A novel human leucocyte antigen-DRB1 genotyping method based on multiplex primer extension reactions

We have developed and validated a semi-automated fluorescent method of genotyping human leucocyte antigen (HLA)-DRB1 alleles, HLA-DRB1*01-16, by multiplex primer extension reactions. This method is based on the extension of a primer that anneals immediately adjacent to the single-nucleotide polymorphism with fluorescent dideoxynucleotide triphosphates (minisequencing), followed by analysis on an ABI Prism 3700 capillary electrophoresis instrument. The validity of the method was confirmed by genotyping 261 individuals using both this method and polymerase chain reaction with sequence-specific primer (PCR-SSP) or sequencing and by demonstrating Mendelian inheritance of HLA-DRB1 alleles in families. Our method provides a rapid means of performing high-throughput HLA-DRB1 genotyping using only two PCR reactions followed by four multiplex primer extension reactions and PCR-SSP for some allele groups. In this article, we describe the method and discuss its advantages and limitations.

Study of miRNA polymorphisms and their potential association with breast cancer risk in Australian Caucasian populations

This project established a large and well characterised prospective breast cancer DNA biobank and used this biobank to conduct genetic studies in breast cancer. The thesis presented the results of these high-throughput genotyping studies in two separate Australian Caucasian case-control populations and identified association between three novel genetic variants in microRNA genes and breast cancer risk.

PocketMatch: A new algorithm to compare binding sites in protein structures

Recognizing similarities and deriving relationships among protein molecules is a fundamental requirement in present-day biology. Similarities can be present at various levels which can be detected through comparison of protein sequences or their structural folds. In some cases similarities obscure at these levels could be present merely in the substructures at their binding sites. Inferring functional similarities between protein molecules by comparing their binding sites is still largely exploratory and not as yet a routine protocol. One of the main reasons for this is the limitation in the choice of appropriate analytical tools that can compare binding sites with high sensitivity. To benefit from the enormous amount of structural data that is being rapidly accumulated, it is essential to have high throughput tools that enable large scale binding site comparison. Results: Here we present a new algorithm PocketMatch for comparison of binding sites in a frame invariant manner. Each binding site is represented by 90 lists of sorted distances capturing shape and chemical nature of the site. The sorted arrays are then aligned using an incremental alignment method and scored to obtain PMScores for pairs of sites. A comprehensive sensitivity analysis and an extensive validation of the algorithm have been carried out. A comparison with other site matching algorithms is also presented. Perturbation studies where the geometry of a given site was retained but the residue types were changed randomly, indicated that chance similarities were virtually non-existent. Our analysis also demonstrates that shape information alone is insufficient to discriminate between diverse binding sites, unless combined with chemical nature of amino acids. Conclusion: A new algorithm has been developed to compare binding sites in accurate, efficient and high-throughput manner. Though the representation used is conceptually simplistic, we demonstrate that along with the new alignment strategy used, it is sufficient to enable binding comparison with high sensitivity. Novel methodology has also been presented for validating the algorithm for accuracy and sensitivity with respect to geometry and chemical nature of the site. The method is also fast and takes about 1/250(th) second for one comparison on a single processor. A parallel version on BlueGene has also been implemented.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

Comparative analysis of the uropathogenic Escherichia coli surface proteome by tandem mass-spectrometry of artificially induced outer membrane vesicles

Uropathogenic Escherichia coli (UPEC) are the major cause of urinary tract infections. For successful colonisation of the urinary tract, UPEC employ multiple surface-exposed or secreted virulence factors, including adhesins and iron uptake systems. Whilst individual UPEC strains and their virulence factors have been the focus of extensive research, there have been no outer membrane (OM) proteomic studies based on large clinical UPEC collections, primarily due to limitations of traditional methods. In this study, a high-throughput method based on tandem mass-spectrometry of EDTA heat-induced outer membrane vesicles (OMVs) was developed for the characterisation of the UPEC surface-associated proteome. The method was applied to compare the OM proteome of fifty-four UPEC isolates, resulting in the identification of 8789 proteins, consisting of 619 unique proteins, which were subsequently interrogated for their subcellular origin, prevalence and homology to characterised virulence factors. Multiple distinct virulence-associated proteins were identified, including two novel putative iron uptake proteins, an uncharacterised type of chaperone-usher fimbriae and various highly prevalent hypothetical proteins. Our results give fundamental insight into the physiology of UPEC and provide a framework for understanding the composition of the UPEC OM proteome.

