Abstract
Background
Spinibarbus hollandi is an economically important fish species in
southern China. This fish is known to have nutritional and medicinal
properties; however, its farming is limited by its slow growth rate. In
the present study, we observed that a compensatory growth phenomenon
could be induced by adequate refeeding following 7 days of fasting in
S. hollandi. To understand the starvation response and compensatory
growth mechanisms in this fish, the muscle transcriptomes of S.
hollandi under control, fasting, and refeeding conditions were profiled
using next-generation sequencing (NGS) techniques.
Results
More than 4.45 × 10^8 quality-filtered 150-base-pair Illumina reads
were obtained from all nine muscle samples. De novo assemblies yielded
a total of 156,735 unigenes, among which 142,918 (91.18%) could be
annotated in at least one available database. After 7 days of fasting,
2422 differentially expressed genes were detected, including 1510
up-regulated genes and 912 down-regulated genes. Genes involved in fat,
protein, and carbohydrate metabolism were significantly up-regulated,
and genes associated with the cell cycle, DNA replication, and immune
and cellular structures were inhibited during fasting. After refeeding,
84 up-regulated genes and 16 down-regulated genes were identified. Many
genes encoding the components of myofibers were significantly
up-regulated. Histological analysis of muscle verified the important
role of muscle hypertrophy in compensatory growth.
Conclusion
In the present work, we reported the transcriptome profiles of S.
hollandi muscle under different conditions. During fasting, the genes
involved in the mobilization of stored energy were up-regulated, while
the genes associated with growth were down-regulated. After refeeding,
muscle hypertrophy contributed to the recovery of growth. The results
of this study may help to elucidate the mechanisms underlying the
starvation response and compensatory growth.
Keywords: Spinibarbus hollandi, Starvation response, Compensatory
growth, Muscle
Background
Unfavorable environmental conditions, such as extreme temperature,
depression, and hypoxic conditions, and human activities, such as
transportation, can inhibit feeding behavior in fish, resulting in the
starvation of fish in aquaculture. Starvation can influence growth,
development, reproduction, and immunity in animals [[33]1, [34]2].
Organisms usually maintain metabolic homeostasis during starvation by
changing their behavior and activating various physiological and
biochemical adaptive mechanisms. Recent studies have shown that lipid
metabolism could be increased, and energy reserves could be mobilized,
to cope with starvation in Piaractus mesopotamicus [[35]3]. In rainbow
trout (Oncorhynchus mykiss), it was found that genes related to protein
degradation and amino acid metabolism increased, while genes involved
in protein synthesis decreased under starvation [[36]4]. In yellow
croaker (Larimichthys crocea), a number of genes associated with
carbohydrate metabolism also increased during fasting conditions
[[37]5]. In some fish species, food shortages have been shown to weaken
immunity and inhibit body growth because of decreased energy
consumption [[38]6, [39]7].
Previous studies have shown that some fish have the ability to tolerate
short-term food deprivation or fasting. Animals fed to satiation
following continuous fasting have the potential to exhibit increased
feeding intensity compared with continuously fed controls, resulting in
the acceleration of growth; this phenomenon is defined as compensatory
growth [[40]8], which is known to occur in a wide range of fish
species, such as Atlantic salmon (Salmo salar) [[41]9], barramundi
(Lates calcarifer) [[42]10], channel catfish (Ictalurus punctatus)
[[43]11], tongue sole (Cynoglossus semilaevis) [[44]12], European
minnow (Phoxinus phoxinus) [[45]13], and gibel carp (Carassius auratus
gibelio) [[46]14]. However, the regulatory mechanisms governing this
phenomenon have not been thoroughly elucidated in fish.
Musculature provides the largest store of protein in the body of fish;
muscle proteins are the most important energy source and are
preferentially mobilized in vital organs during long-term food
deprivation [[47]15]. Furthermore, the muscle is the main edible tissue
of most fish species and accounts for at least 50% of the body weight
in most commercial fish species [[48]16]. Previous studies have shown
that muscle may play an important role in maintaining normal metabolism
during dietary restriction due to an increase in protein degradation of
the white muscle during starvation [[49]15]. The investigation of the
morphology and molecular changes in muscle during food deprivation can
facilitate a better understanding of the starvation response and
compensatory growth mechanisms.
Spinibarbus hollandi (also called army fish) is an endemic Cyprinidae
species in southeastern China and is primarily distributed in
Guangdong, Guangxi, Hunan, Hubei, Fujian, and Anhui Provinces. This
fish is omnivorous, is easy to rear, and has already received
increasing attention owing to its high nutritional and medicinal value
[[50]17]. However, the low growth rate seriously restricts the
production efficiency and popularization of S. hollandi [[51]17]. In
addition, this fish species is sensitive to external stimuli,
environmental changes and artificial stimulation, which can easily
result in fasting for several days. In our previous work, we attempted
to enhance the growth rate of S. hollandi by improving the rearing
conditions and crossbreeding. The molecular markers associated with
growth traits were developed in S. hollandi [[52]17, [53]18]. However,
studies on the effects of fasting and refeeding on the growing status
of this species are deficient. The underlying physiological responses
and gene expression changes associated with growth depression due to
feed restriction have not been elucidated.
In the present study, the growth compensation phenomenon was observed
in S. hollandi. To understand the regulatory mechanisms underlying the
starvation response and growth compensation, comparative transcriptome
analyses on skeletal muscle of different feeding statuses were
performed in S. hollandi. The results showed that muscle overgrowth is
an important reason for growth compensation. Therefore, a histological
analysis of muscle was carried out to verify the conclusions obtained
from transcriptome data.
Results
As shown in Fig. [54]1a, a total of 210 mixed-sex, full-sib S. hollandi
were randomly divided into a test group and a control group. For the
test group, fish were first deprived of food for 7 days and then fed
twice a day to apparent satiation for 33 days. For the control group,
fish were fed twice a day continuously for 40 days (Fig. [55]1a). Both
groups were sampled sequentially on days 0, 7, 14 and 40, and the
growth traits, including weight, body length, total length, thickness
and height, were measured. The muscle tissue transcriptomes were
profiled by RNA-sequencing (RNA-seq) at day 7 for the control group and
test group (after 7 days of fasting) and 14 for the test group (after
7 days of refeeding).
