Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

Rapid Multivariate Analysis Approach to Explore Differential Spatial Protein Profiles in Tissue

Spatially targeted proteomics analyzes the proteome of specific cell types and functional regions within tissue. While spatial context is often essential to understanding biological processes, interpreting sub-region-specific protein profiles can pose a challenge due to the high-dimensional nature of the data. Here, we develop a multivariate approach for rapid exploration of differential protein profiles acquired from distinct tissue regions and apply it to analyze a published spatially targeted proteomics data set collected from Staphylococcus aureus-infected murine kidney, 4 and 10 days postinfection. The data analysis process rapidly filters high-dimensional proteomic data to reveal relevant differentiating species among hundreds to thousands of measured molecules. We employ principal component analysis (PCA) for dimensionality reduction of protein profiles measured by microliquid extraction surface analysis mass spectrometry. Subsequently, k-means clustering of the PCA-processed data groups samples by chemical similarity. Cluster center interpretation revealed a subset of proteins that differentiate between spatial regions of infection over two time points. These proteins appear involved in tricarboxylic acid metabolomic pathways, calcium-dependent processes, and cytoskeletal organization. Gene ontology analysis further uncovered relationships to tissue damage/repair and calcium-related defense mechanisms. Applying our analysis in infectious disease highlighted differential proteomic changes across abscess regions over time, reflecting the dynamic nature of host-pathogen interactions.

UPLC-HDMSE to discover serum biomarkers in adults with type 1 diabetes

Type 1 diabetes (T1D) is a complex disease with metabolic and functional changes that can alter an individual's proteome. An LC-MS/MS analytical method, in an HDMS^E system, was used to identify differentially expressed proteins in the high abundance protein-depleted serum of T1D patients and healthy controls. Samples were processed in Progenesis QI for Proteomics software. A functional enrichment of the proteins was performed with Gene Ontology and ToppGene, and the interactions were visualized by STRING 11.5. As a result, 139 proteins were identified, 14 of which were downregulated in the serum of patients with T1D compared to controls. Most of the differentially expressed proteins were shown to be involved with the immune system, inflammation, and growth hormone stimulus response, and were associated with the progression of T1D. Differential protein expression data showed for the first-time changes in CPN2 expression levels in the serum of patients with T1D. Our findings indicate that these proteins are targets of interest for future investigations and for validation of protein biomarkers in T1D.

Proteomic analysis of vitreous humour of eyes with diabetic macular oedema: a systematic review

The pathophysiology of diabetic macular oedema (DME) remains poorly understood. Proteomic analysis of the vitreous using mass spectrometry (MS) can potentially identify proteins of pathophysiological importance. In this systematic review, we summarize the available evidence on protein changes in DME detected by MS. We systematically searched 13 literature databases on 19 September 2021. Eligible studies were defined as those using samples from human eyes with DME analysed with MS. Two authors assessed the studies for eligibility, extracted data and evaluated risk of bias independently. Six eligible studies were identified. All were designed in a cross-sectional fashion comparing results to either a non-diabetic control group or a control group without DME. A total of 62 eyes from 60 patients contributed as study group and 48 eyes from 48 patients served as control group. Proteomic analyses revealed significant differences in the vitreous protein levels in patients with DME when compared with controls. Three studies or more identified increased contents of apolipoprotein A-I, apolipoprotein A-II, apolipoprotein A-IV, apolipoprotein C-III, gelsolin, pigment epithelium-derived factor, serum albumin, transthyretin, vitamin D-binding protein in DME. Two studies found increased levels of complement factors B and C3. Protein changes reproduced across the studies suggested that DME was associated with retinal lipid accumulation, angiogenesis, retinal protective mechanisms, inflammation and complement activation. Proteome studies support the multifactorial pathogenesis of DME as proteins with highly different biological functions are regulated in DME. An important number of proteins differ, provide pathophysiological insight and suggest the direction for future research.

Oxidative Stress in Type 2 Diabetes: The Case for Future Pediatric Redoxomics Studies

Considerable evidence supports the role of oxidative stress in adult type 2 diabetes (T2D). Due to increasing rates of pediatric obesity, lack of physical activity, and consumption of excess food calories, it is projected that the number of children living with insulin resistance, prediabetes, and T2D will markedly increase with enormous worldwide economic costs. Understanding the factors contributing to oxidative stress and T2D risk may help develop optimal early intervention strategies. Evidence suggests that oxidative stress, triggered by excess dietary fat consumption, causes excess mitochondrial hydrogen peroxide emission in skeletal muscle, alters redox status, and promotes insulin resistance leading to T2D. The pathophysiological events arising from excess calorie-induced mitochondrial reactive oxygen species production are complex and not yet investigated in children. Systems medicine is an integrative approach leveraging conventional medical information and environmental factors with data obtained from “omics” technologies such as genomics, proteomics, and metabolomics. In adults with T2D, systems medicine shows promise in risk assessment and predicting drug response. Redoxomics is a branch of systems medicine focusing on “omics” data related to redox status. Systems medicine with a complementary emphasis on redoxomics can potentially optimize future healthcare strategies for adults and children with T2D.

