33^c
SGR(%/d) 4.70±0.25^b 4.97±0.12^b 5.34±0.24^ab 5.68±0.20^a 4.82±0.12^b
4.29±0.23^c
FCR(%) 1.14±0.03^a 1.05±0.06^ab 1.04±0.05^ab 0.92±0.08^c 1.03±0.04^ab
1.15±0.04^a
HSI(%) 1.80±0.08^a 1.86±0.19^a 1.74±0.10^ab 1.64±0.14^b 1.58±0.06^b
1.51±0.11^b
VSI(%) 14.36±0.27^a 14.27±0.38^a 13.49±0.19^ab 12.21±0.27^b
12.45±0.19^b 12.81±0.44^b
Survival (%) 98.89±1.11 100.00±0.00 100.00±0.00 100.00±0.00 96.67±1.93
100.00±0.00
[88]Open in a new tab
Data were analyzed by one-way analysis of variance and are mean ±
standard deviation. Differences among six groups were detected by
Duncan’s multiple range test (P < 0.05). Different lowercase letters
show significant differences among treatment groups.
WG: Weight gain; SGR: Specific growth rate; FCR: Feed conversion ratio;
HSI: Hepatosomatic index; VSI: Viscerosomatic index
Fig 1. Relationship between specific growth rate and amount of apple peel
powder (APP) in feed, as analyzed by two slope broken-line model.
[89]Fig 1
[90]Open in a new tab
Serum biochemical parameters
When the level of APP supplementation in the diet was 0%–0.4%, the
serum TG and TC levels of the GIFT significantly decreased with
increasing APP (P < 0.05) ([91]Table 4). The serum TC and TG contents
were significantly lower in the 0.1%, 0.2%, and 0.4% APP groups than in
the control group (P < 0.05). However, the TC and TG levels were
significantly higher in the 0.8% APP group than in the 0.4% group. The
serum GLU level was significantly higher in the 0.2% group than in the
control group (P < 0.05), while there was no significant difference in
GLU levels among the 0.05%, 0.1%, 0.2%, 0.4%, and 0.8% APP groups (P >
0.05). The serum ALT and AST activities were significantly higher in
the 0.8% APP group than in the 0.05%, 0.1%, 0.2%, and 0.4% APP groups.
Table 4. Serum biochemistry parameters of GIFT (Oreochromis niloticus) fed on
diets supplemented with apple peel powder for 8 weeks.
Parameters Dietary apple peel powder level (%) (n = 9)
0 0.05 0.1 0.2 0.4 0.8
TC(mmol/L) 4.76±0.52^a 4.09±0.42^b 3.65±0.31^bc 3.51±0.37^bc
3.12±0.31^c 3.97±0.41^a
TG(mmol/L) 5.54±0.64^a 3.87±0.47^b 2.69±0.34^c 2.12±0.31^c 1.47±0.38^d
2.38±0.49^c
GLU(mmol/L) 1.89±0.32^c 2.17±0.25^ab 2.14±0.19^ab 2.33±0.31^a
2.27±0.17^ab 2.11±0.30^b
ALT(U/L) 29.76±1.47^ab 25.13±2.82^b 26.13±2.16^b 26.34±1.92^b
27.11±2.28^b 33.24±2.89^a
AST(U/L) 78.41±6.79^a 65.41±8.11^b 72.19±7.33^b 68.26±5.18^b
67.22±7.31^b 84.06±8.23^a
[92]Open in a new tab
Data were analyzed by one-way analysis of variance and are mean ±
standard deviation. Differences among six groups were detected using
Duncan's multiple range test (P < 0.05). Different lowercase letters
show significant differences among treatment groups.
TC, total cholesterol; TG, triacylglycerol; GLU, Glucose; ALT: alanine
aminotransferase; AST: aspartate aminotransferase
Hepatic biochemical parameters
The levels of TC, TG, and FFA in the liver were significantly lower in
the 0.2% APP group than in the control group (P < 0.05) ([93]Table 5);
however, the levels of hepatic TG and FFA were significantly higher in
the 0.8% APP group than in the 0.2% APP group (P < 0.05).