Fig. 1.
[56]Fig. 1
[57]Open in a new tab
Experimental procedure, growth curves. a Illustration of the experiment
and sample processes performed in this study. Red asterisks indicate
that groups were used for RNA-seq; green asterisks indicate that groups
were used for qRT-PCR; the horizontal axis indicates the time of
experiment. b–f Growth curve of body weight, total length, body length,
body thickness and body height, respectively. Asterisks indicate
significant differences between the control and test groups (*
p < 0.05; Student’s t-test)
Compensatory growth after fasting-refeeding treatment
After fasting, with the exception of body thickness, the body weight,
total length, body length, and body height were decreased and
significantly lower than those of the control group (p < 0.05 Student’s
t-test; Fig. [58]1). After 7 days of refeeding, no remarkable
difference could be detected between the test group and the control.
Finally, at the end of the experiment, all growth traits were recovered
(Fig. [59]1). Taken together, these results suggest effective growth
compensation in S. hollandi after fasting-refeeding treatment. The
daily gains of growth traits can be found in Additional file [60]1:
Figure S1.
Sequencing data and de novo assembly
The variation among individuals was minimized by mixing equal amounts
of RNA from five samples in the same group. For each group, three
replicated mixed RNA pools were generated and used for cDNA library
preparation and RNA-seq thereafter. A total of 4.63 × 10^8 raw reads
(150 bp) were obtained from nine cDNA libraries. After removing the
low-quality sequences, approximately 4.45 × 10^8 clean reads with 66.71
Gb sequences were generated. Then, 355,268 transcripts (ranging from
201 to 27,096 bp) were generated through de novo assembly. The longest
transcript of a gene was regarded as a unigene for further analyses. A
total of 156,735 unigenes with 103.5 Mb sequences were obtained with an
average length of 660 bp. The N50 and N90 lengths were 1061 and 224 bp,
respectively.
Annotation and functional analysis of muscle unigenes
Among all unigenes, 142,918 (91.18%) could be annotated in at least one
database of non-redundant protein (Nr), non-redundant nucleotide (Nt)
NCBI database, Pfam, KOG, Swiss-Prot, KEGG, and GO, with 10,438 (6.65%)
unigenes annotated in all these databases. Approximately 54,408
(34.71%) unigenes were annotated in the Nr database, of which nearly
66.5% had the highest similarity with Danio rerio followed by Astyanax
mexicanus (5.8%), Clupea harengus (2.5%), Larimichthys crocea (1.8%),
and Oncorhynchus mykiss (1.7%).
The functional prediction and classification of all unigenes were
performed against the GO database. A total of 42,174 (26.91%) unigenes
were classified into 55 GO terms, including 10 molecular function, 20
cellular components, and 25 biological process terms. Cellular process,
binding, metabolic process, single-organism process, and catalytic
activity were the five most abundant functional terms at the second GO
level (Fig. [61]2a). Furthermore, the assembled unigenes were aligned
to the COG database for phylogenetic classification. A total of 16,978
(10.83%) unigenes were divided into 26 functional categories (Fig.
[62]2b); the largest category was signal transduction mechanisms with
3198 unigenes followed by general function prediction only (2495);
posttranslational modification, protein turnover, chaperones (1773);
and cytoskeleton (1343). The biological pathways were analyzed by
annotating all assembled unigenes against the KEGG database, and 29,841
(19.04%) unigenes were matched in five categories, including organismal
systems (11,222; 37.61%), environmental information processing (7138;
23.92%), cellular processes (5912; 19.81%), metabolism (5089; 17.05%),
and genetic information processing (3521; 11.80%). These categories
contained 232 pathways with 1 to 1147 unigenes that were involved in an
individual pathway. Among all KEGG pathways, the PI3K-Akt signaling
pathway, focal adhesion, regulation of actin cytoskeleton, endocytosis,
and MAPK signaling pathway were significantly enriched with more than
800 unigenes (Fig. [63]2c).
Fig. 2.
[64]Fig. 2
[65]Open in a new tab
Annotation and function analysis of unigenes in S. hollandi. a
Classification of the assembled unigenes in the Gene Ontology (GO)
database; b Classification of the assembled unigenes in the Cluster of
Orthologous Groups (COG) database; c Classification of the assembled
unigenes in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database
Identification of DEGs in different feeding conditions
A total of 4503 unigenes showed significant differential expression
among the control, fasting and refeeding groups. Of these
differentially expressed genes (DEGs), 2422 were found between the
control and fasting groups, 110 were found between the control and
refeeding groups, and 3970 were found between the fasting and refeeding
groups (Fig. [66]3a, b and Additional file [67]2: Table S2). The
overall expression profiles of control group and refeeding group were
similar (R^2 = 0.95, p < 2.2e-16; only the 4503 DEGs were considered),
and the DEGs identified from fasting compared to control comparison and
fasting compared refeeding comparison were largely overlapped (Fig.
[68]3a, b). We mainly focused on genes significantly changed in fasting
group compared to control and genes significantly changed in refeeding
group compared to control in our following analysis.
Fig. 3.
[69]Fig. 3
[70]Open in a new tab
Overall transcriptome profiles of all DEGs. a Heatmap of all DEGs.
