Kolavenic acid analog restores growth in HSET-overproducing fission yeast cells and multipolar mitosis in MDA-MB-231 human cells

Although cancer cells often harbor supernumerary centrosomes, they form pseudo-bipolar spindles via centrosome clustering, instead of lethal multipolar spindles, and thus avoid cell death. Kinesin-14 HSET/KIFC1 is a crucial protein involved in centrosome clustering. Accordingly, a compound that targets HSET could potentially inhibit cancer cell proliferation in a targeted manner. Here, we report three natural compounds derived from Solidago altissima that restored the growth of fission yeast cells exhibiting lethal HSET overproduction (positive screening), namely solidagonic acid (SA) (1), kolavenic acid analog (KAA: a stereo isomer at C-9 and C-10 of 6β-tigloyloxykolavenic acid) (2), and kolavenic acid (KA) (3). All three compounds suppressed fission yeast cell death and enabled reversion of the mitotic spindles from a monopolar to bipolar morphology. Compound 2, which exerted the strongest activity against HSET-overproducing yeast cells, also inhibited centrosome clustering in MDA-MB-231 human breast adenocarcinoma cells, which contained large numbers of supernumerary centrosomes. These natural compounds may be useful as bioprobes in studies of HSET function. Moreover, compound 2 is a prime contender in the development of novel agents for cancer treatment.     

Automated analysis of courtship suppression learning and memory in Drosophila melanogaster

Study of the fruit fly, Drosophila melanogaster, has yielded important insights into the underlying molecular mechanisms of learning and memory. Courtship conditioning is a well-established behavioral assay used to study Drosophila learning and memory. Here, we describe the development of software to analyze courtship suppression assay data that correctly identifies normal or abnormal learning and memory traits of individual flies. Development of this automated analysis software will significantly enhance our ability to use this assay in large-scale genetic screens and disease modeling. The software increases the consistency, objectivity, and types of data generated.     

MicroRNA 32 promotes cell proliferation,migration, and suppresses apoptosis in colon cancer cells by targeting OTU domain containing 3

Colorectal cancer is considered as the fourth leading reason of cancer-linked deaths worldwide. However, our knowledge about its pathogenic mechanism remains inadequate. MicroRNA 32 (miR-32), a member of small noncoding RNAs, has been found vital roles in tumorigenesis. This study studied its functions and underlying mechanism in colorectal cancer. The experiment revealed the obvious upregulation of miR-32 in colorectal cancer tissues and six cancer cell lines, compared with normal tissues and cells. Moreover, miR-32 upregulation reduced cell apoptosis and promoted cell proliferation and migration, while its downregulation displayed opposite effects. Dual luciferase reporter assays proved that miR-32 bound to the 3′-untranslated region (3′-UTR) of OTU domain containing 3 (OTUD3), suggesting that miR-32 directly targeted OTUD3. Further experiments demonstrated that overexpression of miR-32 could reduce the expression level of OTUD3. Furthermore, OTUD3 silence promoted proliferation and motility and decreased apoptosis for HCT116 cells and restored partly miR-32-mediated cell proliferation, migration, and antiapoptosis for colon cancer. Therefore, our study indicated that miR-32 enhanced cell proliferation and motility abilities, and inhibited apoptosis by directly targeting OTUD3 in colon cancer cells, which implied that miR-32 was hopeful to be a biomarker or target used for diagnosis and therapy of colon cancer.     

