Plasma proteomics analysis of diabetic patients complicated with pulmonary tuberculosis by iTRAQ technology

doi:10.19982/j.issn.1000-6621.20210659

Abstract

Abstract:

Objective: To analyze the difference in plasma protein mass spectrum between diabetic (DM) patients and diabetic patients complicated with pulmonary tuberculosis (DM-PTB), screen potential protein biomarkers of DM-PTB, and to provide basis for further pathogenesis exploration. Methods: A retrospective study was conducted in 16 DM and 16 DM-PTB patients from Infectious Disease Hospital of Heilongjiang Province between January 1, 2017and January 1, 2018. The plasma protein mass spectra between the two groups were analyzed by isobaric tags for relative and absolute quantitation (iTRAQ) proteomics technology. The differential proteins were screened according to the following criteria: fold of protein expression change in DM-PTB compared to DM>1.2 or <0.83, and P<0.05. The differential proteins were analyzed by bioinformatics, such as Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and so on. Results: A total of 275 differentially expressed proteins were selected out, among which 111 were up-regulated and 164 were down-regulated in DM-PTB. GO analysis showed that the biological process with the largest number of differentially expressed proteins was cellular process (92.00%, 253/275), located in organelle (87.27%, 240/275) and the molecular function was binding (90.55%, 249/275). KEGG pathway analysis showed that the differentially expressed proteins were enriched into 26 pathways (false discovery rate <0.05) and focal adhesion was the pathway with the largest number of enrichment (22 proteins). Moreover, changes were also found in PI3K-Akt signaling pathway, cholesterol metabolism, platelet activation, phagosome, complement and coagulation pathways, et al., which related to glucose and lipid metabolism and immunity. Conclusion: In this study, differentially expressed proteins of DM-PTB patients were screened by iTRAQ quantitative proteomics, and they were involved in signaling pathways related to cellular activity, glucose and lipid metabolism, and immune regulation, suggesting that the changes of pathways mentioned above may be closely related to the pathogenesis of DM-PTB.

Key words: Diabetes mellitus, Tuberculosis,pulmonary, Isotope labeling, Proteomics, Plasma

CLC Number:

WU Ming-qi, YAN Shi-chun, LIU Yu-qin, GUO Xin, WANG Mei-jie, TIAN Jing, HOU Shao-ying. Plasma proteomics analysis of diabetic patients complicated with pulmonary tuberculosis by iTRAQ technology[J]. Chinese Journal of Antituberculosis, 2022, 44(5): 442-449. doi: 10.19982/j.issn.1000-6621.20210659

Figures/Tables 6

特征	DM-PTB组(16例)	DM组(16例)	统计检验值	P值
年龄[岁,M(Q₁,Q₃)]	52.50(43.25,65.50)	56.50(46.00,63.50)	U=142.500	0.584
性别[例(构成比,%)]			-	1.000
男性	9(56.3)	8(50.0)
女性	7(43.7)	8(50.0)
体质量指数	22.36±3.03	27.54±3.78	t=-4.274	<0.001
糖尿病病程(年, $x ¯$ ±s)	5.35±2.94	7.36±3.07	t=-1.888	0.069
空腹血糖[mmol/L,M(Q₁,Q₃)]	7.92(7.12,11.27)	7.24(6.54,10.32)	U=104.000	0.366
使用胰岛素[例(构成比,%)]			-	0.458
是	9(56.3)	12(75.0)
否	7(43.7)	4(25.0)
口服降糖药[例(构成比,%)]			-	0.002
是	1(6.3)	10(62.5)
否	15(93.7)	6(37.5)