Green and red indicate the low and high expression levels,
respectively. C1, C2 and C3 indicate the control group, F1, F2 and F3
indicate the fasting group, and R1, R2 and R3 indicate the refeeding
group. Cluster1 contains genes significantly down regulated in fasting
group compared to control, with the exception of genes also
significantly changed in refeeding group compared to control; Cluster2
contains genes significantly down regulated in fasting group compared
to refeeding group, with the exception of genes also significantly
changed in refeeding group compared to control; Cluster3 contains genes
significantly up regulated in refeeding group compared to control;
Cluster4 contains genes significantly down regulated in refeeding group
compared to control; Cluster5 contains genes significantly up regulated
in fasting group compared to control, with the exception of genes also
significantly changed in refeeding group compared to control; Cluster6
contains genes significantly up regulated in fasting group compared to
refeeding group, with the exception of genes significantly changed in
refeeding group compared to control. The full list of these DEGs can be
found in Additional file [71]2: Table S2. b UpSet chart showing
intersection between different DEG sets from various comparisons. The
vertical bar plot reports the intersection size, the dot plot reports
the set participation in the intersection, and the horizontal bar plot
reports the set sizes
Analysis of DEGs after fasting in S. hollandi
After 7 days of fasting, we detected 2422 DEGs, which included 1510
up-regulated and 912 down-regulated genes (Additional file [72]2: Table
S2). Approximately 331 up-regulated DEGs mapped to 284 KEGG pathways,
26 of which were significantly enriched (corrected p-value < 0.05;
Fig. [73]4a). The top five significantly enriched pathways were the
AMPK signaling pathway (ko04152), insulin resistance (ko04931), insulin
signaling pathway (ko04910), fatty acid degradation (ko00071), and
adipocytokine signaling pathway (ko04920). Many metabolism-relevant
genes were significantly up-regulated in the muscle after 7 days of
fasting (Fig. [74]4b). The genes associated with lipid metabolism
(PNPLA2, SLC27A1, SLC27A3, HADH, HADHA, LPIN1, ACACB1, ACACB2, CPT1A,
and CPT1B), protein degradation and metabolism (USP19, RNF25, USP25,
USP28, UBE2A, PSMB7, and PSMG3), and glycometabolism (PPP1CB, PFKFB1,
GSK3B, and GYS) were significantly up-regulated. In addition, some
genes associated with signal transduction (FOXO3, FOXO4, PIK3, and
ARS1) were up-regulated during fasting. To validate the results from
RNA-seq, the expression profiles of RNF25 and SLC27A3 were analyzed by
using quantitative PCR (qPCR). The results were similar to the RNA-seq
results, in which the expression of these two genes was significantly
increased after 7 days of fasting and then returned to normal levels
after refeeding (Fig. [75]4c).
Fig. 4.
[76]Fig. 4
[77]Open in a new tab
Analysis of up-regulated differentially expressed genes (DEGs) during
fasting and refeeding. a classification of the up-regulated DEGs in the
Kyoto Encyclopedia of Genes and Genomes (KEGG) database; b expression
profiles of the parts of up-regulated DEGs from the RNA-seq result; c
RNF25 and SCL27A3 expression profiles in the control and test groups
from the qRT-PCR result. Asterisks indicate significant differences
between the control and test groups (* p < 0.05; Student’s t-test)
A total of 316 down-regulated DEGs were mapped to 243 pathways in the
KEGG database, of which 26 pathways (Fig. [78]5a) were significantly
enriched (corrected p-value < 0.05). The top five significantly
enriched pathways were cell cycle (ko04110), protein digestion and
absorption (ko04974), ECM-receptor interaction (ko04512), PI3K-Akt
signaling pathway (ko04151), and phagosome (ko04145). The expression
profiles of some of the down-regulated DEGs from RNA-seq are shown in
Fig. [79]5b. Genes associated with the cell cycle (HRAS, CDK1, CDK2,
CDC6, FGF6, CCNA2, Wee1, and CCNB1), DNA replication (EIF4E1A, PCNA,
POLD1, MCM1, MCM2, MCM3, MCM4, MCM5, and MCM6), extracellular matrix
(ITGA4, COL1A, LAMC1, FN1, TN, and DAG1), protein synthesis (RPN2,
GCS1, HSPA5, PDIA3, PDIA4, LMAN1, and ERLEC1), and immune and stress
tolerance (ARHGEF2, TUBA, TUBB, FYN, MHCII, TAP1, HSP70, HSP90, and
CTSB) were significantly down-regulated. The expression of CDK1 and
MHCII in the control and test groups was analyzed using qRT-PCR (Fig.
[80]5c). The expression of CDK1 was significantly down-regulated after
7 days of fasting, and then returned to normal levels after refeeding.
MHCII was significantly down-regulated after 7 days of fasting, and its
expression gradually increased.
Fig. 5.
[81]Fig. 5
[82]Open in a new tab
Analysis of down-regulated differentially expressed genes (DEGs) during
fasting and refeeding. a classification of the down-regulated DEGs in
the Kyoto Encyclopedia of Genes and Genomes (KEGG) database; b
expression profiles of some down-regulated DEGs from the RNA-seq
result; c the expression of CDK1 and MHCII in the control and test
groups from the qRT-PCR result. Asterisks indicate significant
differences between the control and test groups (* p < 0.05; Student’s
t-test)
Analysis of DEGs after refeeding
After refeeding, we detected a total of 3970 DEGs between the fasting
and refeeding groups, of which 1805 were up-regulated and 2165 were
down-regulated (Additional file [83]2: Table S2). Compared with the
control group, a total of 110 genes were significantly changed,
including 94 DEGs and 16 DEGs that were up-regulated and
down-regulated. It’s worth noting that among the 94 up regulated genes
in the refeeding group, 38 of them increased in one or two fasting
samples too. These genes, thus, may not related to the compensatory
growth. In the remaining DEGs, 9 genes involved in myofiber structure
(ACTC1, ACT2, ACTA1, MHC, MLC1, MYL2, TM1, TNT, and TNNT3) were
significantly up-regulated (Additional file [84]1: Figure S2 and
Table [85]1). In addition, genes involved in collagen (COL3A1, COL1A2,
and COL5A2), ribosomal protein (RPL22L1), protein synthesis (INFB), and
energy metabolism (ATPD, GAPDH, ND2, and PDHB) were also up-regulated
(Table [86]1).
Table 1.
