A genomic perspective on a new bacterial genus and species from the Alcaligenaceae family, Basilea psittacipulmonis

BACKGROUND A novel Gram-negative, non-haemolytic, non-motile, rod-shaped bacterium was discovered in the lungs of a dead parakeet (Melopsittacus undulatus) that was kept in captivity in a petshop in Basel, Switzerland. The organism is described with a chemotaxonomic profile and the nearly complete genome sequence obtained through the assembly of short sequence reads. RESULTS Genome sequence analysis and characterization of respiratory quinones, fatty acids, polar lipids, and biochemical phenotype is presented here. Comparison of gene sequences revealed that the most similar species is Pelistega europaea, with BLAST identities of only 93% to the 16S rDNA gene, 76% identity to the rpoB gene, and a similar GC content (~43%) as the organism isolated from the parakeet, DSM 24701 (40%). The closest full genome sequences are those of Bordetella spp. and Taylorella spp. High-throughput sequencing reads from the Illumina-Solexa platform were assembled with the Edena de novo assembler to form 195 contigs comprising the ~2 Mb genome. Genome annotation with RAST, construction of phylogenetic trees with the 16S rDNA (rrs) gene sequence and the rpoB gene, and phylogenetic placement using other highly conserved marker genes with ML Tree all suggest that the bacterial species belongs to the Alcaligenaceae family. Analysis of samples from cages with healthy parakeets suggested that the newly discovered bacterial species is not widespread in parakeet living quarters. CONCLUSIONS Classification of this organism in the current taxonomy system requires the formation of a new genus and species. We designate the new genus Basilea and the new species psittacipulmonis. The type strain of Basilea psittacipulmonis is DSM 24701 (= CIP 110308 T, 16S rDNA gene sequence Genbank accession number JX412111 and GI 406042063).

Monogenic Human Skin Disorders

Human genodermatoses represent a broad and partly confusing spectrum of countless rare diseases with confluent and overlapping phenotypes often impeding a precise diagnosis in an affected individual. High-throughput sequencing techniques have expedited the identification of novel genes and have dramatically simplified the establishment of genetic diagnoses in such heterogeneous disorders. The precise genetic diagnosis of a skin disorder is crucial for the appropriate counselling of patients and their relatives regarding the course of the disease, prognosis and recurrence risks. Understanding the underlying pathophysiology is a prerequisite to understanding the disease and developing specific, targeted or individualized therapeutic approaches. We aimed to create a comprehensive overview of human genodermatoses and their respective genetic aetiology known to date. We hope this may represent a useful tool in guiding dermatologists towards genetic diagnoses, providing patients with individual knowledge on the respective disorder and applying novel research findings to clinical practice.

Profiling invasiveness in head and neck cancer: recent contributions of genomic and transcriptomic approaches.

High-throughput molecular profiling approaches have emerged as precious research tools in the field of head and neck translational oncology. Such approaches have identified and/or confirmed the role of several genes or pathways in the acquisition/maintenance of an invasive phenotype and the execution of cellular programs related to cell invasion. Recently published new-generation sequencing studies in head and neck squamous cell carcinoma (HNSCC) have unveiled prominent roles in carcinogenesis and cell invasion of mutations involving NOTCH1 and PI3K-patwhay components. Gene-expression profiling studies combined with systems biology approaches have allowed identifying and gaining further mechanistic understanding into pathways commonly enriched in invasive HNSCC. These pathways include antigen-presenting and leucocyte adhesion molecules, as well as genes involved in cell-extracellular matrix interactions. Here we review the major insights into invasiveness in head and neck cancer provided by high-throughput molecular profiling approaches.

