Identification and mapping of an AFLP marker linked to Gm7, a gall midge resistance gene and its conversion to a SCAR marker for its utility in marker aided selection in rice

We have identified an AFLP marker SA598 that is linked to Gm7, a gene conferring resistance to biotypes 1, 2 and 4 of the gall midge ( Orseolia oryzae), a major dipteran pest of rice. A set of PCR primers specific to an RFLP marker, previously identified to be linked to another gall midge resistance gene Gm2, also amplified a 1.5-kb (F8LB) fragment that is linked to Gm7. Gm7 is a dominant gene and non-allelic to Gm2. Hybridization experiments with clones from a YAC library of Nipponbare, a japonica variety, a BAC library of IR-BB21, an indica variety, and cosmid clones encompassing Gm2 from Phalguna, an indica variety, with F8LB and SA598 as probes, revealed that Gm7 is tightly linked to Gm2 and is located on chromosome 4 of rice. SA598 was sequenced and the sequence information was used to design sequence-characterized amplified region (SCAR) primers. The potential use of these SCAR primers in marker-aided selection of Gm7 in a rice breeding program has been demonstrated.     

Mutagenic inverted repeat assisted genome engineering (MIRAGE)

Here we describe a one-step method to create precise modifications in the genome of Saccharomyces cerevisiae as a tool for synthetic biology, metabolic engineering, systems biology and genetic studies. Through homologous recombination, a mutagenesis cassette containing an inverted repeat of selection marker(s) is integrated into the genome. Due to its inherent instability in genomic DNA, the inverted repeat catalyzes spontaneous self-excision, resulting in precise genome modification. Since this excision occurs at very high frequencies, selection for the integration event can be followed immediately by counterselection, without the need for growth in permissive conditions. This is the first time a truly one-step method has been described for genome modification in any organism.     

Binding modes of two novel dinucleotide inhibitors of HIV-1 integrase

Insights into the binding modes on HIV-1 integrase of our novel dinucleotide inhibitors (pisodApdC and pdCpisodU) have been obtained using molecular docking experiments. In contrast to their base-stacked unbound state, these dinucleotides in their integrase-bound state prefer unstacked conformations for a more extensive interaction with the active site. The calculated free energies of binding are in concert with the experimentally acquired anti-HIV-1 integrase data.     

Comparing DNA Extraction Methods for Analysis of Botanical Materials Found in Anti-Diabetic Supplements

A comparative performance evaluation of DNA extraction methods from anti-diabetic botanical supplements using various commercial kits was conducted, to determine which produces the best quality DNA suitable for PCR amplification, sequencing and species identification. All plant materials involved were of suboptimal quality showing various levels of degradation and therefore representing real conditions for testing herbal supplements. Eight different DNA extraction methods were used to isolate genomic DNA from 13 medicinal plant products. Two methods for evaluation, DNA concentration measurements that included absorbance ratios as well as PCR amplifiability, were used to determine quantity and quality of extracted DNA. We found that neither DNA concentrations nor commonly used UV absorbance ratio measurements at A ₂₆₀/A ₂₈₀ between 1.7 and 1.9 are suitable for globally predicting PCR success in these plant samples, and that PCR amplifiablity itself was the best indicator of extracted product quality. However, our results suggest that A ₂₆₀/A ₂₈₀ ratios below about 1.3 and above 2.3 indicated a DNA quality too poor to amplify. Therefore, A ₂₆₀/A ₂₈₀ measurements are not useful to identify samples that likely will amplify but can be used to exclude samples that likely will not amplify reducing the cost for unnecessarily subjecting samples to PCR. The two Nucleospin^® plant II kit extraction methods produced the most pure and amplifiable genomic DNA extracts. Our results suggest that there are clear, discernable differences between extraction methods for low quality plant samples in terms of producing contamination-free, high-quality genomic DNA to be used for further analysis.     

Potential Inhibitors of HIV Integrase

Abstract

In the search for inhibitors of HIV integrase, the enzyme involved in the integration of viral DNA into host DNA, we have synthesized and studied a number of analogs of the heterocyclic molecule, chloroquine.     

Frequency of Thyroid Dysfunctions during Interferon Alpha Treatment of Single and Combination Therapy in Hepatitis C Virus-Infected Patients: A Systematic Review Based Analysis

Background

Thyroid dysfunction is the commonest endocrinopathy associated with HCV infection due to interferon-based treatment. This comprehensive and systematic review presents the available evidence for newly developed thyroid antibodies and dysfunctions during interferon treatment (both single and combination) in HCV patients.

Methodology/Principal Findings

This systematic review was conducted in accordance with the PRISMA guidelines. The data generated were used to analyze the risk for thyroid dysfunctions during interferon (IFN) treatment in HCV patients. There was a wide range in the incidence of newly developed thyroid dysfunctions and thyroid antibodies in HCV patients during IFN treatment (both single and combination). The wide range of incidence also denoted the possibility of factors other than IFN treatment for thyroid-related abnormalities in HCV patients. These other factors include HCV viral factors, genetic predisposition, environmental factors, and patho-physiological factors. Variations in IFN dosage, treatment duration of IFN, definition/criteria followed in each study for thyroid dysfunction and irregular thyroid function testing during treatment in different studies influence the outcome of the single studies and jeopardise the validity of a pooled risk estimate of side effects of thyroid dysfunction. Importantly, reports differ as to whether the thyroid-related side effects disappear totally after withdrawal of the IFN treatment.

Conclusions/Significance

The present review shows that there is a wide range in the incidence of newly developed thyroid dysfunctions and thyroid antibodies in IFN treated HCV patients. This is a comprehensive attempt to collate relevant data from 56 publications across several nations about IFN (both mono and combination therapy) related thyroid dysfunction among HCV patients. The role of each factor in causing thyroid dysfunctions in HCV patients treated with IFN should be analyzed in detail in future studies, for a better understanding of the problem and sounder clinical management of the disease.     

Real-Time Analysis and Visualization for Single-Molecule Based Super-Resolution Microscopy

Accurate multidimensional localization of isolated fluorescent emitters is a time consuming process in single-molecule based super-resolution microscopy. We demonstrate a functional method for real-time reconstruction with automatic feedback control, without compromising the localization accuracy. Compatible with high frame rates of EM-CCD cameras, it relies on a wavelet segmentation algorithm, together with a mix of CPU/GPU implementation. A combination with Gaussian fitting allows direct access to 3D localization. Automatic feedback control ensures optimal molecule density throughout the acquisition process. With this method, we significantly improve the efficiency and feasibility of localization-based super-resolution microscopy.     

Identification of Penicillin-binding proteins employing support vector machines and random forest

Penicillin-Binding Proteins are peptidases that play an important role in cell-wall biogenesis in bacteria and thus maintaining bacterial infections. A wide class of β-lactam drugs are known to act on these proteins and inhibit bacterial infections by disrupting the cell-wall biogenesis pathway. Penicillin-Binding proteins have recently gained importance with the increase in the number of multi-drug resistant bacteria. In this work, we have collected a dataset of over 700 Penicillin-Binding and non-Penicillin Binding Proteins and extracted various sequence-related features. We then created models to classify the proteins into Penicillin-Binding and non-binding using supervised machine learning algorithms such as Support Vector Machines and Random Forest. We obtain a good classification performance for both the models using both the methods.