Table 5. Hepatic biochemical parameters of GIFT (Oreochromis niloticus) fed
on diets supplemented with apple peel powder for 8 weeks.
Parameters Dietary apple peel powder level (%) (n = 9)
0 0.05 0.1 0.2 0.4 0.8
TC(mmol/L) 7.31±0.49^a 5.19±0.40^b 4.85±0.41^b 3.41±0.37^c 3.82±0.41^c
3.67±0.38^c
TG(mmol/L) 21.34±0.64^a 16.78±0.72^b 15.79±1.04^bc 14.12±0.91^c
16.27±0.68^bc 17.78±1.49^ab
FFA(ng/mL) 376.66±16.11^a 269.40±38.24^b 262.45±40.55^b 250.26±34.33^b
285.47±22.88^b 361.19±27.54^a
[94]Open in a new tab
Data were analyzed by one-way analysis of variance and are mean ±
standard deviation. Differences among six groups were detected using
Duncan's multiple range test (P < 0.05). Different lowercase letters
show significant differences among treatment groups.
TC, total cholesterol; TG, triacylglycerol; FFA, free fatty acids
By comparing growth and biochemical parameters among the different
groups, we found that the 0.2% APP group of GIFT showed a good growth
rate and FCR, with low fat deposition in the liver and serum.
Therefore, for further analyses, the 0.2% APP group was selected as
APP_A, and the 0.8% group displaying obvious growth inhibition was
selected as APP_H.
Liver histology and lipid droplets
In the GIFT fed a control diet for 60 days, the hepatocytes became
swollen and part of the nucleus was shrunken, but the cell structure
remained intact. The APP_A group showed a normal histological structure
in contrast to the control group, and their hepatocyte membrane and
nucleus were clear. The hepatocytes in the APP_H group were
significantly enlarged, with a shrunken nucleus and some loss of cell
membrane integrity ([95]Fig 2). There were significantly more lipid
droplets in hepatic cells of the control group had than in those of the
APP_A group and the APP_H group, as revealed by oil red O staining
([96]Fig 3).
Fig 2.
[97]Fig 2
[98]Open in a new tab
Histological analysis of liver sections by hematoxylin-eosin staining
in GIFT (Oreochromis niloticus) fed on diets supplemented with 0% (A),
0.2% (B), and 0.8% (C) apple peel powder. H, hepatocyte; V,
vacuolization; EH, enlarged hepatocyte; SN, shrunken nucleus.
Fig 3.
[99]Fig 3
[100]Open in a new tab
Histological analysis of liver sections by oil red O staining in GIFT
(Oreochromis niloticus) fed on diets supplemented with 0% (A), 0.2% (B)
and 0.8% (C) apple peel powder. Ld, lipid droplet.
Summary of sequencing data and statistics of transcriptome assembly
The transcriptomes of the liver tissues of the C1, C2, C3, APP_A1,
APP_A2, APP_A3, APP_H1, APP_H2, and APP_H3 groups were sequenced using
the Illumina Hiseq4000 platform. After removing low-quality sequences,
the number of valid reads ranged from 40,430,496 to 62,293,208. The Q20
values of the transcriptome data for the nine subgroups from the three
treatment groups were 98.26%–99.23%, while the GC contents were 48%–52%
([101]Table 6). These results showed that the transcriptome sequencing
data were of good quality and could be used for subsequent splicing and
assembly. In the transcriptome data for the C1, C2, C3, APP_A1, APP_A2,
APP_A3, APP_H1, APP_H2, and APP_H3 groups, 31,015,020, 32,605,882,
29,847,539, 27,857,982, 35,474,059, 24,377,649, 31,551,102, 38,937,856,
and 31,822,452 reads were mapped to the Nile tilapia genome,
respectively ([102]S1 Table). Significantly more reads mapped to exonic
regions than to intronic and intergenic regions of the genome ([103]S2
Table).
Table 6. Overview of reads for mRNA-seq of GIFT (Oreochromis niloticus) and
quality filtering.
