scholarly journals A validated analysis pipeline for mass spectrometry-based vitreous proteomics: new insights into proliferative diabetic retinopathy

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Sarah R. Weber ◽  
Yuanjun Zhao ◽  
Jingqun Ma ◽  
Christopher Gates ◽  
Felipe da Veiga Leprevost ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Diabetic Retinopathy ◽  
Proliferative Diabetic Retinopathy ◽  
Metabolic Pathways ◽  
Power Analysis ◽  
Principal Component ◽  
Retinal Disease ◽  
Data Matrix ◽  
Accessible Information ◽  
Pooled Samples

Abstract Background Vitreous is an accessible, information-rich biofluid that has recently been studied as a source of retinal disease-related proteins and pathways. However, the number of samples required to confidently identify perturbed pathways remains unknown. In order to confidently identify these pathways, power analysis must be performed to determine the number of samples required, and sample preparation and analysis must be rigorously defined. Methods Control (n = 27) and proliferative diabetic retinopathy (n = 23) vitreous samples were treated as biologically distinct individuals or pooled together and aliquoted into technical replicates. Quantitative mass spectrometry with tandem mass tag labeling was used to identify proteins in individual or pooled control samples to determine technical and biological variability. To determine effect size and perform power analysis, control and proliferative diabetic retinopathy samples were analyzed across four 10-plexes. Pooled samples were used to normalize the data across plexes and generate a single data matrix for downstream analysis. Results The total number of unique proteins identified was 1152 in experiment 1, 989 of which were measured in all samples. In experiment 2, 1191 proteins were identified, 727 of which were measured across all samples in all plexes. Data are available via ProteomeXchange with identifier PXD025986. Spearman correlations of protein abundance estimations revealed minimal technical (0.99–1.00) and biological (0.94–0.98) variability. Each plex contained two unique pooled samples: one for normalizing across each 10-plex, and one to internally validate the normalization algorithm. Spearman correlation of the validation pool following normalization was 0.86–0.90. Principal component analysis revealed stratification of samples by disease and not by plex. Subsequent differential expression and pathway analyses demonstrated significant activation of metabolic pathways and inhibition of neuroprotective pathways in proliferative diabetic retinopathy samples relative to controls. Conclusions This study demonstrates a feasible, rigorous, and scalable method that can be applied to future proteomic studies of vitreous and identifies previously unrecognized metabolic pathways that advance understanding of diabetic retinopathy.

A Validated Analysis Pipeline for Mass Spectrometry-Based Vitreous Proteomics: Insights Into Proliferative Diabetic Retinopathy

2021 ◽  
Author(s):  
Sarah R Weber ◽  
Yuanjun Zhao ◽  
Jingqun Ma ◽  
Christopher Gates ◽  
Felipe da Veiga Leprevost ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Diabetic Retinopathy ◽  
Proliferative Diabetic Retinopathy ◽  
Power Analysis ◽  
Principal Component ◽  
Retinal Disease ◽  
Data Matrix ◽  
Accessible Information ◽  
Downstream Analysis ◽  
Pooled Samples

Abstract Background: Vitreous is an accessible, information-rich biofluid that has recently been studied as a source of retinal disease-related proteins and pathways. However, the number of samples required to confidently identify perturbed pathways remains unknown. In order to confidently identify these pathways, power analysis must be performed to determine the number of samples required.Methods: Control (n=27) and proliferative diabetic retinopathy (n=23) vitreous samples were treated as biologically distinct individuals or pooled together and aliquoted into technical replicates. Quantitative mass spectrometry with tandem mass tag labeling was used to identify proteins in individual or pooled control samples to determine technical and biological variability. To determine effect size and perform power analysis, control and proliferative diabetic retinopathy samples were analyzed across four 10plexes. Pooled samples were used to normalize the data across plexes and generate a single data matrix for downstream analysis. Results: The total number of unique proteins identified was 1,152 in experiment 1, 989 of which were measured in all samples. In experiment 2, 1,191 proteins were identified, 727 of which were measured across all samples in all plexes. Data are available via ProteomeXchange with identifier PXD025986. Spearman correlations of protein abundance estimations revealed minimal technical (0.99-1.00) and biological (0.94-0.98) variability. Each plex contained two unique pooled samples: one for normalizing across each 10plex, and one to internally validate the normalization algorithm. Spearman correlation of the validation pool following normalization was 0.86-0.90. Principal component analysis revealed stratification of samples by disease and not by plex. Subsequent differential expression and pathway analyses demonstrated significant activation of metabolic pathways and inhibition of neuroprotective pathways in proliferative diabetic retinopathy samples relative to controls.Conclusions: This study demonstrates a feasible, rigorous, and scalable method that can be applied to future proteomic studies of vitreous sampled directly from patients in order to advance understanding of pathways altered in retinal disease.