Up-regulated differentially expressed genes (DEGs) after refeeding
Gene_ID log2FC padj Swissprot Description Symbol
TRINITY_DN53185_c1_g5 14.71 5.04E-14 Uncharacterized protein ORF91
TRINITY_DN28038_c0_g1 11.91 2.30E-10 Cell division protein FtsZ FTSZ
TRINITY_DN53185_c1_g3 11.67 1.31E-12 Uncharacterized protein ORF91
TRINITY_DN40074_c2_g1 11.21 1.49E-08 Sarcoplasmic calcium-binding
protein 1
TRINITY_DN51715_c1_g6 10.96 6.10E-11 Oligopeptide transport ATP-binding
protein OppD OPPD
TRINITY_DN46704_c4_g3 10.64 5.38E-07 Oligopeptide transport ATP-binding
protein OppD OPPD
TRINITY_DN39439_c1_g1 10.60 4.89E-08 Myosin heavy chain, muscle MHC
TRINITY_DN51457_c0_g4 10.56 9.76E-06 Arginine kinase
TRINITY_DN44733_c0_g1 10.38 7.90E-08 Myosin light chain alkali MLC1
TRINITY_DN36404_c0_g1 10.34 5.91E-11 Collagen alpha-1(III) chain COL3A1
TRINITY_DN36624_c0_g1 10.28 8.79E-07 Myosin regulatory light chain 2
TRINITY_DN62802_c0_g1 10.10 2.75E-05 Ribosomal RNA small subunit
methyltransferase H RSMH
TRINITY_DN46916_c1_g3 9.53 2.78E-07 Tropomyosin TM1
TRINITY_DN29972_c1_g3 9.50 4.91E-05 ATP synthase subunit beta ATPD
TRINITY_DN75810_c0_g1 9.44 1.72E-03 DNA-directed RNA polymerase subunit
beta’ RPOC
TRINITY_DN46916_c1_g2 9.26 1.53E-09 Troponin I
TRINITY_DN51457_c0_g2 9.13 2.81E-02 Cytochrome c oxidase subunit 1 COI
TRINITY_DN29188_c0_g1 9.09 1.09E-06 Putative transposase InsK for
insertion sequence element IS150 INSK
TRINITY_DN30901_c0_g1 8.90 1.08E-04 Membrane protein insertase YidC
YIDC
TRINITY_DN14841_c0_g1 8.88 4.80E-03 L-arabinose transport ATP-binding
protein AraG ARAG
TRINITY_DN51715_c1_g8 8.76 1.02E-03 Oligopeptide transport ATP-binding
protein OppD OPPD
TRINITY_DN55417_c1_g2 8.73 5.18E-03 Craniofacial development protein 2
CFDP2
TRINITY_DN6518_c0_g2 8.67 6.49E-04 tRNA-specific 2-thiouridylase MnmA
MNMA
TRINITY_DN54848_c1_g1 8.58 1.22E-02 Cingulin CGN
TRINITY_DN41914_c0_g2 8.55 8.58E-04 von Willebrand factor VWF
TRINITY_DN33939_c0_g1 8.53 1.43E-07 Variant surface antigen C VLPC
TRINITY_DN53727_c0_g1 8.40 2.78E-07 Troponin T TNT
TRINITY_DN42223_c1_g1 8.36 4.80E-07 Actin, alpha cardiac muscle 1 ACTC1
TRINITY_DN26420_c0_g1 8.06 1.21E-03 Fructose-bisphosphate aldolase ALD
TRINITY_DN27809_c1_g2 8.00 2.00E-02 50S ribosomal protein L6 RPLF
TRINITY_DN50962_c2_g1 7.95 7.78E-03 Cytochrome c oxidase subunit 3
COIII
TRINITY_DN50547_c1_g2 7.92 4.03E-02 Collagen alpha-2(I) chain COL1A2
TRINITY_DN29972_c1_g4 7.81 9.29E-03 Elongation factor Tu TUF
TRINITY_DN21598_c0_g2 7.80 2.43E-02 Chaperone protein DnaK DNAK
TRINITY_DN14984_c0_g1 7.79 2.54E-02 Pyruvate dehydrogenase E1 component
subunit beta PDHB
TRINITY_DN4314_c0_g1 7.78 3.33E-02 Putative permease MJ0326 MJ0326
TRINITY_DN71455_c0_g1 7.73 2.15E-04 Membrane-associated lipoprotein
UU045
TRINITY_DN27456_c0_g2 7.69 1.04E-03 Troponin C, isoform 1
TRINITY_DN49873_c2_g2 7.67 2.37E-03 Cytochrome c oxidase subunit 1
MT-CO1
TRINITY_DN57252_c0_g1 7.65 8.30E-05 Putative ABC transporter
ATP-binding protein MG187 homolog MPN_134
TRINITY_DN76701_c0_g1 7.60 5.18E-03 Pyruvate dehydrogenase E1 component
subunit beta PDHB
TRINITY_DN9860_c0_g1 7.57 2.95E-04 Ascorbate-specific permease IIC
component UlaA ULAA
TRINITY_DN72099_c0_g1 7.43 1.14E-03 Lon protease LON
TRINITY_DN37203_c0_g1 7.42 1.02E-03 Uncharacterized protein ORF91
TRINITY_DN50867_c4_g2 7.39 3.41E-02 Collagen alpha-2(V) chain COL5A2
TRINITY_DN39233_c1_g2 7.17 6.64E-03 Putative uncharacterized
transposon-derived protein F52C9.6 F52C9.6
TRINITY_DN26948_c0_g1 7.15 6.88E-03 Troponin C, isotype gamma
TRINITY_DN57481_c0_g1 7.12 8.41E-03 30S ribosomal protein S2 RPSB
TRINITY_DN42492_c1_g7 7.12 7.34E-03 Glyceraldehyde-3-phosphate
dehydrogenase
TRINITY_DN76302_c0_g1 7.09 1.22E-02 Uncharacterized protein PF11_0207
PF11_0207
TRINITY_DN20261_c0_g1 6.98 1.59E-02 NADH-ubiquinone oxidoreductase
chain 2 MT:ND2
TRINITY_DN31759_c0_g1 6.96 4.28E-02 Translation initiation factor IF-2
INFB
TRINITY_DN38000_c0_g1 6.92 2.90E-02 RNA-directed DNA polymerase from
mobile element jockey POL
TRINITY_DN66334_c0_g1 6.80 4.92E-02 PTS system glucose-specific EIICBA
component PTSG
TRINITY_DN50552_c0_g2 3.93 2.48E-04 Collagen alpha-2(I) chain COL1A2
TRINITY_DN41454_c2_g1 3.02 2.00E-02 Actin, alpha skeletal muscle ACTA1
TRINITY_DN39818_c0_g2 2.52 4.02E-02 Actin, alpha skeletal muscle 2 ACT2
TRINITY_DN37767_c0_g1 2.23 2.36E-02 Thymosin beta TMSB
TRINITY_DN48071_c0_g2 1.99 3.45E-03 60S ribosomal protein L22-like 1
RPL22L1
TRINITY_DN51452_c2_g2 1.98 7.99E-03 Troponin T, fast skeletal muscle
TNNT3
TRINITY_DN50109_c0_g2 1.94 4.60E-02 Endothelial lipase LIPG
[87]Open in a new tab
P-value <0.05 indicated different expression between control and
fasting-refeeding groups
Three genes, ACT2, ACTA1, and TNNT3, were used for expression trend
analysis between the control and test groups. The ACT2 expression
significantly decreased after fasting for 7 days (p = 0.013; Student’s
t-test, df = 4) compared with the control group at the same point and
then sharply increased and became significantly higher than that in the
control group with refeeding for 7 days; after refeeding for 33 days,
the ACT2 expression decreased, but it was still significantly higher
than that in the control group (p = 1.0 × 10^− 5; Student’s t-test,
df = 4) (Fig. [88]6a). The expression profile of ACTA1 had the same
pattern as that of ACT2: after fasting, its expression significantly
decreased, whereas after refeeding, its expression significantly
increased and then gradually decreased (p = 8.05 × 10^− 4; Student’s
t-test, df = 4) (Fig. [89]6b). The expression change of TNNT3 was
similar to ACTA1 and ACT2; however, after refeeding for 33 days, no
significant difference was noted in its expression between the control
and refeeding groups (Fig. [90]6c).
