Building Block Extractor: An MS/MS Data Mining Tool for Targeted Discovery of Natural Products with Specified Features.

The utilization of a building-block-based molecular network is an efficient approach to investigate the unknown chemical space of natural products. However, structure-based automated MS/MS data mining remains challenging. This study introduces building block extractor, a user-friendly MS/MS data mining program that automatically extracts user-defined specified features. In addition to the characteristic product ions and neutral losses, this program integrates the abundance of the product ions and sequential neutral loss features as building blocks for the first time. The discovery of nine undescribed sesquiterpenoid dimers from Artemisia heptapotamica highlights the power of this tool. One of these dimers, artemiheptolide I (9), exhibited in vitro inhibition of influenza A/Hongkong/8/68 (H3N2) with an IC50 of 8.01 ± 6.19 µM. Furthermore, two known guaianolide derivatives (16 and 17) possessed remarkable antiviral activity against influenza A/Puerto Rico/8/1934 H1N1, H3N2, and influenza B/Lee/40 with IC50 values ranging from 3.46 to 11.77 µM. In addition to the efficient discovery of novel natural products, this strategy can be generally applied to grab derivatives with specific fragments and enhance the annotation power of LC-MS/MS analysis.

A genome-wide scan for quantitative trait loci affecting serum glucose and lipids in a White Duroc x Erhualian intercross F(2) population.

Serum glucose and lipid levels are associated with diabetes mellitus and cardiovascular disease. The purpose of this study was to identify quantitative trait loci (QTL) for serum glucose and lipids in a White Duroc x Erhualian resource population. Serum glucose, glycosylated serum proteins (GSP), and serum lipid levels were measured in a total of 760 F(2) animals at 240 days. Strong positive correlations were observed between total cholesterol (TC) and low-density-lipoprotein cholesterol (LDL-C)/high-density-lipoprotein cholesterol (HDL-C). A whole-genome scan was performed with 194 microsatellites covering the pig genome across the entire resource population, revealing 2 QTL for serum glucose and 15 QTL for serum lipids. Of them, three 1% genome-wide significant QTL were identified for LDL-C, TC, and triglycerides (TG) in an adjacent region (67-73 cM) on chromosome 2 (SSC2), and the QTL for LDL-C showed the largest effect with a 95% confidence interval of 5 cM. Another 1% genome-wide significant QTL was found for LDL-C at 87 cM on SSC8. Other QTL showed 5% genome-wide significant or suggestive effects on SSC4, 5, 7, 9, 11, 14, and 15. In total, five significant QTL for serum lipids and a suggestive QTL for GSP on SSC4 were identified for the first time in pigs. Most of the identified QTL are homologous to the previously reported QTL for serum lipids in humans and mice. As correlated traits, QTL for TC and LDL-C were always located in the same genomic regions. The results shed new light on studies of human atherosclerosis and cardiovascular-related diseases.