Predicting lupus membranous nephritis using reduced picolinic acid to tryptophan ratio as a urinary biomarker.

The current gold standard for classifying lupus nephritis (LN) progression is a renal biopsy, which is an invasive procedure. Undergoing a series of biopsies for monitoring disease progression and treatments is unlikely suitable for patients with LN. Thus, there is an urgent need for non-invasive alternative biomarkers that can facilitate LN class diagnosis. Such biomarkers will be very useful in guiding intervention strategies to mitigate or treat patients with LN. Urine samples were collected from two independent cohorts. Patients with LN were classified into proliferative (class III/IV) and membranous (class V) by kidney histopathology. Metabolomics was performed to identify potential metabolites, which could be specific for the classification of membranous LN. The ratio of picolinic acid (Pic) to tryptophan (Trp) ([Pic/Trp] ratio) was found to be a promising candidate for LN diagnostic and membranous classification. It has high potential as an alternative biomarker for the non-invasive diagnosis of LN.

High-Resolution QTOF-MRM for Highly Accurate Identification and Quantification of Trace Levels of Triterpenoids in Ganoderma lucidum Mycelium.

The accurate quantification of triterpenoids in Ganoderma lucidum mushroom in the mycelium stage is challenging due to their low concentrations, interference from other possible isomers, and the complex matrix. Here, a high-resolution quadrupole-time-of-flight mass spectrometry "multiple reaction monitoring" with target enhancement (HR-QTOF-MRM) method was developed to quantify seven target triterpenoids in G. lucidum. The performance of this method was compared against an optimized QQQ-MRM method. The HR-QTOF-MRM was shown to be capable of distinguishing target triterpenoids from interferent peaks in the presence of matrices. The HR-QTOF-MRM LOD and LLOQ values were found to be one to two times lower than those derived from the QQQ-MRM method. Intraday and interday variabilities of the HR-QTOF-MRM demonstrated better reproducibility than the QQQ-MRM. In addition, excellent recoveries of the analytes ranging from 80 to 117% were achieved. Spiking experiments were carried out to verify and compare the quantitative accuracy of the two methods. The HR-QTOF-MRM method provided better percent accuracy, ranging from 84% to 99% (<3% RSD), compared with the range of 69 to 114% (<4%RSD) given by the QQQ-MRM method. These results demonstrate that the new HR-QTOF-MRM mode is able to improve sensitivity, reproducibility, and accuracy of trace level analysis of triterpenoids in the complex biological samples. The triterpenoid concentrations were in the range of nondetect to 0.06-6.72 mg/g of dried weight in fruiting body and to 0.0009-0.01 mg/g of dried weight in mycelium.

Natural ACE inhibitory peptides discovery from Spirulina (Arthrospira platensis) strain C1.

Bioactive peptides from natural sources are utilized as food supplements for disease prevention and are increasingly becoming targets for drug discovery due to their specificity, efficacy and the absence of undesirable side effects, among others. Hence, the 'SpirPep' platform was developed to facilitate the in silico-based bioactive peptide discovery of these highly sought-after biomolecules from Spirulina(Arthrospira platensis) and to select the protease (thermolysin) used for in vitro digestion. Analysis of the predicted and experimentally-derived peptides suggested that they were mainly involved in ACE inhibition; thus, an ACEi assay was used to study the ACE inhibitory activity of five candidate peptides (SpirPep1-5), chosen from common peptides with multifunctional bioactivity and 100% bioactive peptide coverage, originating from phycobiliproteins. Results showed that SpirPep1 inhibited the activity of ACE with IC50 of 1.748 mM and was non-toxic to fibroblasts of African green monkey kidney and human dermal skin. The molecular docking and MD simulation analysis revealed SpirPep1 had significantly lower binding scores than others and showed greater specificity to ACE. The non-bonded interaction energy of SpirPep1 and ACE was -883 kJ/mol. The SpirPep1 indirectly bound to ACE via the ACE substrate binding sites residues (D121, E123, S516, and S517) found in natural ACE inhibitory peptides (angiotensin II and bradykinin potentiating peptides). In addition, two unreported substrate binding sites including R124 and S219 were found. These results indicate that 'SpirPep' platform could increase the success rate for natural bioactive peptide discovery.

SpirPep: an in silico digestion-based platform to assist bioactive peptides discovery from a genome-wide database.

BACKGROUND: Bioactive peptides, including biological sources-derived peptides with different biological activities, are protein fragments that influence the functions or conditions of organisms, in particular humans and animals. Conventional methods of identifying bioactive peptides are time-consuming and costly. To quicken the processes, several bioinformatics tools are recently used to facilitate screening of the potential peptides prior their activity assessment in vitro and/or in vivo. In this study, we developed an efficient computational method, SpirPep, which offers many advantages over the currently available tools. RESULTS: The SpirPep web application tool is a one-stop analysis and visualization facility to assist bioactive peptide discovery. The tool is equipped with 15 customized enzymes and 1-3 miscleavage options, which allows in silico digestion of protein sequences encoded by protein-coding genes from single, multiple, or genome-wide scaling, and then directly classifies the peptides by bioactivity using an in-house database that contains bioactive peptides collected from 13 public databases. With this tool, the resulting peptides are categorized by each selected enzyme, and shown in a tabular format where the peptide sequences can be tracked back to their original proteins. The developed tool and webpages are coded in PHP and HTML with CSS/JavaScript. Moreover, the tool allows protein-peptide alignment visualization by Generic Genome Browser (GBrowse) to display the region and details of the proteins and peptides within each parameter, while considering digestion design for the desirable bioactivity. SpirPep is efficient; it takes less than 20 min to digest 3000 proteins (751,860 amino acids) with 15 enzymes and three miscleavages for each enzyme, and only a few seconds for single enzyme digestion. Obviously, the tool identified more bioactive peptides than that of the benchmarked tool; an example of validated pentapeptide (FLPIL) from LC-MS/MS was demonstrated. The web and database server are available at http://spirpepapp.sbi.kmutt.ac.th . CONCLUSION: SpirPep, a web-based bioactive peptide discovery application, is an in silico-based tool with an overview of the results. The platform is a one-stop analysis and visualization facility; and offers advantages over the currently available tools. This tool may be useful for further bioactivity analysis and the quantitative discovery of desirable peptides.