RESUMEN
Diabetic nephropathy is a leading cause of end-stage renal disease. Hence, early detection of diabetic nephropathy is essential to mitigate the disease burden. Microalbuminuria, the currently used diagnostic marker of diabetic nephropathy, is not efficient in detecting it at an early stage. Therefore, we explored the utility of glycated human serum albumin (HSA) peptides for risk prediction of diabetic nephropathy. Three glycation-sensitive HSA peptides, namely, FKDLGEENFK, KQTALVELVK, and KVPQVSTPTLVEVSR, with deoxyfructosyllysine (DFL) modification were quantified by targeted mass spectrometry (MS) in a study population comprising healthy and type II diabetes subjects with and without nephropathy. Mass spectrometry, receiver operating characteristic (ROC) curve, and correlation analysis revealed that the DFL-modified KQTALVELVK peptide was better than other glycated HSA peptides and HbA1c for identifying diabetic nephropathy. DFL-modified KQTALVELVK could be a potential marker for risk prediction of diabetic nephropathy.
RESUMEN
Microbial glycolipids are one of the most interesting alternatives to chemical-based surfactants as they exhibit improved biodegradability and less toxicity. However, their potential has been limited because of specificity of the yeast toward fatty acids having a carbon 16 or carbon 18 chain. This study focuses on sophorolipid (SL) production by the yeast Starmerella bombicola using myristic acid, a medium-chain carbon-14 fatty acid that has not been used as a substrate for SL production. The production was optimized for inoculum size and lipophilic substrate concentration. Furthermore, we also studied the effect of medium-chain fatty acid on yeast cell growth and optimized the process for excellent yield. The myristic acid SL (MASL) so synthesized consisted of mono- and diacetylated forms with preferential glycosylation at the methyl end group, as determined by high-resolution mass spectrometry. Individual congeners of the crude mixture were separated using dry column chromatography and then structurally characterized by mass spectrometry. The synthesized MASL was also shown to have promising surface tension, lowering abilities with a low CMC of 14 mg/L. The SL derived from myristic acid exhibited superior antibacterial activity as compared to SL derived from oleic acid. MASL was also found to be more potent against Gram-positive organisms as compared to Gram-negative organisms. This work, therefore, demonstrates successful synthesis of myristic acid-derived SL and its superior antibacterial activity, establishing a promising future for this biosurfactant.
RESUMEN
Being molecularly heterogeneous, breast cancer tends to be a complicated oncological disease with high incidence rates throughout the world. The primary aim of this study was to identify the set of serum proteins with discriminatory capabilities towards the four major subtypes of breast cancer. We employed multipronged quantitative proteomic approaches like 2D-DIGE, iTRAQ and SWATH-MS and identified 307 differentially regulated proteins. Luminal A subtype consisted of 24, Luminal B subtype 38, HER2 Enriched subtype 17 and Triple negative breast cancer subtype 10 differentially regulated subtype specific proteins. These specific proteins were further subjected to bioinformatic tools which revealed the involvement in platelet degranulation, fibrinolysis, lipid metabolism, immune response, complement activation, blood coagulation, glycolysis and cancer signaling pathways in the subtypes of the breast cancer. The significant discrimination efficiency of the models generated through multivariate statistical analysis was decent to distinguish each of the four subtypes from controls. Further, some of the statistically significant differentially regulated proteins were verified and validated by immunoblotting and mass spectrometry based selected reaction monitoring (SRM) approach. Our Multipronged proteomics approaches revealed panel of serum proteins specifically altered for individual subtypes of breast cancer. The mass spectrometry data are available via ProteomeXchange with identifier PXD006441. BIOLOGICAL SIGNIFICANCE: Worldwide, breast cancer continues to be one of the leading causes of cancer related deaths in women and it encompasses four major molecular subtypes. As breast cancer treatment majorly depends on identification of specific subtype, it is important to diagnosis the disease at subtype level. Our results using multipronged quantitative proteomics identified 307 differentially regulated proteins in which 24 were specific for Luminal A, 38 for Luminal B, 17 for HER2 enriched and 10 proteins were specific for TN subtype. Bioinformatic analysis of these proteins revealed certain biological processes and pathways altered at subtype level and validation experiments of some of these proteins using immunoblotting and SRM assays are consistent with discovery data. This is the first comprehensive proteomic study on serum proteome alterations at subtype level which will not only help to distinguish subtype of breast cancer but also contribute to a better understanding of the molecular characteristic of breast cancer at individual subtype level.
Asunto(s)
Neoplasias de la Mama/sangre , Neoplasias de la Mama/diagnóstico , Proteínas de Neoplasias/sangre , Proteoma/análisis , Neoplasias de la Mama/química , Neoplasias de la Mama/clasificación , Electroforesis en Gel Bidimensional , Femenino , Regulación Neoplásica de la Expresión Génica , Humanos , Proteómica/métodosRESUMEN
Globally, breast cancer is the second most common cancer among women. Although biomarker discoveries through various proteomic approaches of tissue and serum samples have been studied in breast cancer, urinary proteome alterations in breast cancer are least studied. Urine being a noninvasive biofluid and a significant source of proteins, it has the potential in early diagnosis of breast cancer. This study used complementary quantitative gel-based and gel-free proteomic approaches to find a panel of urinary protein markers that could discriminate HER2 enriched (HE) subtype breast cancer from the healthy controls. A total of 183 differentially expressed proteins were identified using three complementary approaches, namely 2D-DIGE, iTRAQ, and sequential window acquisition of all theoretical mass spectra. The differentially expressed proteins were subjected to various bioinformatics analyses for deciphering the biological context of these proteins using protein analysis through evolutionary relationships, database for annotation, visualization and integrated discovery, and STRING. Multivariate statistical analysis was undertaken to identify the set of most significant proteins, which could discriminate HE breast cancer from healthy controls. Immunoblotting and MRM-based validation in a separate cohort testified a panel of 21 proteins such as zinc-alpha2-glycoprotein, A2GL, retinol-binding protein 4, annexin A1, SAP3, SRC8, gelsolin, kininogen 1, CO9, clusterin, ceruloplasmin, and α1-antitrypsin could be a panel of candidate markers that could discriminate HE breast cancer from healthy controls.