Regulation of human (adrenal) androgen biosynthesis-New insights from novel throughput technology studies

Androgens are precursors for sex steroids and are predominantly produced in the human gonads and the adrenal cortex. They are important for intrauterine and postnatal sexual development and human reproduction. Although human androgen biosynthesis has been extensively studied in the past, exact mechanisms underlying the regulation of androgen production in health and disease remain vague. Here, the knowledge on human androgen biosynthesis and regulation is reviewed with a special focus on human adrenal androgen production and the hyperandrogenic disorder of polycystic ovary syndrome (PCOS). Since human androgen regulation is highly specific without a good animal model, most studies are performed on patients harboring inborn errors of androgen biosynthesis, on human biomaterials and human (tumor) cell models. In the past, most studies used a candidate gene approach while newer studies use high throughput technologies to identify novel regulators of androgen biosynthesis. Using genome wide association studies on cohorts of patients, novel PCOS candidate genes have been recently described. Variant 2 of the DENND1A gene was found overexpressed in PCOS theca cells and confirmed to enhance androgen production. Transcriptome profiling of dissected adrenal zones established a role for BMP4 in androgen synthesis. Similarly, transcriptome analysis of human adrenal NCI-H295 cells identified novel regulators of androgen production. Kinase p38α (MAPK14) was found to phosphorylate CYP17 for enhanced 17,20 lyase activity and RARB and ANGPTL1 were detected in novel networks regulating androgens. The discovery of novel players for androgen biosynthesis is of clinical significance as it provides targets for diagnostic and therapeutic use.

Theoretical and experimental studies of linkage disequilibrium in human populations

Linkage disequilibrium (LD) is defined as the nonrandom association of alleles at two or more loci in a population and may be a useful tool in a diverse array of applications including disease gene mapping, elucidating the demographic history of populations, and testing hypotheses of human evolution. However, the successful application of LD-based approaches to pertinent genetic questions is hampered by a lack of understanding about the forces that mediate the genome-wide distribution of LD within and between human populations. Delineating the genomic patterns of LD is a complex task that will require interdisciplinary research that transcends traditional scientific boundaries. The research presented in this dissertation is predicated upon the need for interdisciplinary studies and both theoretical and experimental projects were pursued. In the theoretical studies, I have investigated the effect of genotyping errors and SNP identification strategies on estimates of LD. The primary importance of these two chapters is that they provide important insights and guidance for the design of future empirical LD studies. Furthermore, I analyzed the allele frequency distribution of 26,530 single nucleotide polymorphisms (SNPs) in three populations and generated the first-generation natural selection map of the human genome, which will be an important resource for explaining and understanding genomic patterns of LD. Finally, in the experimental study, I describe a novel and simple, low-cost, and high-throughput SNP genotyping method. The theoretical analyses and experimental tools developed in this dissertation will facilitate a more complete understanding of patterns of LD in human populations. ^

Nonlinear tests for genetic studies of complex disease

Linkage and association studies are major analytical tools to search for susceptibility genes for complex diseases. With the availability of large collection of single nucleotide polymorphisms (SNPs) and the rapid progresses for high throughput genotyping technologies, together with the ambitious goals of the International HapMap Project, genetic markers covering the whole genome will be available for genome-wide linkage and association studies. In order not to inflate the type I error rate in performing genome-wide linkage and association studies, multiple adjustment for the significant level for each independent linkage and/or association test is required, and this has led to the suggestion of genome-wide significant cut-off as low as 5 × 10 −7. Almost no linkage and/or association study can meet such a stringent threshold by the standard statistical methods. Developing new statistics with high power is urgently needed to tackle this problem. This dissertation proposes and explores a class of novel test statistics that can be used in both population-based and family-based genetic data by employing a completely new strategy, which uses nonlinear transformation of the sample means to construct test statistics for linkage and association studies. Extensive simulation studies are used to illustrate the properties of the nonlinear test statistics. Power calculations are performed using both analytical and empirical methods. Finally, real data sets are analyzed with the nonlinear test statistics. Results show that the nonlinear test statistics have correct type I error rates, and most of the studied nonlinear test statistics have higher power than the standard chi-square test. This dissertation introduces a new idea to design novel test statistics with high power and might open new ways to mapping susceptibility genes for complex diseases. ^

PumaPlex 1.0: Data generated during the development of the SNP markers and SNP genotypes of pumas

Pumas are one of the most studied terrestrial mammals because of their widespread distribution, substantial ecological impacts, and conflicts with humans. Extensive efforts, often employing genetic methods, are undertaken to manage this species. However, the comparison of population genetic data is difficult because few of the microsatellite loci chosen are shared across research programs. Here, we describe the development of PumaPlex, a high-throughput assay to genotype 25 single nucleotide polymorphisms in pumas. We validated PumaPlex in more than 700 North American pumas (Puma concolor couguar), and demonstrated its ability to generate reproducible genotypes and accurately identify individuals. Furthermore, we compared PumaPlex with traditional genotyping of 12 microsatellite loci in fecal DNA samples and found that PumaPlex produced significantly more genotypes with fewer false alleles. PumaPlex promotes the cross-laboratory comparison of genotypes, is easily expandable in the future, and is a valuable tool for the genetic monitoring and management of North American puma populations.

