A Proteomics-Based Approach Reveals Differential Regulation of Urine Proteins between Metabolically Healthy and Unhealthy Obese Patients. Int J Mol Sci. 2019;20. [PMID: 31623319 PMCID: PMC6801506 DOI: 10.3390/ijms20194905]

Involvement of Single Nucleotide Variants in the Klotho Gene Among Obesity Individuals with and without Type 2 Diabetes Mellitus in the Saudi Population

Purpose

Aging is characterized by the gradual physiological changes and alterations that accumulate over time in the human body. The combination of obesity and ageing can lead to an increased risk of serious health issues or death. Single nucleotide variants (SNVs) in the Klotho gene were commonly studied, including that in type 2 diabetes mellitus (T2DM).

Aim

The aim of this study is to examine the possible effect of SNVs in Klotho on the obese population in Saudi Arabia using middle-aged participants with and without T2DM.

Methods

This study consists of 100 controls and 100 obesity patients, in which 50 had T2DM and the remaining 50 were obese without T2DM. Genotyping was performed with PCR, and Sanger sequencing analysis was used to validate the molecular association.

Results

In this study, rs1207568 (p = 0.001-0.003) and rs9527025 (p = 0.001-0.00004) SNVs were associated with obesity cases. However, none of the genotypes or allele frequencies showed a positive association with the rs564481 SNV (p = 0.344-0.881). The multiple linear regression model showed that waist and hip were associated (p = 0.01-0.02). ANOVA analysis showed age (p = 0.04), hip (p = 0.002), SBP, and TC (p = 0.02) were associated. Finally, SNV (rs1207568 and rs95270250) and obesity (p < 0.001) associations were confirmed through gene multifactor dimensionality reduction analysis with gene-gene interaction, dendrogram, and graphical depletion method.

Conclusion

This study concludes that rs1207568 and rs9527025 SNVs are associated with obesity in the Saudi population. Additional genetical statistics showed significant association between dependent and independent variables. SNVs in Klotho play a role in the Saudi population's susceptibility to obesity.

Proteomics Investigation of the Impact of the Enterococcus faecalis Secretome on MCF-7 Tumor Cells

Breast cancer is the most prevalent form of cancer among women. The microenvironment of a cancer tumor is surrounded by various cells, including the microbiota. An imbalance between microbes and their host may contribute to the development and spread of breast cancer. Therefore, the objective of this study is to investigate the influence of Enterococcus faecalis on a breast cancer cell line (MCF-7) to mimic the luminal A subtype of breast cancer, using an untargeted proteomics approach to analyze the proteomic profiles of breast cancer cells after their treatment with E. faecalis in order to understand the microbiome and its role in the development of cancer. The breast cancer cell line MCF-7 was cultured and then treated with a 10% bacterial supernatant at two time points (24 h and 48 h) at 37 °C in a humidified incubator with 5% CO2. Proteins were then extracted and separated using two-dimensional difference (2D-DIGE) gel electrophoresis, and the statistically significant proteins (p-value < 0.05, fold change > 1.5) were identified via matrix-assisted laser desorption/ionization-time-of-flight mass spectrometry (MALDI-TOF-MS). The protein fingerprints showed a differential protein expression pattern in the cells treated with E. faecalis for 24 and 48 h compared with the control. We found 58 statistically significant proteins changes in the MCF-7 breast cancer cells affected by E. faecalis. Kilin and transgelin were upregulated after 24 h of treatment and could be used as diagnostic and prognostic markers for breast cancer. In addition, another protein involved in the inhibition of cell proliferation was coiled-coil domain-containing protein 154. The protein markers identified in this study may serve as possible biomarkers for breast cancer progression. This promotes their future uses as important therapeutic goals in the treatment and diagnosis of cancer and increases our understanding of the breast microbiome and its role in the development of cancer.