SU-8-Based Microchips for Capillary Electrophoresis and Electrospray Ionization Mass Spectrometry

Miniaturization of analytical instrumentation is attracting growing interest in response to the explosive demand for rapid, yet sensitive analytical methods and low-cost, highly automated instruments for pharmaceutical and bioanalyses and environmental monitoring. Microfabrication technology in particular, has enabled fabrication of low-cost microdevices with a high degree of integrated functions, such as sample preparation, chemical reaction, separation, and detection, on a single microchip. These miniaturized total chemical analysis systems (microTAS or lab-on-a-chip) can also be arrayed for parallel analyses in order to accelerate the sample throughput. Other motivations include reduced sample consumption and waste production as well as increased speed of analysis. One of the most promising hyphenated techniques in analytical chemistry is the combination of a microfluidic separation chip and mass spectrometer (MS). In this work, the emerging polymer microfabrication techniques, ultraviolet lithography in particular, were exploited to develop a capillary electrophoresis (CE) separation chip which incorporates a monolithically integrated electrospray ionization (ESI) emitter for efficient coupling with MS. An epoxy photoresist SU-8 was adopted as structural material and characterized with respect to its physicochemical properties relevant to chip-based CE and ESI/MS, namely surface charge, surface interactions, heat transfer, and solvent compatibility. As a result, SU-8 was found to be a favorable material to substitute for the more commonly used glass and silicon in microfluidic applications. In addition, an infrared (IR) thermography was introduced as direct, non-intrusive method to examine the heat transfer and thermal gradients during microchip-CE. The IR data was validated through numerical modeling. The analytical performance of SU-8-based microchips was established for qualitative and quantitative CE-ESI/MS analysis of small drug compounds, peptides, and proteins. The CE separation efficiency was found to be similar to that of commercial glass microchips and conventional CE systems. Typical analysis times were only 30-90 s per sample indicating feasibility for high-throughput analysis. Moreover, a mass detection limit at the low-attomole level, as low as 10E+5 molecules, was achieved utilizing MS detection. The SU-8 microchips developed in this work could also be mass produced at low cost and with nearly identical performance from chip to chip. Until this work, the attempts to combine CE separation with ESI in a chip-based system, amenable to batch fabrication and capable of high, reproducible analytical performance, have not been successful. Thus, the CE-ESI chip developed in this work is a substantial step toward lab-on-a-chip technology.

Transcriptome analysis of Neotyphodium and Epichloë grass endophytes

Large-scale gene discovery has been performed for the grass fungal endophytes Neotyphodium coenophialum, Neotyphodium lolii, and Epichloë festucae. The resulting sequences have been annotated by comparison with public DNA and protein sequence databases and using intermediate gene ontology annotation tools. Endophyte sequences have also been analysed for the presence of simple sequence repeat and single nucleotide polymorphism molecular genetic markers. Sequences and annotation are maintained within a MySQL database that may be queried using a custom web interface. Two cDNA-based microarrays have been generated from this genome resource. They permit the interrogation of 3806 Neotyphodium genes (NchipTM microarray), and 4195 Neotyphodium and 920 Epichloë genes (EndoChipTM microarray), respectively. These microarrays provide tools for high-throughput transcriptome analysis, including genome-specific gene expression studies, profiling of novel endophyte genes, and investigation of the host grass–symbiont interaction. Comparative transcriptome analysis in Neotyphodium and Epichloë was performed

Domestication to crop improvement: Genetic resources for Sorghum and Saccharum (Andropogoneae).

Background: Both sorghum (Sorghum bicolor) and sugarcane (Saccharum officinarum) are members of the Andropogoneae tribe in the Poaceae and are each other's closest relatives amongst cultivated plants. Both are relatively recent domesticates and comparatively little of the genetic potential of these taxa and their wild relatives has been captured by breeding programmes to date. This review assesses the genetic gains made by plant breeders since domestication and the progress in the characterization of genetic resources and their utilization in crop improvement for these two related species. Genetic Resources: The genome of sorghum has recently been sequenced providing a great boost to our knowledge of the evolution of grass genomes and the wealth of diversity within S. bicolor taxa. Molecular analysis of the Sorghum genus has identified close relatives of S. bicolor with novel traits, endosperm structure and composition that may be used to expand the cultivated gene pool. Mutant populations (including TILLING populations) provide a useful addition to genetic resources for this species. Sugarcane is a complex polyploid with a large and variable number of copies of each gene. The wild relatives of sugarcane represent a reservoir of genetic diversity for use in sugarcane improvement. Techniques for quantitative molecular analysis of gene or allele copy number in this genetically complex crop have been developed. SNP discovery and mapping in sugarcane has been advanced by the development of high-throughput techniques for ecoTILLING in sugarcane. Genetic linkage maps of the sugarcane genome are being improved for use in breeding selection. The improvement of both sorghum and sugarcane will be accelerated by the incorporation of more diverse germplasm into the domesticated gene pools using molecular tools and the improved knowledge of these genomes.

