IQGAP1: a regulator of intracellular spacetime relativity

Activating and inhibiting receptors of lymphocytes collect valuable information about their mikròs kósmos. This information is essential to initiate or to turn off complex signaling pathways. Irrespective of these advances, our knowledge on how these intracellular activation cascades are coordinated in a spatiotemporal manner is far from complete. Among multiple explanations, the scaffolding proteins have emerged as a critical piece of this evolutionary tangram. Among many, IQGAP1 is one of the essential scaffolding proteins that coordinate multiple signaling pathways. IQGAP1 possesses multiple protein interaction motifs to achieve its scaffolding functions. Using these domains, IQGAP1 has been shown to regulate a number of essential cellular events. This includes actin polymerization, tubulin multimerization, microtubule organizing center formation, calcium/calmodulin signaling, Pak/Raf/Mek1/2-mediated Erk1/2 activation, formation of maestrosome, E-cadherin, and CD44-mediated signaling and glycogen synthase kinase-3/adenomatous polyposis coli-mediated β-catenin activation. In this review, we summarize the recent developments and exciting new findings of cellular functions of IQGAP1.     

Characterization of phytohormonal and postharvest senescence responses of balsam fir (Abies balsamea (L.) Mill.) exposed to short-term low temperature

To fulfill the US Thanksgiving and Christmas tree markets, balsam fir (Abies balsamea (L.) Mill.) is generally harvested before the cold season, anecdotally leading to premature needle senescence. Accordingly, we tested the hypothesis that LT exposure before harvest induces specific hormonal changes and delays postharvest senescence and/or abscission in balsam fir. Two hundred and six seedlings exposed to two temperature treatments for 48?h, LT at 5?°C and controls at 22?°C were severed off roots and monitored for their postharvest needle senescence. Root and shoot (needles and buds) tissues were examined for major endogenous hormone metabolites. LT increased shoot ABA (2,007?ng?g^?1 DW) by 2.5× and decreased GA₄₄ (9.84?ng?g^?1 DW) by 3.5× over those in roots. LT did not alter cytokinins, auxins or any root hormonal concentration. With auxins, only IAA, IAA-Asp, IAA-Leu and IAA-Glu were detected and the concentrations of IAA and IAA-Asp in shoots were lower than those found in roots. Among cytokinins, shoot c-ZR (58.95?ng?g^?1 DW) and t-ZR (4.17?ng?g^?1 DW) were 3× higher than those in roots. Apart from GA₄₄, GA₉ (136.76?ng?g^?1 DW) was abundant in shoots. The PBL and PNL were 46 and 1.2?%, irrespective of treatments. LT seedlings held needles 11?days longer than the controls (122?days). In balsam fir, short-term LT exposure augmented ABA and decreased GA₄₄ levels in shoots and delayed postharvest needle senescence.     

Reducing false-positive prediction of minimotifs with a genetic interaction filter

Background

Minimotifs are short contiguous peptide sequences in proteins that have known functions. At its simplest level, the minimotif sequence is present in a source protein and has an activity relationship with a target, most of which are proteins. While many scientists routinely investigate new minimotif functions in proteins, the major web-based discovery tools have a high rate of false-positive prediction. Any new approach that reduces false-positives will be of great help to biologists.

Methods and Findings

We have built three filters that use genetic interactions to reduce false-positive minimotif predictions. The basic filter identifies those minimotifs where the source/target protein pairs have a known genetic interaction. The HomoloGene genetic interaction filter extends these predictions to predicted genetic interactions of orthologous proteins and the node-based filter identifies those minimotifs where proteins that have a genetic interaction with the source or target have a genetic interaction. Each filter was evaluated with a test data set containing thousands of true and false-positives. Based on sensitivity and selectivity performance metrics, the basic filter had the best discrimination for true positives, whereas the node-based filter had the highest sensitivity. We have implemented these genetic interaction filters on the Minimotif Miner 2.3 website. The genetic interaction filter is particularly useful for improving predictions of posttranslational modifications such as phosphorylation and proteolytic cleavage sites.

Conclusions

Genetic interaction data sets can be used to reduce false-positive minimotif predictions. Minimotif prediction in known genetic interactions can help to refine the mechanisms behind the functional connection between genes revealed by genetic experimentation and screens.     

Diversity array technology markers: genetic diversity analyses and linkage map construction in rapeseed (Brassica napus L.)

