In vivo gene expression: DNA electrotransfer

The use of electric pulses to deliver therapeutic molecules to tissues and organs in vivo is a rapidly growing field of research. Electrotransfer can be used to deliver a wide range of potentially therapeutic agents, including drugs, proteins, oligonucleotides, RNA and DNA. Optimization of this approach depends upon a number of parameters such as target organ accessibility, cell turnover, microelectrode design, electric pulsing protocols and the physiological response to the therapeutic agent. Many organs have been successfully transfected by electroporation, including skin, liver, skeletal and cardiac muscle, male and female germ cells, artery, gut, kidney, retinal ganglion cells, cornea, spinal cord, joint synovium and brain. Electrotransfer technology is relevant in a variety of research and clinical settings including cancer therapy, modulation of pathogenic immune reactions, delivery of therapeutic proteins and drugs, and the identification of drug targets by the modulation of normal gene expression. This, together with the capacity to deliver very large DNA constructs, greatly expands the research and clinical applications of in vivo DNA electrotransfer.

A genetic linkage map in autotetraploid lucerne adapted to northern Australia, and use of the map to identify DNA markers linked to resistance to Phytophthora medicaginis

Phytophthora root rot, caused by Phytophthora medicaginis, is a major limitation to lucerne ( Medicago sativa L.) production in Australia and North America. Quantitative trait loci (QTLs) involved in resistance to P. medicaginis were identified in a lucerne backcross population of 120 individuals. A genetic linkage map was constructed for tetraploid lucerne using 50 RAPD ( randomly amplified polymorphic DNA), 104 AFLP (amplified fragment length polymorphism) markers, and one SSR ( simple sequence repeat or microsatellite) marker, which originated from the resistant parent (W116); 13 markers remain unlinked. The linkage map contains 18 linkage groups covering 2136.5 cM, with an average distance of 15.0 cM between markers. Four of the linkage groups contained only either 2 or 3 markers. Using duplex markers and repulsion phase linkages the map condensed to 7 homology groups and 2 unassigned linkage groups. Three regions located on linkage groups 2, 14, and 18, were identified as associated with root reaction and the QTLs explained 6 - 15% of the phenotypic variation. The research also indicates that different resistance QTLs are involved in conferring resistance in different organs. Two QTLs were identified as associated with disease resistance expressed after inoculation of detached leaves. The marker, W11-2 on group 18, identified as associated with root reaction, contributed 7% of the phenotypic variation in leaf response in our population. This marker appears to be linked to a QTL encoding a resistance factor contributing to both root and leaf reaction. One other QTL, not identified as associated with root reaction, was positioned on group 1 and contributed to 6% of the variation. This genetic linkage map provides an entry point for future molecular-based improvement of lucerne in Australia, and markers linked to the QTLs we have reported should be useful for marker-assisted selection for partial resistance to P. medicaginis in lucerne.

SeqDoC: rapid SNP and mutation detection by direct comparison of DNA sequence chromatograms

Background: This paper describes SeqDoC, a simple, web-based tool to carry out direct comparison of ABI sequence chromatograms. This allows the rapid identification of single nucleotide polymorphisms (SNPs) and point mutations without the need to install or learn more complicated analysis software. Results: SeqDoC produces a subtracted trace showing differences between a reference and test chromatogram, and is optimised to emphasise those characteristic of single base changes. It automatically aligns sequences, and produces straightforward graphical output. The use of direct comparison of the sequence chromatograms means that artefacts introduced by automatic base-calling software are avoided. Homozygous and heterozygous substitutions and insertion/deletion events are all readily identified. SeqDoC successfully highlights nucleotide changes missed by the Staden package 'tracediff' program. Conclusion: SeqDoC is ideal for small-scale SNP identification, for identification of changes in random mutagenesis screens, and for verification of PCR amplification fidelity. Differences are highlighted, not interpreted, allowing the investigator to make the ultimate decision on the nature of the change.