Fig. 6.
[91]Fig. 6
[92]Open in a new tab
Expression profiles of some of the genes associated with myofibers
under prolonged refeeding. a, b and c indicated the expression profiles
of ACT2, ACTA1 and TNNT3, respectively; Asterisks indicate significant
differences between the control and test groups (* p < 0.05; Student’s
t-test)
qRT-PCR validation of DEGs from RNA-Seq
A total of ten DEGs of different functions were randomly selected to
verify the RNA-seq results using quantitative real-time PCR (qRT-PCR),
including genes involved in protein degradation (RNF25), lipid
metabolism (SLC27A3), cell cycle (CDK1 and TMSB), immunity (MCHII and
TAP1), DNA replication (MCM4) and myofiber structure (ACTA1, ACT2 and
TNNT3). The expression changes of these genes were analyzed under
fasting and refeeding conditions. Under both fasting and refeeding
conditions, the gene expression changes obtained from qRT-PCR were
remarkably consistent with those obtained from the RNA-Seq result, with
R^2 values of 0.9145 and 0.9282 (Fig. [93]7), respectively. The
analyses confirmed the reliability and accuracy of the RNA-seq result.
Fig. 7.
[94]Fig. 7
[95]Open in a new tab
Correlation between the results of RNA-seq and qRT-PCR. a and b
represent the correlations between the control and test group (after
fasting) and between the control and test group (after refeeding),
respectively. The X-axis numbers represent the log[2] (fold-change)
values from the RNA-seq results. The Y-axis numbers represent the
log[2](fold-change) values from the qRT-PCR results
Changes in myofibers during fasting and refeeding periods
The dimensions of myofibers were analyzed using histology. The myofiber
sections of the control groups are shown in Fig. [96]8a–c and those of
the test groups are shown in Fig. [97]8d–f. The shortest and longest
diameters of myofibers were measured (Fig. [98]8g, h). After 7 days,
the shortest and longest diameters of the test group were 32.86 ± 0.98
and 36.30 ± 1.07 μm, respectively, which were significantly shorter
than those of the control group (37.80 ± 1.96 and 42.14 ± 2.09 μm,
p = 0.014 and p = 0.026; Student’s t-test). After 7 days of refeeding,
the mean longest diameter of the test group of the refeeding group was
still significantly shorter than that of the control group (p = 0.043;
Student’s t-test); however, no significant difference was noted between
their shortest diameters (p = 0.203; Student’s t-test). In addition, at
the end of 40 days, no significant differences were noted in both
diameters (p = 0.942 and p = 0.924, Student’s t-test).
Fig. 8.
[99]Fig. 8
[100]Open in a new tab
Changes in myofibers (a-f) indicate myofiber cross-sections in the
control group at days 7, 14, 40 and the test group at day 7 (after
7 days fasting), 14 (after 7 days refeeding), 40 (after 33 days
refeeding), respectively; g and h indicate the longest and shortest
diameters of cross-section in the control and test groups,
respectively. Asterisks indicate significant differences between the
control and test groups (* p < 0.05; Student’s t-test; n = 5);
bars = 50 μm
Discussion
In this study, a compensatory growth phenomenon was observed in S.
hollandi that were refed after fasting for 7 days. During fasting, the
growth of S. hollandi was inhibited; after 33 days of refeeding, the
weight of the fasted fish almost recovered to the normal weight of the
control group. In S. hollandi, starvation increased the expression of
genes involved in fat, protein, and carbohydrate metabolism but reduced
the expression of genes associated with the cell cycle, DNA
replication, and immune and cellular structures. The compensatory
growth seemed to mainly result from muscle overgrowth; many genes
involved in myofiber development were significantly upregulated.
Histological analyses of muscle suggested that starvation inhibited
myofiber growth but that refeeding after fasting induced myofibril
overgrowth. Fasting also inhibited the growth of S. hollandi overall;
the body weight of fasted fish even decreased slightly during fasting.
A reduction in body mass may be the most obvious response to
starvation.
The body weight reduction after fasting has been reported in several
fish species, including Morone saxatilis [[101]19], Stizostedion
vitreum [[102]20], Cynoglossus semilaevis [[103]12], and Oncorhynchus
mykiss [[104]21]. Refeeding could accelerate the growth of S. hollandi
after a period of fasting; this phenomenon is known as compensatory
growth and might be affected by feed intake and food utilization
efficiency [[105]22, [106]23]. This has been reported in many fish
species, such as Ctenopharyngodon idella [[107]24], Oncorhynchus mykiss
[[108]21], Rutilus caspicus [[109]25], and Megalobrama amblycephala
[[110]26]. Although starvation and compensatory growth commonly exist
in natural and production environments, the molecular mechanisms
regulating the growth rates of skeletal muscle under both fasting and
refeeding conditions have not been elucidated. The next-generation
sequencing technology revolutionized the field of genomics; RNA-Seq can
detect the transcriptome of the non-model species without known genomic
information [[111]27].