Sample Raw Reads Base Valid Read Base Valid Ratio (reads) Q20% Q30% GC
content%
APP_A1 45867590 6.88G 45374664 6.81G 98.93 98.59 90.43 49
APP_A2 57594264 8.64G 57040408 8.56G 99.04 99.03 90.79 48.50
APP_A3 52452746 7.87G 40430496 6.06G 77.08 99.23 91.10 52
C1 49272160 7.39G 48844226 7.33G 99.13 99.08 90.64 48.50
C2 54099584 8.11G 53512740 8.03G 98.92 98.47 89.52 49
C3 49681658 7.45G 49111518 7.37G 98.85 98.68 90.00 49
APP_H1 54547964 8.18G 47660140 7.15G 87.37 98.26 86.80 49.50
APP_H2 63096352 9.46G 62293208 9.34G 98.73 99.13 92.26 48
APP_H3 52005944 7.80G 51294450 7.69G 98.63 98.98 91.33 50.50
[104]Open in a new tab
APP_A: 0.2% apple peel powder; APP_H: 0.8% apple peel powder; C:
control group, 0% apple peel powder
Screening and functional annotation of differentially expressed genes
After normalizing the abundance of genes mapped to the Nile tilapia
genome, significantly DE genes were identified on the basis of
|log(foldchange)|≥1 and FDR≤0.05. The DE genes are summarized in a
histogram and Venn diagram (Figs [105]4 & [106]5). Comparisons among
the three groups revealed upregulation of 285 DE genes and
downregulation of 408 DE genes in the APP_A vs. C comparison;
upregulation of 451 DE genes and downregulation of 274 DE genes in the
APP_H vs. C comparison; and upregulation of 915 DE genes and
downregulation of 349 DE genes in the APP_A vs. APP_H comparison
([107]Fig 4). The number of DE genes specific to the APP_A vs. C, APP_H
vs. C, and APP_A vs. APP_H comparisons was 366, 257, and 726,
respectively, and seven DE genes were common to all three comparison
groups ([108]Fig 5). The seven DE genes encoded lipoprotein lipase
(LPL), insulin-like growth factor 2 (IGF-2), liver-type fatty
acid-binding protein (FABP2), toll-like receptor 2 (TLR2), heat shock
protein 90 beta family member 1(HSP90b1), fatty acid desaturase 2
(FADS2), and nuclear factor kappa B (NF-kB).
Fig 4. Analysis of differentially expressed genes in APP_A vs. C, APP_H vs.
C, and APP_A vs. APP_H group comparisons by transcriptome sequencing.
[109]Fig 4
[110]Open in a new tab
APP_A: 0.2% apple peel powder; APP_H: 0.8% apple peel powder; C:
control group, 0% apple peel powder.
Fig 5. Venn diagram showing differentially expressed genes among APP_A vs. C,
APP_H vs. C, and APP_A vs. APP_H group comparisons.
[111]Fig 5
[112]Open in a new tab
APP_A: 0.2% apple peel powder; APP_H: 0.8% apple peel powder; C:
control group, 0% apple peel powder.
GO functional annotation
The GO functional annotation results showed that dietary
supplementation with APP affected the biological processes, cellular
components, and molecular functions of tilapia. Compared with the C
group, the APP_A group had DE genes in biological processes of fatty
acid beta-oxidation, fatty acid biosynthetic process, glycogen
metabolic process, and response to virus. The APP_H group had DE genes
in biological processes of response to virus, response to stimulus,
innate immune response, and inflammatory response ([113]S1 Fig).
KEGG pathway significant enrichment analysis
The specific signaling pathways enriched with DE genes were identified
using tools at the KEGG database. The APP_A group had five pathways
with significant enrichment of DE genes compared with the C group: PPAR
signaling pathway, phagosome, cell adhesion molecules, biosynthesis of
unsaturated fatty acids, and antigen processing and presentation
([114]Fig 6). There were multiple pathways enriched with DE genes in
the APP_H group compared with the C group. The top five enriched
pathways were viral myocarditis, PPAR signaling pathway, phagosome,
natural killer cell-mediated cytotoxicity, and B-cell-receptor
signaling pathway. Thus, the pathways enriched in GIFT fed on diets
including APP at different levels were mainly involved in the
regulation of cellular immunity and fat metabolism.
Fig 6. KEGG pathway enrichment analysis of differentially expressed genes
(corrected P-value < 0.05) in APP_A vs. C and APP_H vs. C group comparisons.