Black Sigatoka disease: new technologies to strengthen eradication strategies in Australia

In 2001, an incursion of Mycosphaerella fijiensis, the causal agent of black Sigatoka, was detected in Australia's largest commercial banana growing region, the Tully Banana Production Area in North Queensland. An intensive surveillance and eradication campaign was undertaken which resulted in the reinstatement of the disease-free status for black Sigatoka in 2005. This was the first time black Sigatoka had ever been eradicated from commercial plantations. The success of the eradication campaign was testament to good working relationships between scientists, growers, crop monitors, quarantine regulatory bodies and industry. A key contributing factor to the success was the deployment of a PCR-based molecular diagnostic assay, developed by the Cooperative Research Centre for Tropical Plant Protection (CRCTPP). This assay complemented morphological identification and allowed high throughput diagnosis of samples facilitating rapid decision-making during the eradication campaign. This paper describes the development and successful deployment of molecular diagnostics for black Sigatoka. Shortcomings in the gel-based assay are discussed and the advantages of highly specific real-time PCR assays, capable of differentiating between Mycosphaerella fijiensis, Mycosphaerella musicola and Mycosphaerella eumusae are outlined. Real-time assays may provide a powerful diagnostic tool for applications in surveillance, disease forecasting and resistance testing for Sigatoka leaf spot diseases.

Simple sequence repeat markers associated with three quantitative trait loci for black point resistance can be used to enrich selection populations in bread wheat

Black point in wheat has the potential to cost the Australian industry $A30.4 million a year. It is difficult and expensive to screen for resistance, so the aim of this study was to validate 3 previously identified quantitative trait loci (QTLs) for black point resistance on chromosomes 2B, 4A, and 3D of the wheat variety Sunco. Black point resistance data and simple sequence repeat (SSR) markers, linked to the resistance QTLs and suited to high-throughput assay, were analysed in the doubled haploid population, Batavia (susceptible) × Pelsart (resistant). Sunco and Pelsart both have Cook in their pedigree and both have the Triticum timopheevii translocation on 2B. SSR markers identified for the 3 genetic regions were gwm319 (2B, T. timopheevii translocation), wmc048 (4AS), and gwm341 (3DS). Gwm319 and wmc048 were associated with black point resistance in the validation population. Gwm341 may have an epistatic influence on the trait because when resistance alleles were present at both gwm319 and wmc048, the Batavia-derived allele at gwm341 was associated with a higher proportion of resistant lines. Data are presented showing the level of enrichment achieved for black point resistance, using 1, 2, or 3 of these molecular markers, and the number of associated discarded resistant lines. The level of population enrichment was found to be 1.83-fold with 6 of 17 resistant lines discarded when gwm319 and wmc048 were both used for selection. Interactions among the 3 QTLs appear complex and other genetic and epigenetic factors influence susceptibility to black point. Polymorphism was assessed for these markers within potential breeding material. This indicated that alternative markers to wmc048 may be required for some parental combinations. Based on these results, marker-assisted selection for the major black point resistance QTLs can increase the rate of genetic gain by improving the selection efficiency and may facilitate stacking of black point resistances from different sources.

A multi-microprocessor architecture for solving partial differential equations

This paper presents the architecture of a fault-tolerant, special-purpose multi-microprocessor system for solving Partial Differential Equations (PDEs). The modular nature of the architecture allows the use of hundreds of Processing Elements (PEs) for high throughput. Its performance is evaluated by both analytical and simulation methods. The results indicate that the system can achieve high operation rates and is not sensitive to inter-processor communication delay.

How accurate are the marker orders in crop linkage maps generated from large marker datasets?

Marker ordering during linkage map construction is a critical component of QTL mapping research. In recent years, high-throughput genotyping methods have become widely used, and these methods may generate hundreds of markers for a single mapping population. This poses problems for linkage analysis software because the number of possible marker orders increases exponentially as the number of markers increases. In this paper, we tested the accuracy of linkage analyses on simulated recombinant inbred line data using the commonly used Map Manager QTX (Manly et al. 2001: Mammalian Genome 12, 930-932) software and RECORD (Van Os et al. 2005: Theoretical and Applied Genetics 112, 30-40). Accuracy was measured by calculating two scores: % correct marker positions, and a novel, weighted rank-based score derived from the sum of absolute values of true minus observed marker ranks divided by the total number of markers. The accuracy of maps generated using Map Manager QTX was considerably lower than those generated using RECORD. Differences in linkage maps were often observed when marker ordering was performed several times using the identical dataset. In order to test the effect of reducing marker numbers on the stability of marker order, we pruned marker datasets focusing on regions consisting of tightly linked clusters of markers, which included redundant markers. Marker pruning improved the accuracy and stability of linkage maps because a single unambiguous marker order was produced that was consistent across replications of analysis. Marker pruning was also applied to a real barley mapping population and QTL analysis was performed using different map versions produced by the different programs. While some QTLs were identified with both map versions, there were large differences in QTL mapping results. Differences included maximum LOD and R-2 values at QTL peaks and map positions, thus highlighting the importance of marker order for QTL mapping