Through comparative transcriptome analysis, most of the up-regulated
DEGs under starvation were involved in lipid metabolism, protein
degradation and metabolism, and glycometabolism. PNPLA2 is known to be
important for triglyceride hydrolysis, and its up-regulation might
enhance the hydrolysis of triglycerides and produce free fatty acids
for other tissues in response to starvation [[112]28]. SLC27A (SLC27A1
and SLC27A3) is associated with fatty acid transport [[113]29], and an
increase in these genes may contribute to the mobilization of fat. HADH
encodes an enzyme called 3-hydroxyacyl-CoA dehydrogenase, which is
important for the beta-oxidation of short chain fatty acids in the
mitochondria [[114]30]; its increase may contribute to mobilizing the
stored fatty acids to provide the necessary energy for the activity of
organisms. CPT1s participate in the movement of acylcarnitine from the
cytosol into the intermembrane of mitochondria [[115]31], and its
up-regulation contributes to fatty acid oxidation. ACACBs (ACACB1 and
ACACB2) serve as regulators of mitochondrial fatty acid oxidation
through the inhibition of carnitine palmitoyltransferase 1 by its
product malonyl-CoA [[116]32], which reduces the fatty acid oxidation
rate of organisms. Lipin-1 has phosphatidate phosphatase activity and
plays a pivotal role in the maintenance of adipocytes [[117]33]. The
up-regulation of these genes may prevent excessive loss of fat during
starvation conditions. During fasting, several up-regulated DEGs
(USP19, RNF25, USP25, USP28, UBE2A, PSMB7, and PSMG3) are involved in
the ubiquitin-proteasome system, which is one of the major protein
degradation systems [[118]34]. In addition, many genes were
significantly enriched in amino acid catabolism-related KEGG pathways,
including arginine and proline metabolism (ko00330), and valine,
leucine, and isoleucine degradation (ko00280). The up-regulation of
these genes indicated that fasting could accelerate the consumption of
proteins and amino acids. PPP1CB encodes one of the three catalytic
subunits of protein phosphatase 1, which is a serine/threonine-specific
protein phosphatase known to be involved in glycogen metabolism, lipid
metabolism, replication, pre-mRNA splicing and protein synthesis
[[119]35]. However, the direct connection between this gene and
starvation response has not been determined. PFKFB1 is associated with
the regulation of the synthesis and degradation of
fructose-2,6-biphosphate, which is a rate-limiting enzyme in glucose
homeostasis. This protein activates the glycolysis pathway and inhibits
the gluconeogenesis pathway to produce more energy for organisms
[[120]36], its up-regulation may contribute to the regulation of
glucose synthesis and metabolism. GSK3B and GYS are pivotal enzymes in
glycogen metabolism [[121]37, [122]38], which may be essential for the
response to fasting in S. hollandi. However, the function of the two
up-regulated genes is opposite, possibly because glycogen may be a
buffer of glucose; when excessive stored energy is transformed into
carbohydrates, glucose may be transformed into glycogen for temporary
storage; when glucose concentration decreases, glycogen may be
converted back into glucose. Up-regulated DEGs related to lipid
metabolism, protein degradation and metabolism, and glycometabolism
suggested that starvation increased the capacity to catabolize fats,
proteins, and carbohydrates in S. hollandi. Similar results were found
in other fish species: the genes related to fat and carbohydrate
catabolism were up-regulated during fasting in large yellow croaker
[[123]7], and the genes associated with catabolic pathways and beta
oxidation of fatty acids were significantly up-regulated in the muscle
of rainbow trout after fasting for 1 month [[124]4].
In addition to the up-regulated DEGs, a total of 912 genes were
down-regulated by fasting. Most of these genes were involved in the
cell cycle, DNA replication, extracellular matrix, protein synthesis,
and immune and stimulus responses. A mitotic cell cycle is a complex
process that is regulated by many factors. Cyclin (CCNA2 and CCNB1) can
regulate cell cycle progress by interacting with cyclin-dependent
kinases (CDK1 and CDK2). Wee1 is a nuclear kinase that can prevent
cells from undergoing mitosis by inhibiting CDK1; it plays a critical
role in the maintenance of normal mitosis during cell division
[[125]39, [126]40]. HRAS is a GTPase involved in the regulation of cell
division [[127]41]. F6F is a fibroblast growth factor (FGF) family
member that possesses broad mitogenic and cell survival activities and
is known to regulate muscle regeneration or differentiation [[128]42].
DNA replication is a vital event in the mitotic cell cycle and showed
signs of down-regulation by fasting. A mini-chromosome maintenance
(MCM) complex formed by MCM proteins with DNA helicase activity might
be involved in the formation of replication forks and recruitment of
other DNA replication-related proteins [[129]43]. PCNA is a cofactor of
DNA polymerase delta, which acts as a scaffold in recruiting proteins
involved in DNA replication [[130]44]. POLD1 encodes the catalytic
subunit of the DNA polymerase delta complex [[131]45], and CDC6 is an
essential regulator of DNA replication and plays important roles in the
transition from the S phase to the M phase of cell cycle progression
[[132]46]. Similar to our findings in S. hollandi, several genes
associated with cell cycle and DNA replication were shown to be
significantly down-regulated in O. mykiss during fasting [[133]4,
[134]21]. The extracellular matrix comprises a complex mixture of
structural and functional macromolecules and is associated with many
cellular processes, including growth, differentiation, morphogenesis,
survival, and homeostasis [[135]47]. The genes related to the
extracellular matrix (ITGA4, COL1A, LAMC1, FN1, TN, and DAG1) were
ulated and might reduce the growth and differentiation of myocytes
during the fasting period; in addition, several genes associated with
the cytoskeleton were down-regulated. Protein synthesis is essential
for cellular processes. Genes associated with protein synthesis and
modification pathways were down-regulated under fasting conditions,
which might hinder the growth of S. hollandi. Genes associated with
immune and stress tolerance were also down-regulated; heat shock
proteins (HSPs) belong to the molecular chaperone family and play
important roles in protein folding, as well as in protecting cells from
stress. FYN is associated with T-cell signaling [[136]48]; CTSB is a
lysosomal cysteine protease associated with immunity [[137]49]. TAP1
and MHCII are related to specific immunity [[138]50] and are important
parts of the immune system. The down-regulation of these DEGs suggested
that fasting could weaken immunity and might increase morbidity in S.
hollandi when threatened by pathogenic microorganisms. Previous studies
have also shown that many genes related to immune and antimicrobial
peptides were down-regulated in the liver following starvation in
Atlantic salmon (Salmo salar) [[139]51].