[115]Fig 6
[116]Open in a new tab
APP_A: 0.2% apple peel powder; APP_H: 0.8% apple peel powder; C:
control group, 0% apple peel powder.
Validation of DE genes
The seven DE genes common to all group comparisons were further
analyzed by qRT-PCR. The trends in their expression as detected by
qRT-PCR ([117]Fig 7) were basically consistent with the RNA-seq results
([118]Table 7). Appropriate supplementation with APP (APP_A group)
promoted the expression of IGF-2, FABP2, and TLR2 in the liver, and
decreased the expression of LPL, HSP90b1, and NF-κB. Excessive
supplementation of APP (APP_H group) significantly inhibited the
expression of IGF-2 and FABP2, and stimulated the expression of FADS2,
HSP90b1, and NF-kB.
Fig 7. Validation of seven differentially expressed genes in APP_A, APP_H,
and C groups by qRT-PCR.
[119]Fig 7
[120]Open in a new tab
Data were analyzed by one-way analysis of variance. Differences between
two groups were compared using Duncan's multiple range test
(significance at P < 0.05). Different lowercase letters show
significant differences among different treatment groups. APP_A: 0.2%
apple peel powder; APP_H: 0.8% apple peel powder; C: control group, 0%
apple peel powder.
Table 7. Relative gene expression levels of seven differentially expressed
genes in APP_A vs. C and APP_H vs. C comparisons as estimated from mRNA-Seq
data.
Gene abbreviation Gene
description RNA-seq
Log2 (fold_change) Regulation (APP_A vs. C) Log2 (fold_change)
Regulation (APP_H vs. C)
LPL lipoprotein lipase -1.67 down 2 up
IGF-2 insulin-like growth factor 2 1.85 up -2.57 down
FABP2 liver-type fatty acid-binding protein 1.66 up -2.66 down
TLR2 toll-like receptor 2 3.62 up 1.95 up
HSP90b1 heat shock protein 90 beta family member 1 -1.47 down 2.45 up
FADS2 Fatty acid
desaturase 2 1.37 up 3.64 up
NF-κB nuclear factor κappa B -1.99 down 2.94 up
[121]Open in a new tab
APP_A: 0.2% apple peel powder; APP_H: 0.8% apple peel powder; C:
control group, 0% apple peel powder
Discussion
In this study, dietary supplementation with 0.2% APP promoted the
growth of GIFT and reduced its FCR. The high dietary fiber content in
APP may have had a positive effect on fish health. Studies have shown
that fiber supplementation in the diet helps to reduce the energy
concentration in food. This allows the body to increase the retention
time of food and provides a greater absorption area for nutrients,
which are beneficial for other physiological responses that promote
growth and development [[122]30]. However, excessive dietary fiber may
damage intestinal structure or interact with minerals in the diet, and
reducing the efficiency of nitrogen and energy use [[123]31]. This may
explain the significantly inhibited growth of GIFT in the 0.8% APP
group.
The liver is an important organ for storing fat, and an increase in
liver fat content leads to an increase in HSI. In this experiment,
compared with GIFT in the C group, those in the 0.2% APP and 0.4% APP
groups showed significantly decreased TG and TC levels in liver and
serum, and decreased HSI and VSI. These changes may have been related
to the functional components of APP. The abundance of dietary fiber in
APP can affect metabolism, for example, by stimulating lipid
peroxidation and inhibiting fat production in the liver, and by
promoting the oxidation of fatty acids in muscles, thereby reducing the
accumulation of body fat [[124]32]. The dietary fiber in APP has been
shown to reduce plasma sugar and lipid levels in mice under high-fat
stress [[125]33]. Foods that are high in fat and cholesterol can
increase the concentrations of TC, LDL, and TG in the plasma of mice,
and decrease the concentration of high-density lipoprotein (HDL),
thereby inducing hypercholesterolemia. However, diseased mice fed
dietary fiber from apples showed decreased TC, LDL, and TG levels in
plasma, increased HDL, and a reduced risk of cardiovascular disease
[[126]33]. The triterpenoids in APP may also alleviate liver fat
deposition to some extent. For example, the triterpenoids from
Cyclocarya paliurus were shown to have a therapeutic effect on
nonalcoholic fatty liver disease, by reducing the FFA-induced lipid
accumulation in HepG2 cells and reducing the TG content, leading to a
decrease in cellular oxidative damage [[127]32]. The activities of
serum AST and ALT are indicators of stress. These enzymes showed
significantly higher activities in the APP_H group than in the other
groups. In addition, the high concentration of FFAs in liver tissue in
the APP_H group may have caused severe cytotoxicity, which can lead to
hepatocyte damage and the induction of abnormal lipid metabolism
[[128]34,[129]35]. This may have contributed to the growth inhibition
of GIFT in the APP_H group.