scholarly journals Proteomic Analyses of Vitreous in Proliferative Diabetic Retinopathy: Prior Studies and Future Outlook

2021 ◽  
Vol 10 (11) ◽  
pp. 2309
Author(s):  
Sarah R. Weber ◽  
Yuanjun Zhao ◽  
Christopher Gates ◽  
Jingqun Ma ◽  
Felipe da Veiga Leprevost ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Diabetic Retinopathy ◽  
Proliferative Diabetic Retinopathy ◽  
Proteomic Analysis ◽  
Retinal Disease ◽  
Vitreous Fluid ◽  
Future Outlook ◽  
Novel Proteins ◽  
Popular Medium ◽  
Molecular Information

Vitreous fluid is becoming an increasingly popular medium for the study of retinal disease. Numerous studies have demonstrated that proteomic analysis of the vitreous from patients with proliferative diabetic retinopathy yields valuable molecular information regarding known and novel proteins and pathways involved in this disease. However, there is no standardized methodology for vitreous proteomic studies. Here, we share a suggested protocol for such studies and outline the various experimental and analytic methods that are currently available. We also review prior mass spectrometry-based proteomic studies of the vitreous from patients with proliferative diabetic retinopathy, discuss common pitfalls of these studies, and propose next steps for moving the field forward.

scholarly journals Analysis of Serum Metabolomics in Rats with Osteoarthritis by Mass Spectrometry

Molecules ◽  
2021 ◽  
Vol 26 (23) ◽  
pp. 7181
Author(s):  
Jingtong Zhao ◽  
Meng Liu ◽  
Tongfei Shi ◽  
Mohan Gao ◽  
Yuqian Lv ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Metabolic Pathways ◽  
Acid Metabolism ◽  
Principal Component ◽  
Male Rats ◽  
Control Group ◽  
Liquid Chromatography Mass Spectrometry ◽  
Disease Mechanisms ◽  
Periarticular Tissue ◽  
Serum Metabolomics

Osteoarthritis is a common multifactorial chronic disease that occurs in articular cartilage, subchondral bone, and periarticular tissue. The pathogenesis of OA is still unclear. To investigate the differences in serum metabolites between OA and the control group, liquid chromatography/mass spectrometry (LC/MS)-based metabolomics was used. To reveal the pathogenesis of OA, 12 SD male rats were randomly divided into control and OA groups using collagenase to induce OA for modeling, and serum was collected 7 days after modeling for testing. The OA group was distinguished from the control group by principal component analysis and orthogonal partial least squares-discriminant analysis, and six biomarkers were finally identified. These biomarkers were metabolized through tryptophan metabolism, glutamate metabolism, nitrogen metabolism, spermidine metabolism, and fatty acid metabolism pathways. The study identified metabolites that may be altered in OA, suggesting a role in OA through relevant metabolic pathways. Metabolomics, as an important tool for studying disease mechanisms, provides useful information for studying the metabolic mechanisms of OA.

scholarly journals Characterization of Vitreous and Aqueous Proteome in Humans With Proliferative Diabetic Retinopathy and Its Clinical Correlation

2017 ◽  
Vol 8 ◽  
pp. 117864181668607 ◽  
Author(s):  
Sankarathi Balaiya ◽  
Zimei Zhou ◽  
Kakarla V Chalam
Keyword(s):  
Mass Spectrometry ◽  
Diabetic Retinopathy ◽  
Proliferative Diabetic Retinopathy ◽  
Inflammatory Responses ◽  
Microvascular Complications ◽  
Vitreous Humor ◽  
Human Retina ◽  
Liquid Chromatography Mass Spectrometry ◽  
Mass Spectrometry Mass Spectrometry

Aims: Proliferative diabetic retinopathy (PDR) is associated with microvascular complications that cause biochemical changes in the human retina and alter the proteome of vitreous humor and aqueous humor (AH). Methods: Human vitreous humor and AH of PDR subjects were collected. Subjects who had surgery for epiretinal membrane or macular hole served as controls. Protein profiles were obtained and analyzed after running the samples on a liquid chromatography-mass spectrometry/mass spectrometry. Results: In vitreous humor, 16 unique proteins were noted in PDR patients, but not in controls. Those were associated mainly with coagulation, complement, and kallikrein-kinin systems. Under coagulation, fibrinogen and prothrombin proteins were more evident and may emphasize the importance of angiogenesis in the development of PDR. Vitreous proteins showed replicative presence in AH too. As for AH samples, we detected 10 proteins found in PDR patients, which were related to transport, coagulation, and inflammatory responses. Conclusions: We found 57 proteins in human vitreous and 39 proteins in AH. Identification of these proteins that are involved in various pathways will be helpful to understand diabetic retinopathy pathogenesis and to develop proteome as a biomarker for PDR.

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