Higher-order interhelical spatial interactions in membrane proteins

Higher-order interactions are important for protein folding and assembly. We introduce the concept of interhelical three-body interactions as derived from Delaunay triangulation and alpha shapes of protein structures. In addition to glycophorin A, where triplets are strongly correlated with protein stability, we found that tight interhelical triplet interactions exist extensively in other membrane proteins, where many types of triplets occur far more frequently than in soluble proteins. We developed a probabilistic model for estimating the value of membrane helical interaction triplet (MHIT) propensity. Because the number of known structures of membrane proteins is limited, we developed a bootstrap method for determining the 95% confidence intervals of estimated MHIT values. We identified triplets that have high propensity for interhelical interactions and are unique to membrane proteins, e.g. AGF, AGG, GLL, GFF and others. A significant fraction (32%) of triplet types contains triplets that may be involved in interhelical hydrogen bond interactions, suggesting the prevalent and important roles of H-bond in the assembly of TM helices. There are several well-defined spatial conformations for triplet interactions on helices with similar parallel or antiparallel orientations and with similar right-handed or left-handed crossing angles. Often, they contain small residues and correspond to the regions of the closest contact between helices. Sequence motifs such as GG4 and AG4 can be part of the three-body interactions that have similar conformations, which in turn can be part of a higher-order cooperative four residue spatial motif observed in helical pairs from different proteins. In many cases, spatial motifs such as serine zipper and polar clamp are part of triplet interactions. On the basis of the analysis of the archaeal rhodopsin family of proteins, tightly packed triplet interactions can be achieved with several different choices of amino acid residues.     

Population structure of the butternut canker fungus,Ophiognomonia clavigignenti‐juglandacearum,in North American forests

The occurrence of multiple introduction events, or sudden emergence from a host jump, of forest pathogens may be an important factor in successful establishment in a novel environment or on a new host; however, few studies have focused on the introduction and emergence of fungal pathogens in forest ecosystems. While Ophiognomonia clavigignenti‐juglandacearum (Oc‐j), the butternut canker fungus, has caused range‐wide mortality of butternut trees in North America since its first observation in 1967, the history of its emergence and spread across the United States and Canada remains unresolved. Using 17 single nucleotide polymorphic loci, we investigated the genetic population structure of 101 isolates of Oc‐j from across North America. Clustering analysis revealed that the Oc‐j population in North America is made up of three differentiated genetic clusters of isolates, and these genetic clusters were found to have a strong clonal structure. These results, in combination with the geographic distribution of the populations, suggest that Oc‐j was introduced or has emerged in North America on more than one occasion, and these clonal lineages have since proliferated across much of the range of butternut. No evidence of genetic recombination was observed in the linkage analysis, and conservation of the distinct genetic clusters in regions where isolates from two or more genetic clusters are present, would indicate a very minimal or non‐existent role of sexual recombination in populations of Oc‐j in North America.     

Determination of Cup to Disc Ratio Using Unsupervised Machine Learning Techniques for Glaucoma Detection

The cup nerve head, optic cup, optic disc ratio and neural rim configuration are observed as important for detecting glaucoma at an early stage in clinical practice. The main clinical indicator of glaucoma optic cup to disc ratio is currently determined manually by limiting the mass screening was potential. This paper proposes the following methods for an automatic cup to disc ratio determination. In the first part of the work, fundus image of the optic disc region is considered. Clustering means K is used automatically to extract the optic disc whereas K-value is automatically selected by algorithm called hill climbing. The segmented contour of optic cup has been smoothened by two methods namely elliptical fitting and morphological fitting. Cup to disc ratio is calculated for 50 normal images and 50 fundus images of glaucoma patients. Throughout this paper, the same set of images has been used and for these images, the cup to disc ratio values are provided by ophthalmologist which is taken as the gold standard value. The error is calculated with reference to this gold standard value throughout the paper for cup to disc ratio comparison. The mean error of the K-means clustering method for elliptical and morphological fitting is 4.5% and 4.1%, respectively. Since the error is high, fuzzy C-mean clustering has been chosen and the mean error of the method for elliptical and morphological fitting is 3.83% and 3.52%. The error can further be minimized by considering the inter pixel relation. To achieve another algorithm is by Spatially Weighted fuzzy C-means Clustering (SWFCM) is used. The optic disc and optic cup have clustered and segmented by SWFCM Clustering. The SWFCM mean error clustering method for elliptical and morphological fitting is 3.06% and 1.67%, respectively. In this work fundus images were collected from Aravind eye Hospital, Pondicherry.     