In recent years, transcriptomic analyses have been increasingly used in
the fields of immunization, development, and nutrition of aquatic
animals. In this experiment, APP_A, APP_H, and C groups were selected
for transcriptome analyses to investigate the DE genes and
differentially regulated pathways in GIFT fed APP at different levels.
Compared with GIFT in the C group, those in the APP_A group had 693 DE
genes, of which 285 were upregulated and 408 were downregulated. Seven
DE genes were detected in all comparisons among the C, APP_A, and APP_H
groups. The results of the GO and KEGG analyses showed that DE genes in
APP_A vs. C were particularly associated with glucose and lipid
metabolism, and immunological regulation; however, the DE genes in
APP_H vs. C were particularly associated with various immune responses
and cell signaling pathways. These findings indicate that abnormal
immune stress and signal transduction in the APP_H group may have
affected the liver’s metabolic function, leading to inhibition of GIFT
growth.
Dietary supplementation with flavonoids or organic acids can help to
improve disordered fat metabolism in mice and prevent hyperlipidemia
[[130]36,[131]37]. For instance, total flavonoids from Ligustrum
lucidum were shown to have a beneficial regulatory effect on lipid
metabolism disorder in rats in a high-fat model, possibly via
regulation of the PPARα-LPL pathway and HMGCR expression [[132]36]. In
addition, the total organic acids of Armeniaca sibirica were shown to
increase the concentration of HDL-C, decrease TG activity, and reduce
the serum lipid levels in hyperlipidemic rats, thus reducing blood fat
[[133]37]. The flavonoids and organic acids in APP may have played
similar roles in GIFT in this study. The liver is an important organ
for lipid metabolism in animals, and its lipid metabolic balance is
regulated by various factors. The enzyme LPL is mainly synthesized in
adipose tissue, the myocardium, and muscle. Its main physiological
function is to decompose TG into VLDL, and also to promote the transfer
of TC and phospholipids between lipoproteins [[134]38]. Increased LPL
activity can affect the levels of serum TC and TG [[135]38]. The higher
LPL expression levels in the C and APP_H groups may have been related
to increased contents of TG and FFAs in the liver. Increased LPL
activity increases the decomposition of TG in chylomicrons and VLDL
into FFAs, which are then transported to other tissues via the blood to
promote lipid synthesis or supply oxidative energy. The high LPL
expression levels in the C group may have increased the deposition of
fat droplets in the liver. Interestingly, the levels of TC and TG in
serum and liver were significantly lower in the APP_H group than in the
C group. Therefore, the high LPL expression level in the APP_H group
may have been related to the supply of oxidative energy during the
immune response and the alleviation of liver stress injury.
FABP2 is a fatty acid binding protein expressed in the liver. It
affects fat transport in cells, fat metabolism, and lipid synthesis,
and regulates the metabolism of bile acids and TC by long-chain fatty
acid-dependent proteins [[136]39]. In another study, mice with
knocked-out FABP2 showed significantly inhibited synthesis of TC and
fat oxidation in the liver during fasting, compared with mice in the
control group [[137]40]. In addition, a high-fat diet was shown to
upregulate the expression of FABP2 in mouse liver; FABP2 promoted fatty
acid transport and alleviated damage caused by high-fat stress
[[138]41]. Some aspects of metabolic regulation may be conserved
between mammals and aquatic animals. In this study, APP_A stimulated
FABP2 expression in GIFT liver, increased β-oxidation activity and the
content of unsaturated fatty acids, and helped to improve the immune
response and reduce fat deposition. However, the expression level of
FABP2 in GIFT liver was significantly reduced in the APP_H group, which
may have been indicative of liver damage, toxic effects of FFAs, and
reduced transport of FFAs from the liver [[139]42].