Urinary Proteome Differences in Patients with Type 2 Diabetes Pre and Post Liraglutide Treatment

Diabetes mellitus is a chronic multisystem disease with a high global prevalence. The glucagon-like peptide-1 (GLP-1) receptor agonist liraglutide is known to lower glucose levels and reduce weight. However, the mechanisms underlying the benefits of liraglutide treatment in patients with type 2 diabetes mellitus (T2DM) remain unclear. Twelve male patients with T2DM (pre and post liraglutide treatment) and HbA1c between 8% and 11% were recruited. In the present study, a two-dimensional difference gel electrophoresis (2D-DIGE) matrix-assisted laser desorption/ionization-time of flight (MALDI TOF) mass spectrometric approach combined with bioinformatics and network pathway analysis was used to explore the urine proteomic profile. The mean age of the patients was 52.4 ± 7.5 years. After treatment with liraglutide, a statistically significant change (p < 0.006) was observed in HbA1c with no significant changes in body weight or markers of dyslipidemia. Two-dimensional difference gel electrophoresis identified significant changes (≥1.5-fold change, ANOVA, p ≤ 0.05) in 32 proteins (4 down- and 28 upregulated) in liraglutide post treatment compared to the pre-treatment state. Albumin, serotransferrin, metallothionein-2 (MT-2), and keratins K1 and K10 were found to be upregulated after liraglutide treatment. The patients showed significant improvement in glycemic control after the 12-week treatment with liraglutide. The renoprotective effect of liraglutide may be linked to the increased urinary abundance of MT-2 and the decreased abundance of zinc alpha 2-glycoprotein (ZAG) and Alpha-1 antitrypsin (α1-AT). More studies are needed to elucidate the molecular mechanisms behind the renoprotective effects of liraglutide.

DIGE Analysis of Clinical Specimens

Two-dimensional difference gel electrophoresis (2D-DIGE) is an elegant gel electrophoretic analytical tool for comparative protein assessment. It is based on two-dimensional gel electrophoresis (2D-GE) separation of fluorescently labeled protein extracts. The tagging procedures are designed to not interfere with the chemical properties of proteins with respect to their pI and electrophoretic mobility, once a proper labeling protocol is followed. The use of an internal pooled standard makes 2D-DIGE a highly accurate quantitative method enabling multiple protein samples to be separated on the same two-dimensional gel. Technical limitations of this technique (i.e., underrating of low abundant, high molecular mass and integral membrane proteins) are counterbalanced by the incomparable separation power which allows proteoforms and unknown PTM (posttranslational modification) identification. Moreover, the image matching and cross-gel statistical analysis generates robust quantitative results making data validation by independent technologies successful.

The Clinical Significance of Urinary Retinol-Binding Protein 4: A Review

Effective biomarkers for early diagnosis, prognostication, and monitoring in renal diseases (in general) comprise an unmet need. Urinary retinol-binding protein 4, which is the most sensitive indicator of renal tubular damage, holds great promise as a universal biomarker for renal pathologies, in which tubular injury is the driving force. Here, we summarize the most important existing data on the associations between urinary retinol-binding protein 4 and renal diseases and highlight the untapped potential of retinol-binding protein 4 in clinical use.

2D-DIGE based urinary proteomics and functional enrichment studies to reveal novel Mycobacterium tuberculosis and human protein biomarker candidates for pulmonary tuberculosis

In the absence of a sensitive and specific diagnostic modality capable of detecting all forms of tuberculosis (TB), proteomics may identify specific Mycobacterium tuberculosis (M.tb) proteins in urine, with a potential as biomarkers. To identify candidate biomarkers for TB, proteome profile of urine from pulmonary TB patients was compared with non-disease controls (NDC) and disease controls (DC, Streptococcus pneumonia infected patients) using a combination of two-dimensional difference gel electrophoresis (2D-DIGE) and liquid chromatography tandem mass spectrometry (LCMS/MS). Eleven differentially expressed host proteins and Eighteen high abundant M.tb proteins were identified. Protein-protein interactome (PPI) and functional enrichment analyses like Gene Ontologies, Reactome pathway etc. demonstrated that the human proteins mainly belong to extracellular space and show physiological pathways for immune response and hematological disorders. Whereas, M.tb proteins belong to the cell periphery, plasma membrane and cell wall, and demonstrated catalytic, nucleotide binding and ATPase activities along with other functional processes. The study findings provide valuable inputs about the biomarkers of TB and shed light on the probable disease consequences as an outcome of the bacterial pathogenicity.