The complex biogeographic history of a widespread tropical tree species

Many tropical forest tree species have broad geographic ranges, and fossil records indicate that population disjunctions in some species were established millions of years ago. Here we relate biogeographic history to patterns of population differentiation, mutational and demographic processes in the widespread rainforest tree Symphonia globulifera using ribosomal (ITS) and chloroplast DNA sequences and nuclear microsatellite (nSSR) loci. Fossil records document sweepstakes dispersal origins of Neotropical S. globulifera populations from Africa during the Miocene. Despite historical long-distance gene flow, nSSR differentiation across 13 populations from Costa Rica, Panama, Ecuador (east and west of Andes) and French Guiana was pronounced (F(ST)= 0.14, R(ST)= 0.39, P < 0.001) and allele-size mutations contributed significantly (R(ST) > F(ST)) to the divergences between cis- and trans-Andean populations. Both DNA sequence and nSSR data reflect contrasting demographic histories in lower Mesoamerica and Amazonia. Amazon populations show weak phylogeographic structure and deviation from drift-mutation equilibrium indicating recent population expansion. In Mesoamerica, genetic drift was strong and contributed to marked differentiation among populations. The genetic structure of S. globulifera contains fingerprints of drift-dispersal processes and phylogeographic footprints of geological uplifts and sweepstakes dispersal.     

基于模糊c-均值聚类法的绿洲农田精确管理分区研究

以新疆绿洲棉区为研究对象,将176个土壤耕层属性数据作为变量进行精确管理分区研究.模糊c-均值聚类法被用来进行分区,采用c-φ多次组合法来确定适宜的模糊控制参数.研究区最佳分区数为4,模糊指数为1.5,平均混乱度指数为0.17,不同模糊类别交叠程度小,地理空间上土壤的隶属关系相对明确.为了评价分区结果的合理性,对各管理分区土壤数据进行常规性统计,并用LSR法进行各分区间差异显著性检验,结果表明:各管理分区土壤属性的变异系数都较分区前全研究区有所减小,分区间土壤属性差异显著.通过选取适宜的模糊控制参数,模糊c-均值聚类法可以较好地进行管理分区划分,分区结果可以作为变量施肥的单独作业单元进行耕作管理.     

In silico insights into the identification of potential novel angiogenic inhibitors against human VEGFR-2: a new SAR-based hierarchical clustering approach

Abstract

In this study, binding efficiency of new pyrrolopyrimidine structural analogs against human vascular endothelial growth factor receptor-2 (VEGFR-2) were elucidated using integrated in silico methods. Optimized high-resolution model of VEGFR-2 was generated and adopted for structure-based virtual screening approaches. Pyrrolopyrimidine inhibitor (CP15) associated compounds were screened from PubChem database and subjected to virtual screening and comparative docking methods against the receptor ligand-binding domain. Accordingly, high efficient compounds were clustered with similarity indices through PubChem structure cluster module using single-linkage algorithm. Moreover, pharmacokinetics including drug metabolism activities of high-binding leads under investigation was portrayed using ADMET and similarity ensemble analysis. Optimal energy orientations of the selected protein model have been shown to be reliable, and highly recommended for screening and docking studies. Docking and clustering strategies were shown that nineteen candidates as most effective binders for VEGFR-2 than CP15, and are grouped as three classes. Lys⁸⁶⁸, Glu⁸⁸⁵, Cys⁹¹⁹, His¹⁰²⁶, Arg¹⁰²⁷, Asp¹⁰⁴⁶, and Gly¹⁰⁴⁸ residues were predicted as novel hotspot residues, and participate in H-bonds, π-cation, π-stacking, halogen bonds, and salt-bridges formation with ligands. These additional bonds are contributing extent stability that holds the receptor structure at flexible state, this make difficult to any further conformational changes for evoking angiogenic signals. The ADMET and similarity ensemble analysis results were strongly indicated that thirteen candidates as best ligands for angiogenesis targets. Altogether, these findings indicate potential angiogenic templates and their binding levels with VEGFR-2; sorted viewpoints could be useful as a promising way to describe potential angiogenesis inhibitors with related molecular targets.