Polyunsaturated fatty acids (PUFAs) in aquatic animals can be further
converted into long-chain PUFAs by a series of dehydrogenation and
prolongation reactions catalyzed by fatty acid desaturase (Fad) and
elongase [[140]43]. As important membrane components, long-chain PUFAs
maintain the fluidity of the cell membrane, thus ensuring the normal
physiological function of cells. They can also esterify TC and reduce
the TC and TG levels in blood [[141]44]. In our study, the APP_A group
showed increased expression of FADS2; this may have helped to protect
the integrity of the cell membrane and reduce fat deposition in serum.
The integrity of liver cell membranes was impaired in the APP_H group.
In this group, therefore, elevated FADS2 expression was insufficient to
maintain cell membrane integrity.
Adipose tissue is not only a passive tissue involved in fuel storage
and tissue organ filling, but also a huge endocrine system. It secretes
a variety of factors that are actively involved in regulating the
neuro-endocrine-immune network. Abnormal fat cell differentiation can
cause excessive fat accumulation, which in turn leads to endocrine
dysfunction of fat cells, and causes the development of insulin
resistance and type II diabetes [[142]45]. Recent studies have found
that IGF-2 is closely related to diseases of glucose metabolism and fat
metabolism in mammals. The overexpression of IGF-2 has been shown to
increase incidence of obesity and diabetes [[143]46]. Other studies
found that the concentration of IGF-2 was positively correlated with
the body weight of pigs during growth, and that increasing
concentrations of IGF-2 in plasma were related to increased thickness
of backfat [[144]47]. Moreover, when IGF-2 was injected into 4-week-old
broilers (0.5 mg/kg), it directly or indirectly caused a change in
plasma T3 content and affect the deposition of abdominal fat [[145]48].
In addition, male rats fed a diet supplemented with soy isoflavones
showed increased blood IGF activity, which promoted the utilization and
decomposition of fat and induced protein synthesis [[146]49]. In this
experiment, flavonoids in APP may have stimulated IGF-2 expression in
the APP_A group. High levels of IGF-2 may increase fatty acid synthesis
and fat storage, promote protein synthesis, and accelerate fish growth.
However, the APP_H group showed abnormal metabolism and glucose and fat
synthesis, as well as disordered glucose/fat utilization, alongside
decreased IGF-2 expression in liver tissue.
The TLR can initiate innate immunity by recognizing pathogens, and can
initiate acquired immunity through signaling. Thus, TLR plays an
important role in the body’s immune defense [[147]14]. Flavonoids exert
immunomodulatory effects by regulating TLR signaling pathways,
particularly the expression of TLR2 and TLR4. Baicalin and quercetin
are rich in flavonoids. Baicalin has been shown to reduce the
expression of TLR2, TLR4, and MyD88 proteins in rats with renal
ischemia–reperfusion injury [[148]50]. Quercetin was shown to reduce
the expression of high mobility group box 1 (HMGB1) and the mRNA and
protein levels of TLR2 and TLR4 in liver tissues of mice with hepatitis
[[149]51]. The flavonoids in APP may have increased the expression
level of TLR2 to stimulate the immune defense response in GIFT.
However, the high FFA content in the APP_H group may have acted
synergistically with TLR2, inducing an inflammatory response [[150]52].
The GO and KEGG analyses showed that, in the APP_H group, immune and
inflammatory response pathways were affected in the GIFT liver. NF-κB
is a key factor regulating the transcription of cellular genes. Under
normal conditions, it binds to NF-κB inhibitory protein (inhibitor of
NF-κB: IκB) and becomes inactive. After stimulation, the IκB kinase
(IKK) complex is activated. IκB phosphorylates and dissociates from
NF-κB, and the activated NF-κB is transported into the nucleus where it
directly initiates and regulates the transcription of genes related to
the immune response, cytokines, and adhesion molecules [[151]53].