We developed Diversity Array Technology (DArT) markers for application in genetic studies of Brassica napus and other Brassica species with A or C genomes. Genomic representation from 107 diverse genotypes of B. napus L. var. oleifera (rapeseed, AACC genomes) and B. rapa (AA genome) was used to develop a DArT array comprising 11 520 clones generated using PstI/BanII and PstI/BstN1 complexity reduction methods. In total, 1547 polymorphic DArT markers of high technical quality were identified and used to assess molecular diversity among 89 accessions of B. napus, B. rapa, B. juncea, and B. carinata collected from different parts of the world. Hierarchical cluster and principal component analyses based on genetic distance matrices identified distinct populations clustering mainly according to their origin/pedigrees. DArT markers were also mapped in a new doubled haploid population comprising 131 lines from a cross between spring rapeseed lines 'Lynx-037DH' and 'Monty-028DH'. Linkage groups were assigned on the basis of previously mapped simple sequence repeat (SSRs), intron polymorphism (IP), and gene-based markers. The map consisted of 437 DArT, 135 SSR, 6 IP, and 6 gene-based markers and spanned 2288 cM. Our results demonstrate that DArT markers are suitable for genetic diversity analysis and linkage map construction in rapeseed.     

Na,K-ATPase is a target of cigarette smoke and reduced expression predicts poor patient outcome of smokers with lung cancer

Diminished Na,K-ATPase expression has been reported in several carcinomas and has been linked to tumor progression. However, few studies have determined whether Na,K-ATPase function and expression are altered in lung malignancies. Because cigarette smoke (CS) is a major factor underlying lung carcinogenesis and progression, we investigated whether CS affects Na,K-ATPase activity and expression in lung cell lines. Cells exposed to CS in vitro showed a reduction of Na,K-ATPase activity. We detected the presence of reactive oxygen species (ROS) in cells exposed to CS before Na,K-ATPase inhibition, and neutralization of ROS restored Na,K-ATPase activity. We further determined whether Na,K-ATPase expression correlated with increasing grades of lung adenocarcinoma and survival of patients with smoking history. Immunohistochemical analysis of lung adenocarcinoma tissues revealed reduced Na,K-ATPase expression with increasing tumor grade. Using tissue microarray containing lung adenocarcinomas of patients with known smoking status, we found that high expression of Na,K-ATPase correlated with better survival. For the first time, these data demonstrate that CS is associated with loss of Na,K-ATPase function and expression in lung carcinogenesis, which might contribute to disease progression.     

Achieving High Accuracy Prediction of Minimotifs

The low complexity of minimotif patterns results in a high false-positive prediction rate, hampering protein function prediction. A multi-filter algorithm, trained and tested on a linear regression model, support vector machine model, and neural network model, using a large dataset of verified minimotifs, vastly improves minimotif prediction accuracy while generating few false positives. An optimal threshold for the best accuracy reaches an overall accuracy above 90%, while a stringent threshold for the best specificity generates less than 1% false positives or even no false positives and still produces more than 90% true positives for the linear regression and neural network models. The minimotif multi-filter with its excellent accuracy represents the state-of-the-art in minimotif prediction and is expected to be very useful to biologists investigating protein function and how missense mutations cause disease.     

A novel computational and structural analysis of nsSNPs in CFTR gene

Single Nucleotide Polymorphisms (SNPs) are being intensively studied to understand the biological basis of complex traits and diseases. The Genetics of human phenotype variation could be understood by knowing the functions of SNPs. In this study using computational methods, we analyzed the genetic variations that can alter the expression and function of the CFTR gene responsible candidate for causing cystic fibrosis. We applied an evolutionary perspective to screen the SNPs using a sequence homology-based SIFT tool, which suggested that 17 nsSNPs (44%) were found to be deleterious. The structure-based approach PolyPhen server suggested that 26 nsSNPS (66%) may disrupt protein function and structure. The PupaSuite tool predicted the phenotypic effect of SNPs on the structure and function of the affected protein. Structure analysis was carried out with the major mutation that occurred in the native protein coded by CFTR gene, and which is at amino acid position F508C for nsSNP with id (rs1800093). The amino acid residues in the native and mutant modeled protein were further analyzed for solvent accessibility, secondary structure and stabilizing residues to check the stability of the proteins. The SNPs were further subjected to iHAP analysis to identify htSNPs, and we report potential candidates for future studies on CFTR mutations.