urine proteome
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2022 ◽  
pp. 104477
Author(s):  
Jing Wei ◽  
Yuhang Huan ◽  
Ziqi Heng ◽  
Chenyang Zhao ◽  
Lulu Jia ◽  
...  

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261488
Author(s):  
Wenshu Meng ◽  
Chenyang Zhao ◽  
Youhe Gao

Purpose To explore and compare urine proteome changes among rat models by intraperitoneal injection with single bacteria and co-injection with two bacteria. Method Escherichia coli and Staphylococcus aureus are two common human pathogens. Three rat models were established: (i) the intraperitoneal co-injection of E. coli and S. aureus model (ES model), (ii) intraperitoneal injection of E. coli model (E model), and (iii) intraperitoneal injection of S. aureus model (S model). Urinary proteomes on days 0, 1 and 2 of the three models were analyzed by liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Results A total of 111, 34 and 94 differential proteins were identified in the ES model, E model and S model, respectively. Among them, some differential proteins were reported to be associated with bacterial infection. Approximately 47% differential proteins in the E model overlapped with ES model, and 37% differential proteins in the S model overlapped with ES model. Compared with the E model and S model, a total of 71 unique differential proteins were identified in the ES model. Conclusion Our results indicated that (1) the urine proteome could distinguish different bacterial intraperitoneal injections models and (2) the effects of co-injection with two bacteria on the urine proteome were not simple superposition of single injection.


2021 ◽  
Author(s):  
Jing Wei ◽  
Yuhang Huan ◽  
Ziqi Heng ◽  
Chenyang Zhao ◽  
Youhe Gao

Background: Statin-associated muscle symptoms (SAMS) are the main side effects of statins. Currently, there are no effective biomarkers for accurate clinical diagnosis. Urine is not subject to homeostatic control and therefore accumulates early changes, making it an ideal biomarker source. We therefore examined urine proteome changes associated with SAMS in an animal model. Methods: Here, we established a SAMS rat model by intragastric intubation with simvastatin (80 mg/kg). Biochemical analyses and hematoxylin and eosin (H&E) staining were used to evaluate the degree of muscle injury. The urine proteome on days 3, 6, 9 and 14 was profiled using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) with the data-independent acquisition (DIA) method. Results: Differential proteins on day 14 of SAMS were mainly associated with glycolysis/gluconeogenesis, pyruvate metabolism, metabolism of reactive oxygen species and apoptosis, all of which were reported to be associated with the pathological mechanism of SAMS. Among the 14 differentially expressed proteins on day 3, FIBG, OSTP and CRP were associated with muscle damage, while EHD1, CUBN and FINC were associated with the pathogenic mechanisms of SAMS. MYG and PRVA increased dramatically compared with CK elevation in serum on day 14 of SAMS. Conclusions: Our preliminary results indicated that the urine proteome can reflect early changes in the SAMS rat model, providing the potential for monitoring drug side effects in future clinical research. Keywords: Urine proteome, statin-associated muscle symptoms, animal model, biomarkers


2021 ◽  
Vol 8 ◽  
Author(s):  
Adam C. Swensen ◽  
Jingtang He ◽  
Alexander C. Fang ◽  
Yinyin Ye ◽  
Carrie D. Nicora ◽  
...  

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.


URINE ◽  
2021 ◽  
Author(s):  
Yanchang Li ◽  
Yihao Wang ◽  
Huiying Liu ◽  
Wei Sun ◽  
Baoqing Ding ◽  
...  
Keyword(s):  

2021 ◽  
Author(s):  
Adam C. Swensen ◽  
Jingtang He ◽  
Alexander C. Fang ◽  
Yinyin Ye ◽  
Carrie D. Nicora ◽  
...  

AbstractUrine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers. Surprisingly, 43% (167) of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as myoglobin, serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.


2021 ◽  
Vol 2021 ◽  
pp. 1-20
Author(s):  
Yameng Zhang ◽  
Yufei Gao ◽  
Jing Wei ◽  
Youhe Gao

Urine can accumulate systemic changes with no mechanism to be stable, which may reflect early changes associated with physiological or pathophysiological processes. To explore the potential value of the urine proteome, two rat models were established by intrahepatic injection of two different hepatoma cell lines, CBRH-7919 and RH-35. Urine samples were collected and analyzed. Compared with controls, the two models exhibited different numbers and types of differentially expressed urinary proteins despite having similar histological results. The results were compared with the urine proteome of a Walker 256 (W-256) liver tumor model. The differentially expressed urinary protein patterns in the three models were different. These findings demonstrate that changes in the urine proteomes of the two models can be detected at early stages and that the patterns of differentially expressed urinary proteins can differ even when the histological results are similar. Urinary proteins have potential utility for distinguishing among different tumor cells grown in the same organ.


2021 ◽  
Author(s):  
Chang-Hai Liu ◽  
Shanshan Zheng ◽  
ShiSheng Wang ◽  
DongBo Wu ◽  
Wei Jiang ◽  
...  

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