Flavonoids in baicalin were shown to promote the expression of
phosphorylated NF-κB (p-NF-κB) and phosphorylated IκB (p-IκB) proteins
in rats with renal ischemia–reperfusion injury, leading to the
regulation of immune inflammatory responses [[152]50]. In diabetic mice
with myocarditis, the flavonoids in liquiritigenin significantly
reduced the secretion of inflammatory cytokines and the phosphorylation
level of NF-κB by inhibiting the nuclear factor-κB inhibitor kinase α
(IKK-α)/IκB-α signaling pathway [[153]54]. Similar results were found
in this study. Our results showed that the flavonoids in APP can
protect the liver of GIFT, reduce fat deposition, and inhibit the
expression of NF-κB, which may help reduce the secretion of
pro-inflammatory cytokines. However, excessive flavonoids may be toxic
to the liver. Some flavonoid molecules have similar DNA-embedded
molecular structures and are potentially genotoxic and mutagenic
[[154]55]. For example, soy isoflavones have been shown to cause or
promote DNA oxidative damage in cells of the reproductive system,
thereby increasing tumorigenesis [[155]56]. Therefore, the higher
flavonoid intake in the APP_H group may have increased liver damage,
upregulated the expression of NF-κB, and promoted inflammatory
reactions in GIFT.
HSP90, as an important molecular chaperone protein, plays a key role in
the development of inflammatory reactions. It has been shown to play an
important pro-inflammatory role when retinal pigment epithelial cells
develop an inflammatory response caused by non-bacterial infections
[[156]57]. In addition, in patients with inflammatory reactions, the
expression of HSP32, HSP70, and HSP90 was significantly increased, and
the expression of HSP90 was closely related to the inflammatory
reaction [[157]58]. However, taurochenodeoxycholic acid was found to
inhibit HSP90 gene expression in an arthritis model, exerting an
anti-inflammatory effect [[158]59]. Our results showed that the APP_A
group had well-functioning liver fat metabolism and good growth, and
low levels of inflammatory response signaling factors such as HSP90b1
and NF-κB. A long-term, low-grade pro-inflammatory state of the body is
one of the most important factors for obesity and insulin resistance
[[159]60]. Although the GIFT in the control group grew normally, the
levels of pro-inflammatory factors NF-κB and HSP90b1 in the liver were
significantly higher than those in the APP_A group, and may have led to
chronic inflammatory reactions, metabolic abnormalities, increased fat
deposition, and the development of fatty liver.
Conclusion
With the development and use of natural products, apple peel has
attracted increasing attention. Its low price and abundance make it a
suitable feed additive for aquatic animals. Our results show that
appropriate dietary supplementation with APP (APP_A, 0.2%) can promote
the growth of GIFT, reduce the levels of TC and TG in the serum and
liver, decrease AST and ALT activities in liver tissue, improve lipid
metabolism, and inhibit pro-inflammatory reactions ([160]Fig 8). These
beneficial effects may be related to the dietary fiber, flavonoids, and
organic acids in APP. However, excessive supplementation with APP
(APP_H, 0.8%) can lead to disordered lipid metabolism and inflammatory
stress (upregulation of HSP90b1 and NF-κB) and increased liver damage.
Further research is required to determine how the functional components
of APP exert their effects to improve fatty liver, glycolipid
metabolism, and inflammatory factors in GIFT.
Fig 8. Pathways related to inflammatory response and fat metabolism in GIFT
(Oreochromis niloticus) potentially affected by apple peel powder in feed.
[161]Fig 8
[162]Open in a new tab
Supporting information
S1 Fig. GO functional annotation of differentially expressed genes
(corrected P-value < 0.05) in APP_A vs. C and APP_H vs. C group
comparisons.
(DOCX)
[163]Click here for additional data file.^ (897KB, docx)
S1 Table. Summary of read data aligned with Oreochromis_niloticus
transcriptome.
(DOCX)
[164]Click here for additional data file.^ (19.7KB, docx)
S2 Table. Exonic rates (%) in APP_A, APP_H, and C libraries as
determined from mRNA-seq data.
(DOCX)
[165]Click here for additional data file.^ (13.1KB, docx)
Acknowledgments