MALDI-TOF MS Characterisation of the Serum Proteomic Profile in Insulin-Resistant Normal-Weight Individuals

Insulin resistance (IR) is one of the most common metabolic disorders worldwide and is involved in the development of diseases, such as diabetes and cardiovascular diseases, affecting civilisations. The possibility of understanding the molecular mechanism and searching for new biomarkers useful in assessing IR can be achieved through modern research techniques such as proteomics. This study assessed the protein–peptide profile among normal-weight patients with IR to understand the mechanisms and to define new risk biomarkers. The research involved 21 IR and 43 healthy, normal-weight individuals, aged 19–65. Serum proteomic patterns were obtained using matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry. The proposed methodology identified six proteins differentiating normal weight IR and insulin sensitive individuals. They were fibrinogen alpha chain, serum albumin, kininogen-1, complement C3, serotransferrin, and Ig gamma-1 chain, which could potentially be related to inflammation. However, further investigation is required to confirm their correlation with IR.

Obesity, metabolic health and omics: Current status and future directions

The growing obesity epidemic is becoming a major public health concern, and the associated costs represent a considerable burden on societies. Among the most common complications of severe obesity are the development of hypertension, dyslipidemia, type 2 diabetes, cardiovascular disease, and various types of cancer. Interestingly, some obese individuals have a favorable metabolic profile and appear to be somehow protected from the detrimental effects of excessive adipose tissue accumulation. These individuals remain normoglycemic, insulin sensitive, and hypotensive with proper blood lipid levels, despite their high body mass index and/or waist circumference. Multiple independent observations have led to the concept of the metabolically healthy obese (MHO) phenotype, yet no consensus has been reached to date regarding a universal definition or the main mechanism behind this phenomenon. Recent technological advances and the use of high-throughput analysis techniques have revolutionized different areas of biomedical research. A multi-omics approach, which is used to investigate changes at different molecular levels in an organism or tissue, may provide valuable insights into the interplay between the molecules or pathways and the roles of different factors involved in the mechanisms underlying metabolic health deterioration. The aim of this review is to present the current status regarding the use of omics technologies to investigate the MHO phenotype, as well as the results of targeted analyses conducted in MHO individuals.

Identification of Protein Changes in the Urine of Hypothyroid Patients Treated with Thyroxine Using Proteomics Approach

The thyroid gland and thyroid hormones control a multitude of homeostatic functions including maintenance of fluid and electrolyte balance and normal functioning of the kidneys. Thyroid dysfunction alters the sytemic hemodynamic and metabolic balance, thereby affecting the kidney. In this study, we aimed to identify and characterize the urinary proteome of the patients with hypothyroidism. An untargeted proteomic approach with network analysis was used to identify changes in total urinary proteome in patients with newly diagnosed overt hypothyroidism. Urine samples were collected from nine age-matched patients' before and after l-thyroxine treatment. Differences in the abundance of urinary proteins between hypothyroid and euthyroid states were determined using a two-dimensional difference in gel electrophoresis (2D-DIGE) coupled to matrix-assisted laser desorption and ionization time-of-flight (MALDI TOF) mass spectrometry. Alterations in the abundance of urinary proteins, analyzed by Progenesis software, revealed statistically significant differential abundance in a total of 49 spots corresponding to 42 proteins, 28 up and 14 down (≥1.5-fold change, analysis of variance (ANOVA), p ≤ 0.05). The proteins identified in the study are known to regulate processes related to transport, acute phase response, oxidative stress, generation of reactive oxygen species, cellular proliferation, and endocytosis. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) identified dysregulation of pathways related to amino acid metabolism, molecular transport, and small-molecule biochemistry and involved the MAPK kinase, vascular endothelial growth factor (VEGF), PI3 kinase/Akt, protein kinase C (PKC), signaling pathways. The identified proteins were involved in the regulation of thyroglobulin (Tg) and thyrotropin (TSH) metabolism. Alterations in their levels indicate the presence of a compensatory mechanism aimed at increasing the regulation of Tg in the hypothyroid state.