Development of microdevices for proteome research and diagnosis

The basic goal of a proteomic microchip is to achieve efficient and sensitive high throughput protein analyses, automatically carrying out several measurements in parallel. A protein microchip would either detect a single protein or a large set of proteins for diagnostic purposes, basic proteome or functional analysis. Such analyses would include e.g. interactomics, general protein expression studies, detecting structural alterations or secondary modifications. Visualization of the results may occur by simple immunoreactions, general or specific labelling, or mass spectrometry. For this purpose we have manufactured chip-based proteome analysis devices that utilize the classical polymer gel electrophoresis technology to run one and two-dimensional gel electrophoresis separations of proteins in just a smaller size. In total, we manufactured three functional prototypes of which one performed a miniaturized one-dimensional gel electrophoresis (1-DE) separation, the second and third preformed two-dimensional gel electrophoresis (2-DE) separations. These microchips were successfully used to separate and characterize a set of predefined standard proteins, cell and tissue samples. Also, the miniaturized 2-DE (ComPress-2DE) chip presents a novel way of combining the 1st and 2nd dimensional separations, thus avoiding manual handling of the gels, eliminate cross-contamination, and make analyses faster and repeatability better. They all showed the advantages of miniaturization over the commercial devices; such as fast analysis, low sample- and reagent consumption, high sensitivity, high repeatability and inexpensive performance. All these instruments have the potential to be fully automated due to their easy-to-use set-up.

Analysis of proteins with the `hot dog' fold: Prediction of function and identification of catalytic residues of hypothetical proteins

Background: The hot dog fold has been found in more than sixty proteins since the first report of its existence about a decade ago. The fold appears to have a strong association with fatty acid biosynthesis, its regulation and metabolism, as the proteins with this fold are predominantly coenzyme A-binding enzymes with a variety of substrates located at their active sites. Results: We have analyzed the structural features and sequences of proteins having the hot dog fold. This study reveals that though the basic architecture of the fold is well conserved in these proteins, significant differences exist in their sequence, nature of substrate and oligomerization. Segments with certain conserved sequence motifs seem to play crucial structural and functional roles in various classes of these proteins. Conclusion: The analysis led to predictions regarding the functional classification and identification of possible catalytic residues of a number of hot dog fold-containing hypothetical proteins whose structures were determined in high throughput structural genomics projects.

Genomic microarrays in chromosomal analysis of leukemia

Chromosomal alterations in leukemia have been shown to have prognostic and predictive significance and are also important minimal residual disease (MRD) markers in the follow-up of leukemia patients. Although specific oncogenes and tumor suppressors have been discovered in some of the chromosomal alterations, the role and target genes of many alterations in leukemia remain unknown. In addition, a number of leukemia patients have a normal karyotype by standard cytogenetics, but have variability in clinical course and are often molecularly heterogeneous. Cytogenetic methods traditionally used in leukemia analysis and diagnostics; G-banding, various fluorescence in situ hybridization (FISH) techniques, and chromosomal comparative genomic hybridization (cCGH), have enormously increased knowledge about the leukemia genome, but have limitations in resolution or in genomic coverage. In the last decade, the development of microarray comparative genomic hybridization (array-CGH, aCGH) for DNA copy number analysis and the SNP microarray (SNP-array) method for simultaneous copy number and loss of heterozygosity (LOH) analysis has enabled investigation of chromosomal and gene alterations genome-wide with high resolution and high throughput. In these studies, genetic alterations were analyzed in acute myeloid leukemia (AML) and chronic lymphocytic leukemia (CLL). The aim was to screen and characterize genomic alterations that could play role in leukemia pathogenesis by using aCGH and SNP-arrays. One of the most important goals was to screen cryptic alterations in karyotypically normal leukemia patients. In addition, chromosomal changes were evaluated to narrow the target regions, to find new markers, and to obtain tumor suppressor and oncogene candidates. The work presented here shows the capability of aCGH to detect submicroscopic copy number alterations in leukemia, with information about breakpoints and genes involved in the alterations, and that genome-wide microarray analyses with aCGH and SNP-array are advantageous methods in the research and diagnosis of leukemia. The most important findings were the cryptic changes detected with aCGH in karyotypically normal AML and CLL, characterization of amplified genes in 11q marker chromosomes, detection of deletion-based mechanisms of MLL-ARHGEF12 fusion gene formation, and detection of LOH without copy number alteration in karyotypically normal AML. These alterations harbor candidate oncogenes and tumor suppressors for further studies.