Molecular tools to improve chestnut management: El Bierzo as a case study

The European chestnut (Castanea sativa Mill.) is a multipurpose species that has been widely cultivated around the Mediterranean basin since ancient times. New varieties were brought to the Iberian Peninsula during the Roman Empire, which coexist since then with native populations that survived the last glaciation. The relevance of chestnut cultivation has being steadily growing since the Middle Ages, until the rural decline of the past century put a stop to this trend. Forest fires and diseases were also major factors. Chestnut cultivation is gaining momentum again due to its economic (wood, fruits) and ecologic relevance, and represents currently an important asset in many rural areas of Europe. In this Thesis we apply different molecular tools to help improve current management strategies. For this study we have chosen El Bierzo (Castile and Leon, NW Spain), which has a centenary tradition of chestnut cultivation and management, and also presents several unique features from a genetic perspective (next paragraph). Moreover, its nuts are widely appreciated in Spain and abroad for their organoleptic properties. We have focused our experimental work on two major problems faced by breeders and the industry: the lack of a fine-grained genetic characterization and the need for new strategies to control blight disease. To characterize with sufficient detail the genetic diversity and structure of El Bierzo orchards, we analyzed DNA from 169 trees grafted for nut production covering the entire region. We also analyzed 62 nuts from all traditional varieties. El Bierzo constitutes an outstanding scenario to study chestnut genetics and the influence of human management because: (i) it is located at one extreme of the distribution area; (ii) it is a major glacial refuge for the native species; (iii) it has a long tradition of human management (since Roman times, at least); and (iv) its geographical setting ensures an unusual degree of genetic isolation. Thirteen microsatellite markers provided enough informativeness and discrimination power to genotype at the individual level. Together with an unexpected level of genetic variability, we found evidence of genetic structure, with three major gene pools giving rise to the current population. High levels of genetic differentiation between groups supported this organization. Interestingly, genetic structure does not match with spatial boundaries, suggesting that the exchange of material and cultivation practices have strongly influenced natural gene flow. The microsatellite markers selected for this study were also used to classify a set of 62 samples belonging to all traditional varieties. We identified several cases of synonymies and homonymies, evidencing the need to substitute traditional classification systems with new tools for genetic profiling. Management and conservation strategies should also benefit from these tools. The avenue of high-throughput sequencing technologies, combined with the development of bioinformatics tools, have paved the way to study transcriptomes without the need for a reference genome. We took advantage of RNA sequencing and de novo assembly tools to determine the transcriptional landscape of chestnut in response to blight disease. In addition, we have selected a set of candidate genes with high potential for developing resistant varieties via genetic engineering. Our results evidenced a deep transcriptional reprogramming upon fungal infection. The plant hormones ET and JA appear to orchestrate the defensive response. Interestingly, our results also suggest a role for auxins in modulating such response. Many transcription factors were identified in this work that interact with promoters of genes involved in disease resistance. Among these genes, we have conducted a functional characterization of a two major thaumatin-like proteins (TLP) that belongs to the PR5 family. Two genes encoding chestnut cotyledon TLPs have been previously characterized, termed CsTL1 and CsTL2. We substantiate here their protective role against blight disease for the first time, including in silico, in vitro and in vivo evidence. The synergy between TLPs and other antifungal proteins, particularly endo-p-1,3-glucanases, bolsters their interest for future control strategies based on biotechnological approaches.

