A novel multiplex PCR assay for the identification of Indian crocodiles

Illegal hunting has been a major threat for the survival of wildlife fauna, including the three crocodile species that India harbours: Crocodylus palustris, Crocodylus porosus and Gavialis gangeticus. Although law prevents trade on these species, illicit hunting for trade continues to threaten the survival of these endangered species; conservation strategies therefore require a rapid molecular identification technique for Indian crocodiles. A multiplex polymerase chain reaction (PCR) assay with species-specific primers, considered as one of the most effective molecular techniques, is described herein. The primers were designed to yield species-specific sized amplicons. The assay discriminates the three Indian crocodile species unambiguously within a short time period using only simple agarose gel electrophoresis. We recommend this multiplex PCR assay to be used in the identification of Indian crocodile species.     

Phenotypic and functional effects of heat shock protein 90 inhibition on dendritic cell

The 90-kDa heat shock protein (Hsp90) plays an important role in conformational regulation of cellular proteins and thereby cellular signaling and function. As Hsp90 is considered a key component of immune function and its inhibition has become an important target for cancer therapy, we here evaluated the role of Hsp90 in human dendritic cell (DC) phenotype and function. Hsp90 inhibition significantly decreased cell surface expression of costimulatory (CD40, CD80, CD86), maturation (CD83), and MHC (HLA-A, B, C and HLA-DP, DQ, DR) markers in immature DC and mature DC and was associated with down-regulation of both RNA and intracellular protein expression. Importantly, Hsp90 inhibition significantly inhibited DC function. It decreased Ag uptake, processing, and presentation by immature DC, leading to reduced T cell proliferation in response to tetanus toxoid as a recall Ag. It also decreased the ability of mature DC to present Ag to T cells and secrete IL-12 as well as induce IFN-gamma secretion by allogeneic T cells. These data therefore demonstrate that Hsp90-mediated protein folding is required for DC function and, conversely, Hsp90 inhibition disrupts the DC function of significant relevance in the setting of clinical trials evaluating novel Hsp90 inhibitor therapy in cancer.     

The role of actin cytoskeleton in oscillatory fluid flow-induced signaling in MC3T3-E1 osteoblasts

Fluid flow due to loading in bone is a potent mechanical signal that may play an important role in bone adaptation to its mechanical environment. Previous in vitro studies of osteoblastic cells revealed that the upregulation of cyclooxygenase-2 (COX-2) and c-fos induced by steady fluid flow depends on a change in actin polymerization dynamics and the formation of actin stress fibers. Exposing cells to dynamic oscillatory fluid flow, the temporal flow pattern that results from normal physical activity, is also known to result in increased COX-2 expression and PGE₂ release. The purpose of this study was to determine whether dynamic fluid flow results in changes in actin dynamics similar to steady flow and to determine whether alterations in actin dynamics are required for PGE₂ release. We found that exposure to oscillatory fluid flow did not result in the development of F-actin stress fibers in MC3T3-E1 osteoblastic cells and that inhibition of actin polymerization with cytochalasin D did not inhibit intracellular calcium mobilization or PGE₂ release. In fact, PGE₂ release was increased threefold in the polymerization inhibited cells and this PGE₂ release was dependent on calcium release from the endoplasmic reticulum. This was in contrast to the PGE₂ release that occurs in normal cells, which is independent of calcium flux from endoplasmic reticulum stores. We suggest that this increased PGE₂ release involves a different molecular mechanism perhaps involving increased deformation due to the compromised cytoskeleton. mechanotransduction; cell mechanics     

Synthesis of some thiazolyl aminobenzothiazole derivatives as potential antibacterial, antifungal and anthelmintic agents

A series of 4-(6-substituted-1,3-benzothiazol-2-yl)amino-2-(4-substitutedphenyl)- amino-1,3-thiazoles, 9-24 have been synthesised from 2-chloro-N-(6-substituted-1,3-benzothiazol-2-yl)acetamides, 5-8. The structures of these compounds have been elucidated by spectral (IR, (1)H NMR, Mass) and elemental (C, H, N) analysis data. All the newly synthesised compounds (9-24) were screened for their antibacterial, antifungal and anthelmintic activities. Almost all of these compounds showed moderate to good antimicrobial activity against two gram negative bacteria (E. coli, P. aeruginosa), two gram positive bacteria (S. aureus, B. subtilis), pathogenic fungal strains (C. albicans, A. niger) and good anthelmintic activity against earthworm species (P. corethruses). Compounds 18 and 20 exhibited good antibacterial and antifungal activities, while compound 22 displayed the most significant anthelmintic activity.     

An essential role for diet in exercise-mediated protection against dyslipidemia, inflammation and atherosclerosis in ApoE⁻/⁻ mice

Background

Diet and exercise promote cardiovascular health but their relative contributions to atherosclerosis are not fully known. The transition from a sedentary to active lifestyle requires increased caloric intake to achieve energy balance. Using atherosclerosis-prone ApoE-null mice we sought to determine whether the benefits of exercise for arterial disease are dependent on the food source of the additional calories.