Antimicrobial Mechanism and Identification of the Proteins Mediated by Extracts from Asphaltum punjabianum and Myrtus communis

Myrtus communis ("myrtle") and Asphaltum punjabianum ("shilajeet") are a medicinal plant and a long-term-humified dead plant material, respectively. We studied their antibacterial and anticandidal activities against Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus, and Candida albicans. The activities of the aqueous extracts of the studied materials were measured using agar-well diffusion methods. Furthermore, proteomic analysis of treated microbial cells was conducted to identify affected proteins. The results showed both antibacterial and anticandidal activities for the myrtle extract (ME), while the shilajeet extract (SE) showed antibacterial activity only. The highest antimicrobial activity was observed against E. coli among the microbes tested; therefore, it was taken as the model for the proteomic analysis to identify the antimicrobial mechanism of ME and SE using two-dimensional electrophoresis. Upregulation of expression of 42 proteins and downregulation of expression of 6 proteins were observed in E. coli treated with ME, whereas 12 upregulated and 104 downregulated proteins were detected in E. coli treated with SE, in comparison with the control. About 85% of identified expressed proteins were from the cytoplasm and 15% from microbial cell walls, indicating the penetration of extracts inside cells. A higher percentage of expressed proteins was recorded for enzymatic activity. Our findings suggest that the major targets of the antibacterial action were proteins involved in the outer membrane, oxidative stress, and metabolism. Our data might reveal new targets for antimicrobial agents.

Serum-Based Proteomics Profiling in Adult Patients with Cystic Fibrosis

Cystic fibrosis (CF), the most common lethal autosomal recessive disorder among Caucasians, is caused by mutations in the CF transmembrane conductance regulator (CFTR) chloride channel gene. Despite significant advances in the management of CF patients, novel disease-related biomarkers and therapies must be identified. We performed serum proteomics profiling in CF patients (n = 28) and healthy subjects (n = 10) using the 2D-DIGE MALDI-TOF proteomic approach. Out of a total of 198 proteins identified, 134 showed a statistically significant difference in abundance and a 1.5-fold change (ANOVA, p < 0.05), including 80 proteins with increased abundance and 54 proteins with decreased abundance in CF patients. A multiple reaction monitoring-mass spectrometry analysis of six differentially expressed proteins identified by a proteomic approach (DIGE-MALD-MS) showed a significant increase in C3 and CP proteins and a decrease in APOA1, Complement C1, Hp, and RBP4proteins compared with healthy controls. Fifteen proteins were identified as potential biomarkers for CF diagnosis. An ingenuity pathway analysis of the differentially regulated proteins indicates that the central nodes dysregulated in CF subjects involve pro-inflammatory cytokines, ERK1/2, and P38 MAPK, which are primarily involved in catalytic activities and metabolic processes. The involved canonical pathways include those related to FXR/RXR, LXR/RXR, acute phase response, IL12, nitric oxide, and reactive oxygen species in macrophages. Our data support the current efforts toward augmenting protease inhibitors in patients with CF. Perturbations in lipid and vitamin metabolism frequently observed in CF patients may be partly due to abnormalities in their transport mechanism.

Serum proteomic profiling of patients with amphetamine use disorder

BACKGROUND

Amphetamine use disorder has been recently classified as an epidemic condition. Amphetamine use/abuse has been associated with several neurological and inflammatory effects. However, the exact mechanism involved in these effects warrants further investigation. The aim of this study was to determine any alterations in the serum proteome of individuals classified as patients with amphetamine use disorder compared to that of control subjects.

METHODS

An untargeted proteomic approach employing two-dimensional difference in gel electrophoresis coupled with mass spectrometry was used to identify the patterns of differentially expressed proteins. Serum samples were collected from 20 individuals (males) including 10 subjects with amphetamine use disorder and 10 healthy controls for the present study.

RESULTS

The analysis revealed 78 proteins with a significant difference in protein abundance between the amphetamine-addicted subjects and controls. Among them, 71 proteins were upregulated while 7 proteins remained downregulated in the amphetamine-addicted group. These proteins were further analyzed by ingenuity pathway analysis (IPA) to investigate their correlation with other biomarkers. IPA revealed the correlation of altered proteins with mitogen-activated protein kinase (MAP2K1/K2), p38MAPK, protein kinase-B (PKB; Akt), extracellular signal-regulated kinase (ERK1/2), and nuclear factor-κB signaling pathways. Importantly, these pathways are highly involved in neurological diseases, inflammatory responses, and cellular compromise.

CONCLUSIONS

Our data suggest that the changes in the levels of serum proteins between amphetamine and control groups might affect cellular compromise, inflammatory response, and neurological diseases.

Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis

Recent advances in mass spectrometry (MS)-based proteomics have enabled tremendous progress in the understanding of cellular mechanisms, disease progression, and the relationship between genotype and phenotype. Though many popular bioinformatics methods in proteomics are derived from other omics studies, novel analysis strategies are required to deal with the unique characteristics of proteomics data. In this review, we discuss the current developments in the bioinformatics methods used in proteomics and how they facilitate the mechanistic understanding of biological processes. We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods that have been developed to perform comprehensive analysis in proteomics studies. We conclude with a discussion of how quantitative protein data can be used to reconstruct protein interactions and signaling networks.

A proteomic approach towards understanding crypoprotective action of Me2SO on the CHO cell proteome

Chinese hamster ovary (CHO) cell lines are the most widely used in vitro cells for research and production of recombinant proteins such as rhGH, tPA, and erythropoietin. We aimed to investigate changes in protein profiles after cryopreservation using 2D-DIGE MALDI-TOF MS and network pathway analysis. The proteome changes that occur in CHO cells between freshly prepared cells and cryopreserved cells with and without Me2SO were compared to determine the key proteins and pathways altered during recovery from cryopreservation. A total of 54 proteins were identified and successfully matched to 37 peptide mass fingerprints (PMF). 14 protein spots showed an increase while 23 showed decrease abundance in the Me2SO free group compared to the control. The proteins with increased abundance included vimentin, heat shock protein 60 kDa, mitochondrial, heat shock 70 kDa protein 9, protein disulfide-isomerase A3, voltage-dependent anion-selective channel protein 2. Those with a decrease in abundance were myotubularin, glutathione peroxidase, enolase, phospho glyceromutase, chloride intracellular channel protein 1. The main canonical functional pathway affected involved the unfolded protein response, aldosterone Signaling in Epithelial Cells, 14-3-3-mediated signaling. 2D-DIGE MALDI TOF mass spectrometry and network pathway analysis revealed the differential proteome expression of FreeStyle CHO cells after cryopreservation with and without 5% Me2SOto involve pathways related to post-translational modification, protein folding and cell death and survival (score = 56, 22 focus molecules). This study revealed, for the first time to our knowledge the proteins and their regulated pathways involved in the cryoprotective action of 5% Me2SO. The use of 5% Me2SO as a cryoprotectant maintained the CHO cell proteome in the cryopreserved cells, similar to that of fresh CHO cells.

Metabolically Healthy Obesity (MHO)-New Research Directions for Personalised Medicine in Cardiovascular Prevention

PURPOSE OF REVIEW

To discuss new findings on the heterogeneity of obesity and associated risks.

RECENT FINDINGS

Obesity is a public health problem of immense importance on a global scale. However, epidemiological findings and clinical studies have revealed that obesity is a heterogeneous phenotype and that not all obese subjects run the same risk for complications. Current research has tried to describe so-called metabolically healthy obesity (MHO), defined by lack of risk factors included in the metabolic syndrome. These subjects will not escape long-term complications, but mortality risk is not increased. However, a new definition of MHO has recently been proposed, based on the lack of hospitalisation for somatic disease for decades in middle life. MHO subjects defined in this way are characterised by being "fat and fit" and also run a lower risk of long-term complications. If MHO could be better understood, this could contribute to a more diverse clinical approach to obesity based on personalised medicine.

Screening and analysis of small molecular peptides in urine of gestational diabetes mellitus

Gestational diabetes mellitus (GDM) is a common clinical disease with complicated clinical process and harmful effects on pregnant women and fetus. The purpose of this study is to use the convenient urine samples in combination with glucose levels to detect or predict GDM. In this study, urine samples of non-pregnant women, normal pregnant women and GDM patients were collected. The peptides in urine were enriched by weak cationic exchange magnetic beads (MB-WCX) and analyzed by matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). 46 polypeptide peaks with statistical difference (P < 0.01) were screened out by using Bioexplorer analysis software. The level of molecules with mass-to-charge ratio of 1079.2, 1290.6 and 1500.7 was higher in the GDM group than the other two groups. Through the analysis of differential molecules by liquid chromatography tandem mass spectrometry (LC-MS), the above molecules were identified as coagulation factor IX, TBC1 family member 5 isoform a [Homo sapiens] (TBC1D5a) and immunoglobulin kappa constant. The discovery of polypeptides provides the research basis for further primary screening and assistant diagnosis of GDM through urine samples.