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序号	基因	蛋白名称	FC值	P值	表达趋势
P02741	CRP	C反应蛋白	5.22	0.019	↑
P0DJI9	SAA2	血清淀粉样蛋白A2	3.84	0.007	↑
P02763	ORM1	α1酸性糖蛋白1	3.01	0.012	↑
Q96IU4	ABHD14B	α/β水解酶结构域蛋白14B	2.53	<0.001	↑
Q9NP78	ABCB9	ATP结合盒式亚族B成员9	2.51	0.035	↑
Q13126	MTAP	S-甲基化-5'-腺苷磷酸化酶	2.25	0.023	↑
P02679	FGG	纤维蛋白原γ链	2.15	0.029	↑
P11226	MBL2	甘露糖结合凝集素	2.12	0.012	↑
P02675	FGB	纤维蛋白原β链	2.04	0.032	↑
P02750	LRG1	富亮氨酸α-2糖蛋白1	2.00	<0.001	↑
Q9P1F3	ABRACL	Costars家族蛋白ABRACL	0.44	0.021	↓
Q9HBI1	PARVB	β-parvin	0.43	0.004	↓
P12814	ACTN1	α-辅肌动蛋白1	0.42	<0.001	↓
P23284	PPIB	肽基-脯氨酰顺-反异构酶B	0.42	0.010	↓
P09104	ENO2	烯醇化酶γ	0.39	0.003	↓
Q92686	NRGN	神经颗粒素	0.39	0.001	↓
P62158	CALM1	钙调蛋白	0.39	0.002	↓
Q5VZ66	JAKMIP3	Janus激酶与微管相互作用蛋白3	0.39	<0.001	↓
P37802	TAGLN2	转凝蛋白2	0.38	0.002	↓
P62328	TMSB4X	胸腺肽β4	0.37	0.003	↓

序号	功能名称	富集差异蛋白数量
细胞组成
GO:0043226	细胞器	240
GO:0005622	细胞内	229
GO:0043227	膜结合细胞器	229
GO:0044424	细胞内组分	228
GO:0005737	细胞质	224
GO:0005576	细胞外区	218
GO:0044444	细胞质组分	213
GO:0044421	胞外区组分	205
GO:0043229	胞内细胞器	202
GO:0005615	细胞外间隙	198
分子功能
GO:0005488	结合	249
GO:0005515	蛋白结合	225
GO:0043168	负离子结合	68
GO:0044877	蛋白复合体结合	64
GO:0042802	同一蛋白结合	63
GO:0036094	小分子结合	62
GO:0005102	信号受体结合	61
GO:0019899	酶结合	61
GO:0098772	分子功能调节器	59
GO:0097367	碳水化合物衍生物结合	57
生物过程
GO:0009987	细胞过程	253
GO:0065007	生物调节	222
GO:0050789	生物过程调节	216
GO:0050896	刺激反应	212
GO:0050794	细胞过程调节	208
GO:0051179	定位	182
GO:0051716	细胞刺激反应	167
GO:0032501	多细胞生物过程	160
GO:0051234	建立定位	154
GO:0006810	转运	153

序号	通路名称	富集差异蛋白数量
hsa04510	黏着斑通路	22
hsa04151	PI3K-Akt信号通路	17
hsa04810	肌动蛋白细胞骨架调节通路	15
hsa04611	血小板激活通路	14
hsa04015	Rap1信号通路	12
hsa04512	ECM受体交互作用	11
hsa01200	碳代谢通路	11
hsa04514	细胞黏着分子通路	11
hsa04145	吞噬体通路	11
hsa00010	糖酵解/糖异生通路	10
hsa05146	阿米巴通路	10
hsa04530	紧密连接通路	10
hsa04979	胆固醇代谢通路	9
hsa05100	上皮细胞细菌侵入通路	9
hsa05132	沙门菌感染通路	9
hsa04670	白细胞跨内皮迁移通路	9
hsa05130	致病性大肠杆菌感染通路	8
hsa05412	右心室心率失常心肌病通路	8
hsa04610	补体及凝血通路	8
hsa05410	肥厚性心机病通路	8
hsa05414	扩张性心肌病通路	8
hsa05131	志贺菌通路	7
hsa04520	黏着连接通路	7
hsa01230	氨基酸生物合成通路	7
hsa05020	朊病毒通路	6
hsa05144	疟疾通路	6