ConSIG: consistent discovery of molecular signature from OMIC data

The discovery of proper molecular signature from OMIC data is indispensable for determining biological state, physiological condition, disease etiology, and therapeutic response. However, the identified signature is reported to be highly inconsistent, and there is little overlap among the signatures identified from different biological datasets. Such inconsistency raises doubts about the reliability of reported signatures and significantly hampers its biological and clinical applications. Herein, an online tool, ConSIG, was constructed to realize consistent discovery of gene/protein signature from any uploaded transcriptomic/proteomic data. This tool is unique in a) integrating a novel strategy capable of significantly enhancing the consistency of signature discovery, b) determining the optimal signature by collective assessment, and c) confirming the biological relevance by enriching the disease/gene ontology. With the increasingly accumulated concerns about signature consistency and biological relevance, this online tool is expected to be used as an essential complement to other existing tools for OMIC-based signature discovery. ConSIG is freely accessible to all users without login requirement at https://idrblab.org/consig/.

Functional annotation and enrichment analysis of differentially expressed serum proteins in patients with type 2 diabetes after dapagliflozin

BACKGROUND

Only 50% of patients with type 2 diabetes mellitus (T2DM) can control their blood glucose levels. Dapagliflozin is a selective inhibitor of sodium-glucose co-transporter 2 (SGLT-2) that improves the insulin sensitivity of the liver and peripheral tissues. Many studies confirmed that SGLT2 inhibitors reduce blood glucose and have multiple beneficial effects such as weight loss, lipid regulation, and kidney protection. Nevertheless, the mechanisms of the renal and cardiovascular protective effects of dapagliflozin from the perspective of differentially expressed proteins in the serum of T2DM patients have not been intensively explored so far.

AIM

To identify differentially expressed proteins associated with dapagliflozin treatment in patients with T2DM.

METHODS

Twenty T2DM patients [hemoglobin A1c (HbA1c) 7.0%-10.0%] were enrolled at The Affiliated Hospital of Inner Mongolia Medical University between January 1, 2017 and December 1, 2018. They received dapagliflozin (10 mg/d) for 3 mo, and the HbA1c < 7.0% target was achieved. The changes in clinical indexes were compared before and after treatments. Label-free quantitative proteomics was used to identify differentially expressed proteins using the serum samples of five patients. The identified differentially expressed proteins were analyzed using various bioinformatics tools.

RESULTS

Dapagliflozin significantly improved the clinical manifestation of the patients. There were 18 downregulated proteins and one upregulated protein in the serum samples of patients after dapagliflozin administration. Bioinformatics analyses, including subcellular localization, EuKaryotic Orthologous Groups, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes annotations, were used to profile the biological characteristics of the 19 differentially expressed proteins. Based on the literature and function enrichment analysis, two downregulated proteins, myeloperoxidase (MPO) and alpha II B integrin (ITGA2B), and one upregulated protein, podocalyxin (PCX), were selected for enzyme linked immunosorbent assay validation. These validated differentially expressed proteins had multiple correlations with clinical indexes, including HbAc1 and fasting C-peptide.

CONCLUSION

Dapagliflozin has hypoglycemic effects and regulates the serum expressions of MPO, ITGA2B, and PCX, possibly contributing to the effects of dapagliflozin on oxidative stress, insulin resistance, and lipid metabolism.

Identifying Potential Mitochondrial Proteome Signatures Associated with the Pathogenesis of Pulmonary Arterial Hypertension in the Rat Model

Pulmonary arterial hypertension (PAH) is a severe and progressive disease that affects the heart and lungs and a global health concern that impacts individuals and society. Studies have reported that some proteins related to mitochondrial metabolic functions could play an essential role in the pathogenesis of PAH, and their specific expression and biological function are still unclear. We successfully constructed a monocrotaline- (MCT-) induced PAH rat model in the present research. Then, the label-free quantification proteomic technique was used to determine mitochondrial proteins between the PAH group (n = 6) and the normal group (n = 6). Besides, we identified 1346 mitochondrial differentially expressed proteins (DEPs) between these two groups. Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the mainly mitochondrial DEPs' biological functions and the signal pathways. Based on the protein-protein interaction (PPI) network construction and functional enrichment, we screened 19 upregulated mitochondrial genes (Psmd1, Psmc4, Psmd13, Psmc2, etc.) and 123 downregulated mitochondrial genes (Uqcrfs1, Uqcrc1, Atp5c1, Atp5a1, Uqcrc2, etc.) in rats with PAH. Furthermore, in an independent cohort dataset and experiments with rat lung tissue using qPCR, validation results consistently showed that 6 upregulated mitochondrial genes (Psmd2, Psmc4, Psmc3, Psmc5, Psmd13, and Psmc2) and 3 downregulated mitochondrial genes (Lipe, Cat, and Prkce) were significantly differentially expressed in the lung tissue of PAH rats. Using the RNAInter database, we predict potential miRNA target hub mitochondrial genes at the transcriptome level. We also identified bortezomib and carfilzomib as the potential drugs for treatment in PAH. Finally, this study provides us with a new perspective on critical biomarkers and treatment strategies in PAH.

