iTRAQ-based quantitative proteomic analysis on differentially expressed proteins of rat mandibular condylar cartilage induced by reducing dietary loading

doi:10.1007/s11684-016-0496-1

Frontiers of Medicine

2017, Vol. 11

Issue (1): 97-109 https://doi.org/10.1007/s11684-016-0496-1

本期目录

iTRAQ-based quantitative proteomic analysis on differentially expressed proteins of rat mandibular condylar cartilage induced by reducing dietary loading

Liting Jiang^1,²,Yinyin Xie³,Li Wei⁴,Qi Zhou⁴,Ning Li¹,Xinquan Jiang²(

),Yiming Gao¹(

)

¹. Department of Stomatology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
². Department of Prosthodontics, Ninth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Stomatology, Shanghai 200011, China
³. State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
⁴. Shanghai Institute of Traumatology and Orthopedics, Shanghai 200025, China

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Abstract：

As muscle activity during growth is considerably important for mandible quality and morphology, reducing dietary loading directly influences the development and metabolic activity of mandibular condylar cartilage (MCC). However, an overall investigation of changes in the protein composition of MCC has not been fully described in literature. To study the protein expression and putative signaling in vivo, we evaluated the structural changes of MCC and differentially expressed proteins induced by reducing functional loading in rat MCC at developmental stages. Isobaric tag for relative and absolute quantitation-based 2D nano-high performance liquid chromatography (HPLC) and matrix-assisted laser desorption/ionization time-of-flight/ time-of-flight (MALDI-TOF/TOF) technologies were used. Global protein profiling, KEGG and PANTHER pathways, and functional categories were analyzed. Consequently, histological and tartrate-resistant acid phosphatase staining indicated the altered histological structure of condylar cartilage and increased bone remodeling activity in hard-diet group. A total of 805 differentially expressed proteins were then identified. GO analysis revealed a significant number of proteins involved in the metabolic process, cellular process, biological regulation, localization, developmental process, and response to stimulus. KEGG pathway analysis also suggested that these proteins participated in various signaling pathways, including calcium signaling pathway, gap junction, ErbB signaling pathway, and mitogen-activated protein kinase signaling pathway. Collagen types I and II were further validated by immunohistochemical staining and Western blot analysis. Taken together, the present study provides an insight into the molecular mechanism of regulating condylar growth and remodeling induced by reducing dietary loading at the protein level.

Key words： condylar cartilage mechanical loading proteomic analysis iTRAQ bioinformatics analysis

收稿日期: 2016-04-27 出版日期: 2017-03-20

Corresponding Author(s): Xinquan Jiang,Yiming Gao

引用本文:

. [J]. Frontiers of Medicine, 2017, 11(1): 97-109.
Liting Jiang,Yinyin Xie,Li Wei,Qi Zhou,Ning Li,Xinquan Jiang,Yiming Gao. iTRAQ-based quantitative proteomic analysis on differentially expressed proteins of rat mandibular condylar cartilage induced by reducing dietary loading. Front. Med., 2017, 11(1): 97-109.

链接本文:

https://academic.hep.com.cn/fmd/CN/10.1007/s11684-016-0496-1
https://academic.hep.com.cn/fmd/CN/Y2017/V11/I1/97