After refeeding, many genes associated with the structure of myofibers
were up-regulated. Their expression levels were significantly higher
than those in the control group. The sarcomere primarily consists of
actin, myosin, tropomyosin, and troponin [[140]52]; the overexpression
of these proteins may promote muscle growth [[141]53–[142]55].
Collagens are major components of the perimysium and are essential for
the stabilization of the extracellular matrix of muscle [[143]56]. In
trout, it was also observed that genes associated with myofiber and
muscle remodeling were up-regulated 7 to 36 days post-refeeding
[[144]4], and the same research team suggested that compensatory muscle
growth response resulted from the stimulation of hypertrophy [[145]21].
Furthermore, several genes associated with energy metabolism (ATPD,
GAPDH, ND2, and PDHB) were up-regulated; they might be required for
meeting the energy requirement for muscle growth. In general, these
findings indicated that the accelerated biosynthesis of myofibers
resulted in compensatory growth following refeeding in S. hollandi. In
histology analysis, the significant difference in the dimensions of
myofibers showed that starvation can inhibit the growth of myofibers,
which was in accord with results obtained from transcriptome analysis.
After refeeding, the overgrowth of myofibers was consistent with the
up-regulated expression levels of genes associated with muscle
structure. Based on the above results, we suggest that muscle
overgrowth may play an important role in the compensatory growth of
fish.
Conclusions
In the present experiment, we carried out an analysis of the
transcriptome profiles of S. hollandi muscle under different breeding
conditions. During fasting, genes involved in fat, protein, and
carbohydrate metabolism were up-regulated, which indicated that the
stored energy was mobilized. On the other hand, the expression levels
of genes associated with the cell cycle, DNA replication, and cellular
structures decreased, which suggested that growth might be inhibited by
starvation. After refeeding, most of the genes down-regulated during
fasting were recovered, while many genes associated with the structure
of myofibers were up-regulated. Histological analyses of muscle also
showed muscle overgrowth after refeeding. The results indicated that
muscle hypertrophy may play an important role in compensatory growth
after fasting refeeding. The results of these experiments may help to
elucidate the mechanisms underlying the starvation response and
compensatory growth.
Methods
Sample preparation and fasting experiments
The mixed-sex, full-sib experimental fish were obtained from Shaoguan
Fisheries Research Institute in Guangdong, China. A total of 210 fish
with an approximate weight of 1.0 g were randomly and equally assigned
to seven aquariums. As Spinibarbus hollandi is highly sensitive to the
external stimulus, which will lead to not ingesting for several days,
one aquarium was sampled only once in our experiment. Thus, among the
seven aquariums, one was used for the measurements of the initial
growth traits, and the remaining six aquariums were equally divided
into test and control groups, corresponding to 7, 14, and 40 days. To
minimize the effects introduced by different aquariums, we maintained
all aquariums in the same conditions, including 100 L of
charcoal-dechlorinated and continuous flow-through tap water
(pH 7.0 ± 0.1) with forced-air aeration, and the temperature of the
water was 26 °C with a photoperiod of 14:10 h (light:dark). The fish
were manually fed twice a day to apparent satiation at 7:00 and
17:00 h, with a 35% protein/4% fat commercial diet (QiCai Pet Products
Co., Ltd., Guangzhou, China) for 2 weeks. Fish served as control groups
and were fed to satiation every day as mentioned above. For the test
groups, fish were first deprived of food for 7 days and then fed twice
per day for 33 days. For aquariums used for 7-day continuously feeding,
7-day fasting and 7-day refeeding after fasting, 15 fish were used for
RNA-seq, 3 fish were used for qRT-PCR, 5 fish were used for
histological analysis, and redundant 7 fish were used for prevent
accidental death. For other aquariums, 3 fish were used to qRT-PCR, 5
fish were used to histological analysis, redundant fish were used to
keep same breeding density in all aquariums and prevent accidental
death. Eight fish were randomly selected for measure of growth traits
in each aquarium. After experiments, the remained fish were bred
continuously for further studies. Both groups were sampled sequentially
on days 0, 7, 14, and 40. The fish were put into water with an overdose
(100 ppm) of eugenol (Sangon Biotech Co., Ltd., Shanghai, China) for
10 min to anesthetize them before dissection, and their body weights,
body lengths, total lengths, body thicknesses and body heights were
measured. Daily gain of body weight was also calculated using the
following formula:
[MATH: R=m2−m1/t :MATH]
The R indicated the daily body weight gain ((g/day), the m1 indicated
the initial weight (g), the m2 indicated the final weight after
treatment (g), and t indicated the period of treatment (day).
For RNA sequencing, The muscle tissues were rapidly sampled from the
same location of dorsal white muscle under dorsal fin from all fish
without considering dorsal side, immediately frozen in liquid nitrogen,
and stored at − 80 °C for further testing. At the same time, another
three and five fish were sampled as the above methods for qRT-PCR and
histology analysis, respectively. After the experiment, wherever
possible, most remaining experimental fish were retained for other
research.
RNA isolation
Total RNA was extracted from approximately 80 mg of muscle tissue using
RNAiso reagents (Takara, Dalian, China) according to the manufacturer’s
instructions. The quantity and quality of RNA samples were determined
using a microplate spectrophotometer (BioTek Company, USA) followed by
electrophoresis on a 1% agarose gel. The RNA samples were stored at
− 80 °C until further use.