Methods and Results

Mice were fed a high-fat diet (HF) for 4.5 months to initiate atherosclerosis after which time half were continued on HF while the other half were switched to a high protein/fish oil diet (HP). Half of each group underwent voluntary running. Food intake, running distance, body weight, lipids, inflammation markers, and atherosclerotic plaque were quantified. Two-way ANOVA tests were used to assess differences and interactions between groups. Exercised mice ran approximately 6-km per day with no difference between groups. Both groups increased food intake during exercise and there was a significant main effect of exercise F((1,44) = 9.86, p<0.01) without interaction. Diet or exercise produced significant independent effects on body weight (diet: F(1,52) = 6.85, p = 0.012; exercise: F(1,52) = 9.52, p<0.01) with no significant interaction. The combination of HP diet and exercise produced a greater decrease in total cholesterol (F(1, 46) = 7.9, p<0.01) and LDL (F(1, 46) = 7.33, p<0.01) with a large effect on the size of the interaction. HP diet and exercise independently reduced TGL and VLDL (p<0.05 and 0.001 respectively). Interleukin 6 and C-reactive protein were highest in the HF-sedentary group and were significantly reduced by exercise only in this group. Plaque accumulation in the aortic arch, a marker of cardiovascular events was reduced by the HP diet and the effect was significantly potentiated by exercise only in this group resulting in significant plaque regression (F1, 49 = 4.77, p<0.05).

Conclusion

In this model exercise is beneficial to combat dyslipidemia and protect from atherosclerosis only when combined with diet.     

Discovery of protein phosphorylation motifs through exploratory data analysis

Background

The need for efficient algorithms to uncover biologically relevant phosphorylation motifs has become very important with rapid expansion of the proteomic sequence database along with a plethora of new information on phosphorylation sites. Here we present a novel unsupervised method, called Motif Finder (in short, F-Motif) for identification of phosphorylation motifs. F-Motif uses clustering of sequence information represented by numerical features that exploit the statistical information hidden in some foreground data. Furthermore, these identified motifs are then filtered to find “actual” motifs with statistically significant motif scores.

Results and Discussion

We have applied F-Motif to several new and existing data sets and compared its performance with two well known state-of-the-art methods. In almost all cases F-Motif could identify all statistically significant motifs extracted by the state-of-the-art methods. More importantly, in addition to this, F-Motif uncovers several novel motifs. We have demonstrated using clues from the literature that most of these new motifs discovered by F-Motif are indeed novel. We have also found some interesting phenomena. For example, for CK2 kinase, the conserved sites appear only on the right side of S. However, for CDK kinase, the adjacent site on the right of S is conserved with residue P. In addition, three different encoding methods, including a novel position contrast matrix (PCM) and the simplest binary coding, are used and the ability of F-motif to discover motifs remains quite robust with respect to encoding schemes.

Conclusions

An iterative algorithm proposed here uses exploratory data analysis to discover motifs from phosphorylated data. The effectiveness of F-Motif has been demonstrated using several real data sets as well as using a synthetic data set. The method is quite general in nature and can be used to find other types of motifs also. We have also provided a server for F-Motif at http://f-motif.classcloud.org/, http://bio.classcloud.org/f-motif/ or http://ymu.classcloud.org/f-motif/.     

Identification of single- and multiple-class specific signature genes from gene expression profiles by group marker index

Informative genes from microarray data can be used to construct prediction model and investigate biological mechanisms. Differentially expressed genes, the main targets of most gene selection methods, can be classified as single- and multiple-class specific signature genes. Here, we present a novel gene selection algorithm based on a Group Marker Index (GMI), which is intuitive, of low-computational complexity, and efficient in identification of both types of genes. Most gene selection methods identify only single-class specific signature genes and cannot identify multiple-class specific signature genes easily. Our algorithm can detect de novo certain conditions of multiple-class specificity of a gene and makes use of a novel non-parametric indicator to assess the discrimination ability between classes. Our method is effective even when the sample size is small as well as when the class sizes are significantly different. To compare the effectiveness and robustness we formulate an intuitive template-based method and use four well-known datasets. We demonstrate that our algorithm outperforms the template-based method in difficult cases with unbalanced distribution. Moreover, the multiple-class specific genes are good biomarkers and play important roles in biological pathways. Our literature survey supports that the proposed method identifies unique multiple-class specific marker genes (not reported earlier to be related to cancer) in the Central Nervous System data. It also discovers unique biomarkers indicating the intrinsic difference between subtypes of lung cancer. We also associate the pathway information with the multiple-class specific signature genes and cross-reference to published studies. We find that the identified genes participate in the pathways directly involved in cancer development in leukemia data. Our method gives a promising way to find genes that can involve in pathways of multiple diseases and hence opens up the possibility of using an existing drug on other diseases as well as designing a single drug for multiple diseases.