Fig.1

Fig.2

Fig.3

Fig.4

Gene symbol	Protein name	116.1/114.1	117.1/114.1
Calcium binding protein (PC00060)
CAB45	5 kDa calcium binding protein precursor	0.53	0.61
PLCE1	Phospholipase C-epsilon-1	0.59	0.53
KPCZ	Protein kinase C ζ type	0.57	0.77
CABP1	Ras GTPase-activating protein 1	0.91	1.02
KPCT	Protein kinase C ι type	0.61	0.64
PLCG2	Phospholipase C-γ-2	0.70	0.74
CAN9	Calpain-9	0.69	0.73
PLCG1	Phospholipase C-γ-1	0.87	1.01
M2OM	Mitochondrial 2-oxoglutarate/malate carrier protein	1.07	1.19
PLCB2	Phospholipase C-β-2	0.76	0.75
PLCB1	Phospholipase C-β-1	0.39	0.51
NUCB1	Nucleobindin-1 precursor	0.48	0.68
PKN2	Protein-kinase C-related kinase 2	2.39	2.96
EFCB3	EF-hand calcium binding domain-containing protein 3	0.69	0.81
CAN10	Calpain-10	1.44	1.22
KPCB	Protein kinase C β type	0.60	0.51
KPCG	Protein kinase C γ type	1.55	1.61
MAST1	Microtubule-associated serine/threonine-protein kinase 1	0.74	0.75
PKN1	Serine/threonine-protein kinase N1	0.29	0.53
FA10	Coagulation factor X precursor	0.47	0.50
Cytoskeletal protein (PC00085)
ACTN1	α-actinin-1	1.12	1.20
MYH10	Myosin-10	0.60	0.79
FBP1L	Formin-binding protein 1-like	0.48	0.53
DREB	Drebrin	0.34	0.34
CLIC6	Chloride intracellular channel 6	0.96	1.02
PDLI3	Actinin-associated LIM protein	0.83	0.95
ADDA	α-adducin	1.11	0.93
DYN1	Dynamin-1	0.81	0.85
TBA3	Tubulin α-3 chain	0.76	0.81
LMNB1	Lamin-B1	0.64	0.66
K1C14	Keratin, type I cytoskeletal 14	0.53	0.57
SYN3	Synapsin-3	0.58	0.67
DYN2	Dynamin-2	0.29	0.53
NUDC	Nuclear migration protein nudC	0.73	0.54
KIF2C	Kinesin-like protein KIF2C	0.97	1.08
LHX1	LIM/homeobox protein Lhx1	1.08	1.29
MAP1B	Microtubule-associated protein 1B	0.96	0.97
TBB2B	Tubulin β-2B chain	1.06	1.06
K2C1B	Keratin, type II cytoskeletal 1b	0.45	0.56
CNN1	Calponin-1	0.11	0.21
Extracellular matrix protein (PC00102)
MEGF8	Multiple epidermal growth factor-like domains 8	0.71	0.61
CO5A1	Collagen α-1(V) chain precursor	0.37	0.51
ITB4	Integrin β-4 precursor	1.34	1.40
MEGF6	Multiple epidermal growth factor-like domains 6 precursor	0.66	0.72
R4RL2	Reticulon-4 receptor-like 2 precursor	0.69	0.72
CSPG2	Versican core protein precursor	1.24	1.44
FETUA	α-2-HS-glycoprotein precursor	2.39	2.96
CO1A1	Collagen α-1(I) chain precursor	0.61	0.76
CHRD	Chordin (Fragment)	0.51	0.65
CO1A2	Collagen α-2(I) chain precursor	0.39	0.44
GAS6	Growth-arrest-specific protein 6 precursor	1.41	1.22
CO2A1	Collagen α-1(II) chain precursor	0.68	0.91
LAMB2	Laminin subunit β-2 precursor	0.59	0.77
AP3M1	AP-3 complex subunitμ-1	1.15	1.50
DSPP	Dentin sialophosphoprotein precursor	0.40	0.60
Signaling molecule (PC00207)
CD151	CD151 antigen	1.36	1.41
PLCE1	Phospholipase C-epsilon-1	0.59	0.53
CD53	Cell surface glycoprotein CD53	0.37	0.34
GDF6	Growth/differentiation factor 6 precursor	1.05	1.15
FZD5	Frizzled-5 precursor	0.40	0.60
R4RL2	Reticulon-4 receptor-like 2 precursor	0.69	0.72
PLCG2	Phospholipase C-γ-2	0.70	0.74
CLIC6	Chloride intracellular channel 6	1.03	1.04
PLCG1	Phospholipase C-γ-1	0.87	1.01
SFRP4	Secreted frizzled-related protein 4 precursor	1.39	1.36
A1M	α-1-macroglobulin precursor	0.47	0.63
WISP2	WNT1-inducible-signaling pathway protein 2 precursor	1.42	1.69
PLCB1	Phospholipase C-β-1	0.39	0.51
DSPP	Dentin sialophosphoprotein precursor	0.40	0.60
RASA1	Ras GTPase-activating protein 1	0.91	1.02
BMP3	Bone morphogenetic protein 3 precursor	1.10	1.03
SYGP1	Ras GTPase-activating protein SynGAP	0.60	0.60
PDGFD	Platelet-derived growth factor D precursor	0.94	0.99
VEGFD	Vascular endothelial growth factor D precursor	0.44	0.54
FGF5	Fibroblast growth factor 5 precursor	0.49	0.47
CD40L	CD40 ligand	0.70	0.64
FA10	Coagulation factor X precursor	0.47	0.50
DAB2P	DAB2-interacting protein	0.86	0.98
UBF1	Nucleolar transcription factor 1	0.32	0.33
TNFL4	Tumor necrosis factor ligand superfamily member 4	1.37	1.44
RASA3	Ras GTPase-activating protein 3	1.37	1.43
Transcription factor (PC00218)
MAF	Transcription factor Maf	0.63	0.67
ISL2	Insulin gene enhancer protein ISL-2	0.57	0.68
JUN	Transcription factor AP-1	1.24	1.15
FOSL1	Fos-related antigen 1	0.92	0.96
1433B	14-3-3 protein β/α	0.44	0.38

Tab.1

Tab.2

Tab.3

Fig.5

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