Library preparation and sequencing
The RNA samples prepared above were used for RNA-seq. The variation
among individuals was minimized by mixing equal amounts of RNA from
five samples in the same group to generate three replicated mixed RNA
pools. A total of nine replicated mixed RNA samples were used for cDNA
library preparation. RNA-seq libraries were prepared using NEBNext
UltraTM RNA Library Prep Kit (NEB, USA) following the manufacturer’s
protocols. Briefly, mRNA was purified from total RNA and was broken to
fragmentations using divalent cations. First strand cDNA was
synthesized using reverse transcriptase (MMLV), and second strand cDNA
was synthesized using DNA polymerase I, and the remained mRNA were
subsequently removed using RNase H. cDNA fragments were ligated with
adaptor and then 250~300 bp fragments were selected using AMPure beads
for library construction (Beckman Coulter, Beverly, USA). 3 μl USER
Enzyme (NEB, USA) was added into purified cDNA fragments and incubated
at 37 °C for 15 min followed by 5 min at 95 °C. cDNA fragments were
amplified using polymerase chain reaction (PCR). After purified by
using AMPure beads, the library quality and quantity was measured using
Agilent 2100 Bioanalyzer (Agilent Technologies). Finally, the libraries
were sent to Novogene Co. Ltd. to sequence using Illumina-Hiseq 2000
platform with PE-150 paired-end approach.
RNA-seq data analyses
Raw data were filtered by removing the reads containing the adapters,
poly-N, and low-quality reads, resulting in the generation of clean
reads, which were assembled de novo using the Trinity software version
2.5.1 [[146]57]. The assembled transcripts were identified using Blast+
(version: ncbi-blast-2.2.28+) against the National Center for
Biotechnology Information (NCBI) nonredundant (Nr, e-value <1e-5),
Clusters of Orthologous Groups of proteins (COG, e-value <1e^− 3),
Kyoto Encyclopedia of Genes and Genomes (KEGG, e-value <1e-5), and
Swiss-Prot databases (e-value <1e-5). The gene ontology (GO) annotation
was performed using Blast2GO with an e-value threshold of 1e-6.
The total mapped read counts for each transcript were determined using
the RSEM software v1.2.15 [[147]58]. The differential expression
statistical analyses were performed using the median of ratios from the
R package, DESeq [[148]59]. The adjusted p-value (p-adj) with a cut-off
value of 0.05 and log2 (fold change) with a cut-off absolute value of 1
were used to identify the significant differentially expressed genes
(DEGs). Omicshare online website
([149]http://www.omicshare.com/tools/Home/Soft/pathwaygsea?l=en-us) was
used for Gene Ontology and KEGG pathway enrichment analysis.
Significantly enriched pathways in the given gene set compared to the
genome background are defined by a hypergeometric test. The formula for
calculating the P-value is
[MATH:
P=1−∑i=0m−1<
/mrow>MiN−Mn−iNn :MATH]
In this equation, N is the number of all genes with KEGG pathway
annotation, n is the gene number of given genes set in N, M is the
number of all genes that are annotated to the certain pathway, and m is
the gene number in the given gene set that is annotated to the certain
pathways. The calculated p-value is gone through FDR Correction, taking
FDR ≤ 0.05 as a threshold. GO terms with a q-value lower than 0.05 were
further summarized with REVIGO [[150]60]. The UpSet Chart were made by
an R package UpSetR [[151]61].
Quantitative real-time PCR analysis
Three biological replicates were generated for each RNA sample for
quantitative real-time PCR (qRT-PCR) analysis. The beta-actin gene was
used as an internal control, which did not significantly change
expression in the experiment (Control vs Fasting, p = 0.80; Control vs
Refeeding, p = 0.82; Fasting vs Refeeding, p = 1.0; exactTest, DESeq).
The primers used in the qRT-PCR analysis are shown in Additional file
[152]1: Table S1. The qRT-PCR analysis was performed using the ABI 7000
platform in 20 μL reactions containing the following components: 100 ng
of cDNA, 10 μL Power SYBR Green PCR Master Mix (Vazyme Biotech,
Nanjing, China), 0.3 μL of each primer (10 μM), and 7.4 μL
double-distilled water. The reaction procedure was as mentioned in the
manufacturer’s instructions for the SYBR Green PCR Master Mix. All
samples were analyzed in triplicate, and fold changes were calculated
using the comparative Ct method (also known as the 2^−ΔΔCt method). All
data are provided in terms of the relative mRNA expression as the
mean ± S.E. (n = 3).
Muscle histology
For muscle morphology observation, five fish from each group were
selected. The dorsal muscle tissues obtained in the preceding
experiment were fixed for 24 h in Bouin solution. The tissues were then
dehydrated using an ethyl alcohol series, hyalinized in xylene baths,
and embedded in paraffin. After the paraffin block solidified, thin
sections (6 μm) were cut using a rotary microtome (Cut 4055; Olympus
American, Melville, NY, USA). The sections were flattened, stained with
hematoxylin and eosin, mounted on slides with neutral resin, and
examined using light microscopy. The longest and shortest diameters of
myofibers were measured and recorded for the control and test groups. A
total of ~ 100 cells of each group were randomly selected for
measurement. For each fish, a clear vision was used to measure cell
size, and approximately 20 cells of each vision were randomly measured
and recorded.
Statistical analyses
All data were analyzed using SPSS Statistics software version 20 (IBM,
Chicago, IL, USA) and presented as the means ± SEM. The body weight and
myocyte sizes of fish in the control and test groups were analyzed
using Student’s t-test. P-values < 0.05 were considered to be
statistically significant.
Supplementary information
[153]12864_2019_6345_MOESM1_ESM.docx^ (1.5MB, docx)
Additional file 1: Table S1. Primer pairs used for qRT-PCR. Figure S1.
Daily changes of growth traits. Figure S2. The expression of genes
associated with structure of myofiber.
[154]12864_2019_6345_MOESM2_ESM.xls^ (881.5KB, xls)
Additional file 2: Table S2. Figure S2. The list of all differentially
expressed genes during fasting-refeeding.
Acknowledgments