Quantitative high performance liquid chromatography/tandem mass spectrometric analysis of the four classes of F2-isoprostanes in human urine

Isoprostanes (iPs) are free radical catalyzed prostaglandin isomers. Analysis of individual isomers of PGF2α—F2-iPs—in urine has reflected lipid peroxidation in humans. However, up to 64 F2-iPs may be formed, and it is unknown whether coordinate generation, disposition, and excretion of F2-iPs occurs in humans. To address this issue, we developed methods to measure individual members of the four structural classes of F2-iPs, using liquid chromatography/tandem mass spectrometry (LC/MS/MS), in which sample preparation is minimized. Authentic standards of F2-iPs of classes III, IV, V, and VI were used to identify class-specific ions for multiple reaction monitoring. Using iPF2α-VI as a model compound, we demonstrated the reproducibility of the assay in human urine. Urinary levels of all F2-iPs measured were elevated in patients with familial hypercholesterolemia. However, only three of eight F2-iPs were elevated in patients with congestive heart failure, compared with controls. Paired analyses by GC/MS and LC/MS/MS of iPF2α-VI in hypercholesterolemia and of 8,12-iso-iPF2α-VI in congestive heart failure were highly correlated. This approach will permit high throughput analysis of multiple iPs in human disease.

Serial microanalysis of renal transcriptomes

Large-scale gene expression studies can now be routinely performed on macroamounts of cells, but it is unclear to which extent current methods are valuable for analyzing complex tissues. In the present study, we used the method of serial analysis of gene expression (SAGE) for quantitative mRNA profiling in the mouse kidney. We first performed SAGE at the whole-kidney level by sequencing 12,000 mRNA tags. Most abundant tags corresponded to transcripts widely distributed or enriched in the predominant kidney epithelial cells (proximal tubular cells), whereas transcripts specific for minor cell types were barely evidenced. To better explore such cells, we set up a SAGE adaptation for downsized extracts, enabling a 1,000-fold reduction of the amount of starting material. The potential of this approach was evaluated by studying gene expression in microdissected kidney tubules (50,000 cells). Specific gene expression profiles were obtained, and known markers (e.g., uromodulin in the thick ascending limb of Henle's loop and aquaporin-2 in the collecting duct) were found appropriately enriched. In addition, several enriched tags had no databank match, suggesting that they correspond to unknown or poorly characterized transcripts with specific tissue distribution. It is concluded that SAGE adaptation for downsized extracts makes possible large-scale quantitative gene expression measurements in small biological samples and will help to study the tissue expression and function of genes not evidenced with other high-throughput methods.

A quantitative method for evaluating the stabilities of nucleic acids

We report a general method for screening, in solution, the impact of deviations from canonical Watson-Crick composition on the thermodynamic stability of nucleic acid duplexes. We demonstrate how fluorescence resonance energy transfer (FRET) can be used to detect directly free energy differences between an initially formed “reference” duplex (usually a Watson-Crick duplex) and a related “test” duplex containing a lesion/alteration of interest (e.g., a mismatch, a modified, a deleted, or a bulged base, etc.). In one application, one titrates into a solution containing a fluorescently labeled, FRET-active, reference duplex, an unlabeled, single-stranded nucleic acid (test strand), which may or may not compete successfully to form a new duplex. When a new duplex forms by strand displacement, it will not exhibit FRET. The resultant titration curve (normalized fluorescence intensity vs. logarithm of test strand concentration) yields a value for the difference in stability (free energy) between the newly formed, test strand-containing duplex and the initial reference duplex. The use of competitive equilibria in this assay allows the measurement of equilibrium association constants that far exceed the magnitudes accessible by conventional titrimetric techniques. Additionally, because of the sensitivity of fluorescence, the method requires several orders of magnitude less material than most other solution methods. We discuss the advantages of this method for detecting and characterizing any modification that alters duplex stability, including, but not limited to, mutagenic lesions. We underscore the wide range of accessible free energy values that can be defined by this method, the applicability of the method in probing for a myriad of nucleic acid variations, such as single nucleotide polymorphisms, and the potential of the method for high throughput screening.