GANN: Genetic algorithm neural networks for the detection of conserved combinations of features in DNA

Background: The multitude of motif detection algorithms developed to date have largely focused on the detection of patterns in primary sequence. Since sequence-dependent DNA structure and flexibility may also play a role in protein-DNA interactions, the simultaneous exploration of sequence-and structure-based hypotheses about the composition of binding sites and the ordering of features in a regulatory region should be considered as well. The consideration of structural features requires the development of new detection tools that can deal with data types other than primary sequence. Results: GANN ( available at http://bioinformatics.org.au/gann) is a machine learning tool for the detection of conserved features in DNA. The software suite contains programs to extract different regions of genomic DNA from flat files and convert these sequences to indices that reflect sequence and structural composition or the presence of specific protein binding sites. The machine learning component allows the classification of different types of sequences based on subsamples of these indices, and can identify the best combinations of indices and machine learning architecture for sequence discrimination. Another key feature of GANN is the replicated splitting of data into training and test sets, and the implementation of negative controls. In validation experiments, GANN successfully merged important sequence and structural features to yield good predictive models for synthetic and real regulatory regions. Conclusion: GANN is a flexible tool that can search through large sets of sequence and structural feature combinations to identify those that best characterize a set of sequences.

Quantitative analysis of DNA-protein interactions using double-labeled native gel electrophoresis and fluorescence-based imaging

We have developed a sensitive, non-radioactive method to assess the interaction of transcription factors/DNA-binding proteins with DNA. We have modified the traditional radiolabeled DNA gel mobility shift assay to incorporate a DNA probe end-labeled with a Texas-red fluorophore and a DNA-binding protein tagged with the green fluorescent protein to monitor precisely DNA-protein complexation by native gel electrophoresis. We have applied this method to the DNA-binding proteins telomere release factor-1 and the sex-determining region-Y, demonstrating that the method is sensitive (able to detect 100 fmol of fluorescently labeled DNA), permits direct visualization of both the DNA probe and the DNA-binding protein, and enables quantitative analysis of DNA and protein complexation, and thereby an estimation of the stoichiometry of protein-DNA binding.

Engineering of needle-free physical methods to target epidermal cells for DNA vaccination

A challenge in epidermal DNA vaccination is the efficient and targeted delivery of polynucleotides to immunologically sensitive Langerhans cells. This paper investigates this particular challenge for physical delivery approaches. The skin immunology and material properties are examined in the context of the physical cell targeting requirements of the viable epidermis. Selected current physical cell targeting technologies engineered to meet these needs are examined: needle and syringe; diffusion patches; liquid jet injectors; microneedle arrays/patches; and biolistic particle injection. The operating methods and relative performance of these approaches are discussed, with a comment on potential future developments and technologies. (c) 2005 Elsevier Ltd. All rights reserved.

Plasma Epstein-Barr virus (EBV) DNA is a biomarker for EBV-positive Hodgkin's lymphoma

Purpose: Latent Epstein-Barr virus (EBV) genomes are found in the malignant cells of approximately one-third of Hodgkin's lymphoma (HL) cases. Detection and quantitation of EBV viral DNA could potentially be used as a biomarker of disease activity. Experimental Design: Initially, EBV-DNA viral load was prospectively monitored from peripheral blood mononuclear cells (PBMC) in patients with HL. Subsequently, we analyzed viral load in plasma from a second cohort of patients. A total of 58 patients with HL (31 newly diagnosed, 6 relapsed, and 21 in long-term remission) were tested. Using real-time PCR, 43 PBMC and 52 plasma samples were analyzed. Results: EBV-DNA was detectable in the plasma of all EBV-positive patients with HL prior to therapy. However, viral DNA was undetectable following therapy in responding patients (P = 0.0156), EBV-positive HL patients in long-term remission (P = 0.0011), and in all patients with EBV-negative HL (P = 0.0238). Conversely, there was no association seen for the EBV-DNA load measured from PBMC in patients with active EBV-positive HL patients as compared with EBV-negative HL, or patients in long-term remission. EBV-DNA load in matched plasma/PBMC samples were not correlated. Conclusions: We show that free plasma EBV-DNA has excellent sensitivity and specificity, and can be used as a noninvasive biomarker for EBV-positive HL and that serial monitoring could predict response to therapy. Additional prospective studies are required to further evaluate the use of free plasma EBV-DNA as a biomarker for monitoring response to treatment in patients with EBV-positive HL.