Clinical identification of expressed proteins in adrenal medullary hyperplasia detected with hypertension

BACKGROUND

Hypertension remains a challenging public health problem worldwide, and adrenal gland-related diseases are one class of the major causes for secondary hypertension. Among them, one relatively rare pattern is adrenal hyperplastic hypertension caused by adrenal medullary hyperplasia (AMH), leading to excessive secretion of autonomic catecholamine. Given that the pathological changes of adrenal medulla are not well correlated to the onset and even severity of secondary hypertension, the molecular basis why some AMH patients are accompanied with hypertension remains unclear and is worth exploring.

AIMS

For this reason, this study aims at investigating differentially expressed proteins in clinical AMH tissue, with special focus on the potential contribution of these differentially expressed proteins to AMH development, in order to have a better understanding of mechanisms how AMH leads to secondary hypertension to some extent.

METHODS AND RESULTS

To this end, AMH specimens were successfully obtained and verified through computed tomography (CT) and haematoxylin-eosin (HE) staining. Proteomic analyses of AMH and control tissues revealed 782 kinds of differentially expressed proteins. Compared with the control tissue, there were 357 types of upregulated proteins and 425 types of downregulated proteins detected in AMH tissue. Of interest, these differentially expressed proteins were significantly enriched in 60 gene ontology terms (P < 0.05), including 28 biological process terms, 14 molecular function terms, and 18 cellular component terms. Pathway analysis further indicated that 306 proteins exert their functions in at least one Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Western blotting showed enhanced expression of phenylethanolamine N- methyltransferase (PNMT), myelin protein zero (MPZ), and Ras-related protein Rab-3C (RAB3C), and reduced expression of cluster of differentiation 36 (CD36) observed in AMH tissue in comparison with controls.

CONCLUSIONS

Clinical AMH specimens display a different proteomic profile compared to control tissue. Of note, PNMT, MPZ, RAB3C, and CD36 are found to differentially expressed and can be potential targets for AMH, providing a theoretical basis for mechanistic exploration of AMH along with hypertension.

Multiple Imputation Approaches Applied to the Missing Value Problem in Bottom-Up Proteomics

Analysis of differential abundance in proteomics data sets requires careful application of missing value imputation. Missing abundance values widely vary when performing comparisons across different sample treatments. For example, one would expect a consistent rate of “missing at random” (MAR) across batches of samples and varying rates of “missing not at random” (MNAR) depending on the inherent difference in sample treatments within the study. The missing value imputation strategy must thus be selected that best accounts for both MAR and MNAR simultaneously. Several important issues must be considered when deciding the appropriate missing value imputation strategy: (1) when it is appropriate to impute data; (2) how to choose a method that reflects the combinatorial manner of MAR and MNAR that occurs in an experiment. This paper provides an evaluation of missing value imputation strategies used in proteomics and presents a case for the use of hybrid left-censored missing value imputation approaches that can handle the MNAR problem common to proteomics data.

Longitudinal proteomics analysis in the immediate microenvironment of islet allografts during progression of rejection

The applicability and benefits of pancreatic islet transplantation are limited due to various issues including the need to avoid immune-mediated rejection. Here, we used our experimental platform of allogeneic islet transplant in the anterior chamber of the eye (ACE-platform) to longitudinally monitor the progress of rejection in mice and obtain aqueous humor samples representative of the microenvironment of the graft for accurately-timed proteomic analyses. LC-MS/MS-based proteomics performed on such mass-limited samples (~5 μL) identified a total of 1296 proteins. Various analyses revealed distinct protein patterns associated with the mounting of the inflammatory and immune responses and their evolution with the progression of the rejection. Pathway analyses indicated predominant changes in cytotoxic functions, cell movement, and innate and adaptive immune responses. Network prediction analyses revealed transition from humoral to cellular immune response and exacerbation of pro-inflammatory signaling. One of the proteins identified by this localized proteomics as a candidate biomarker of islet rejection, Cystatin 3, was further validated by ELISA in the aqueous humor. This study provides (1) experimental evidence demonstrating the feasibility of longitudinal localized proteomics using small aqueous humor samples and (2) proof-of-concept for the discovery of biomarkers of impending immune attack from the immediate local microenvironment of ACE-transplanted islets. SIGNIFICANCE: The combination of the ACE-platform and longitudinal localized proteomics offers a powerful approach to biomarker discovery during the various stages of immune reactions mounted against transplanted tissues including pancreatic islets. It also supports proteomics-assisted drug discovery and development efforts aimed at preventing rejection through efficacy assessment of new agents by noninvasive and longitudinal graft monitoring.