The Medicago Genome Initiative: a model legume database

The Medicago Genome Initiative (MGI) is a database of EST sequences of the model legume Medicago truncatula. The database is available to the public and has resulted from a collaborative research effort between the Samuel Roberts Noble Foundation and the National Center for Genome Resources to investigate the genome of M.truncatula. MGI is part of the greater integrated Medicago functional genomics program at the Noble Foundation (http://www.noble .org), which is taking a global approach in studying the genetic and biochemical events associated with the growth, development and environmental interactions of this model legume. Our approach will include: large-scale EST sequencing, gene expression profiling, the generation of M.truncatula activation-tagged and promoter trap insertion mutants, high-throughput metabolic profiling, and proteome studies. These multidisciplinary information pools will be interfaced with one another to provide scientists with an integrated, holistic set of tools to address fundamental questions pertaining to legume biology. The public interface to the MGI database can be accessed at http://www.ncgr.org/research/mgi.

trEST, trGEN and Hits: access to databases of predicted protein sequences

High throughput genome (HTG) and expressed sequence tag (EST) sequences are currently the most abundant nucleotide sequence classes in the public database. The large volume, high degree of fragmentation and lack of gene structure annotations prevent efficient and effective searches of HTG and EST data for protein sequence homologies by standard search methods. Here, we briefly describe three newly developed resources that should make discovery of interesting genes in these sequence classes easier in the future, especially to biologists not having access to a powerful local bioinformatics environment. trEST and trGEN are regularly regenerated databases of hypothetical protein sequences predicted from EST and HTG sequences, respectively. Hits is a web-based data retrieval and analysis system providing access to precomputed matches between protein sequences (including sequences from trEST and trGEN) and patterns and profiles from Prosite and Pfam. The three resources can be accessed via the Hits home page (http://hits.isb-sib.ch).

High-sensitivity array analysis of gene expression for the early detection of disseminated breast tumor cells in peripheral blood

Early detection is an effective means of reducing cancer mortality. Here, we describe a highly sensitive high-throughput screen that can identify panels of markers for the early detection of solid tumor cells disseminated in peripheral blood. The method is a two-step combination of differential display and high-sensitivity cDNA arrays. In a primary screen, differential display identified 170 candidate marker genes differentially expressed between breast tumor cells and normal breast epithelial cells. In a secondary screen, high-sensitivity arrays assessed expression levels of these genes in 48 blood samples, 22 from healthy volunteers and 26 from breast cancer patients. Cluster analysis identified a group of 12 genes that were elevated in the blood of cancer patients. Permutation analysis of individual genes defined five core genes (P ≤ 0.05, permax test). As a group, the 12 genes generally distinguished accurately between healthy volunteers and patients with breast cancer. Mean expression levels of the 12 genes were elevated in 77% (10 of 13) untreated invasive cancer patients, whereas cluster analysis correctly classified volunteers and patients (P = 0.0022, Fisher's exact test). Quantitative real-time PCR confirmed array results and indicated that the sensitivity of the assay (1:2 × 108 transcripts) was sufficient to detect disseminated solid tumor cells in blood. Expression-based blood assays developed with the screening approach described here have the potential to detect and classify solid tumor cells originating from virtually any primary site in the body.

Simultaneous assessment of loss of heterozygosity at multiple microsatellite loci using semi-automated fluorescence-based detection: subregional mapping of chromosome 4 in cervical carcinoma.

Detection of loss of heterozygosity (LOH) by comparison of normal and tumor genotypes using PCR-based microsatellite loci provides considerable advantages over traditional Southern blotting-based approaches. However, current methodologies are limited by several factors, including the numbers of loci that can be evaluated for LOH in a single experiment, the discrimination of true alleles versus "stutter bands," and the use of radionucleotides in detecting PCR products. Here we describe methods for high throughput simultaneous assessment of LOH at multiple loci in human tumors; these methods rely on the detection of amplified microsatellite loci by fluorescence-based DNA sequencing technology. Data generated by this approach are processed by several computer software programs that enable the automated linear quantitation and calculation of allelic ratios, allowing rapid ascertainment of LOH. As a test of this approach, genotypes at a series of loci on chromosome 4 were determined for 58 carcinomas of the uterine cervix. The results underscore the efficacy, sensitivity, and remarkable reproducibility of this approach to LOH detection and provide subchromosomal localization of two regions of chromosome 4 commonly altered in cervical tumors.