Phylogenomics and barcoding of Panax: toward the identification of ginseng species.

BACKGROUND: The economic value of ginseng in the global medicinal plant trade is estimated to be in excess of US$2.1 billion. At the same time, the evolutionary placement of ginseng (Panax ginseng) and the complex evolutionary history of the genus is poorly understood despite several molecular phylogenetic studies. In this study, we use a full plastome phylogenomic framework to resolve relationships in Panax and to identify molecular markers for species discrimination. RESULTS: We used high-throughput sequencing of MBD2-Fc fractionated Panax DNA to supplement publicly available plastid genomes to create a phylogeny based on fully assembled and annotated plastid genomes from 60 accessions of 8 species. The plastome phylogeny based on a 163 kbp matrix resolves the sister relationship of Panax ginseng with P. quinquefolius. The closely related species P. vietnamensis is supported as sister of P. japonicus. The plastome matrix also shows that the markers trnC-rps16, trnS-trnG, and trnE-trnM could be used for unambiguous molecular identification of all the represented species in the genus. CONCLUSIONS: MBD2 depletion reduces the cost of plastome sequencing, which makes it a cost-effective alternative to Sanger sequencing based DNA barcoding for molecular identification. The plastome phylogeny provides a robust framework that can be used to study the evolution of morphological characters and biosynthesis pathways of ginsengosides for phylogenetic bioprospecting. Molecular identification of ginseng species is essential for authenticating ginseng in international trade and it provides an incentive for manufacturers to create authentic products with verified ingredients.

Quantitative structure-activity relationship analysis and virtual screening studies for identifying HDAC2 inhibitors from known HDAC bioactive chemical libraries.

Histone deacetylases (HDAC) are emerging as promising targets in cancer, neuronal diseases and immune disorders. Computational modelling approaches have been widely applied for the virtual screening and rational design of novel HDAC inhibitors. In this study, different machine learning (ML) techniques were applied for the development of models that accurately discriminate HDAC2 inhibitors form non-inhibitors. The obtained models showed encouraging results, with the global accuracy in the external set ranging from 0.83 to 0.90. Various aspects related to the comparison of modelling techniques, applicability domain and descriptor interpretations were discussed. Finally, consensus predictions of these models were used for screening HDAC2 inhibitors from four chemical libraries whose bioactivities against HDAC1, HDAC3, HDAC6 and HDAC8 have been known. According to the results of virtual screening assays, structures of some hits with pair-isoform-selective activity (between HDAC2 and other HDACs) were revealed. This study illustrates the power of ML-based QSAR approaches for the screening and discovery of potent, isoform-selective HDACIs.

Comparative study to predict toxic modes of action of phenols from molecular structures.

Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. Most of them showed global accuracy of over 90%, and false alarm rate values were below 2.9% for the training set. Cross-validation, complementary subsets and external test set were performed, with good behaviour in all cases. Our models compare favourably with other previously published models, and in general the models obtained with ML techniques show better results than those developed with linear techniques. We developed unsupervised and supervised consensus, and these results were better than our ML models, the results of rule-based approach and other ensemble models previously published. This investigation highlights the merits of ML-based techniques as an alternative to other more traditional methods for modelling MOA.

Pathotype Identification of Xanthomonas citri pv. citri Strains Causing Citrus Canker in Vietnam.

Asiatic citrus canker caused by Xanthomonas citri pv. citri is a bacterial disease of major economic importance in tropical and subtropical citrus-producing areas. It probably originated in Asia (2). X. citri pv. citri induces erumpent, callus-like lesions with a water-soaked margin on aerial organs of the plants. Severe attacks cause premature fruit drop and twig dieback. This pathogen has consequently been subjected to international quarantine regulation and eradication efforts. Two pathogenic variants of X. citri pv. citri can be separated by their host range. X. citri pv. citri pathotype A strains cause severe infection worldwide in a wide range of citrus species; grapefruit (Citrus paradisi) is particularly susceptible. More recently, another group of strains from different areas of West Asia has been designated as X. citri pv. citri pathotype A* (4). These A* strains are genetically related to X. citri pv. citri, but their host range is primarily restricted to Mexican lime (C. aurantifolia) and they do not infect grapefruit. Strains similar in host range were later reported in Florida, Thailand, and Cambodia (2). In this study, we investigated the distribution of X. citri pv. citri pathotypes in Southeast Asia. A large survey on citrus was conducted in 14 provinces in the north (Ha Noi, Hung Yen, Nghe Han, Ha Ting, and Phu Tho) and south (Can Tho, Long An, Dong Nai, Tien Giang, Vinh Long, Ben Tre, Dong Thap, Vung Tau, and Lam Dong) of Vietnam. We collected 557 X. citri pv. citri isolates, after cultivation on KC semiselective medium (3), from citrus species, including 60 strains from Mexican lime in eight provinces. Ligation mediated (IS-LM)-PCR analysis using primers targeting three insertion sequences (1) was done on all Vietnamese strains and on additional reference strains of X. citri pv. citri-A, -A*, and X. citri pv. aurantifolii. IS-LM-PCR indicated that all Vietnamese isolates were pathotype A and did not include any with a restricted host range (X. citri pv. citri-A* and X. citri pv. aurantifolii). Amplified fragment length polymorphism (AFLP) analysis was carried out on a subset of 84 X. citri pv. citri strains, including 22 strains from Mexican lime from seven provinces. AFLP was carried out using SacI/MspI and four primer pairs (unlabeled MspI +1 [A, C, T or G] primers and 5'-labeled - SacI + C primer for the selective amplification step) (2) and the data confirmed that all Vietnamese X. citri pv. citri strains were genetically related to pathotype A strains. Mexican lime and Duncan grapefruit or pineapple sweet orange leaves were inoculated with 25 strains from lime (representative of the genetic diversity) using a detached leaf assay (3) and they produced typical canker lesions on both host species. In spite of the presence of pathotype A* strains in neighboring countries (2), no strains genetically or pathogenically related to this pathotype were identified in this collection. A survey of commercial Mexican lime orchards, especially in Vietnamese provinces bordering Cambodia, should be undertaken to detect and eradicate A* strains because these are known to strongly impact lime production in other parts of Asia (e.g., Thailand). References: (1) L. Bui Thi Ngoc et al. Appl. Environ. Microbiol. 75:1173, 2009. (2) L. Bui Thi Ngoc et al. FEMS Microbiol. Lett. 288:33, 2008. (3) O. Pruvost et al. J. Appl. Microbiol. 99:803, 2005. (4) C. Vernière et al. Eur. J. Plant Pathol. 104:477, 1998.