Oligonucleotide fingerprint identification for microarray-based pathogen diagnostic assays

MOTIVATION: Advances in DNA microarray technology and computational methods have unlocked new opportunities to identify 'DNA fingerprints', i.e. oligonucleotide sequences that uniquely identify a specific genome. We present an integrated approach for the computational identification of DNA fingerprints for design of microarray-based pathogen diagnostic assays. We provide a quantifiable definition of a DNA fingerprint stated both from a computational as well as an experimental point of view, and the analytical proof that all in silico fingerprints satisfying the stated definition are found using our approach. RESULTS: The presented computational approach is implemented in an integrated high-performance computing (HPC) software tool for oligonucleotide fingerprint identification termed TOFI. We employed TOFI to identify in silico DNA fingerprints for several bacteria and plasmid sequences, which were then experimentally evaluated as potential probes for microarray-based diagnostic assays. Results and analysis of approximately 150 in silico DNA fingerprints for Yersinia pestis and 250 fingerprints for Francisella tularensis are presented. AVAILABILITY: The implemented algorithm is available upon request.     

Estimating p-values in small microarray experiments

MOTIVATION: Microarray data typically have small numbers of observations per gene, which can result in low power for statistical tests. Test statistics that borrow information from data across all of the genes can improve power, but these statistics have non-standard distributions, and their significance must be assessed using permutation analysis. When sample sizes are small, the number of distinct permutations can be severely limited, and pooling the permutation-derived test statistics across all genes has been proposed. However, the null distribution of the test statistics under permutation is not the same for equally and differentially expressed genes. This can have a negative impact on both p-value estimation and the power of information borrowing statistics. RESULTS: We investigate permutation based methods for estimating p-values. One of methods that uses pooling from a selected subset of the data are shown to have the correct type I error rate and to provide accurate estimates of the false discovery rate (FDR). We provide guidelines to select an appropriate subset. We also demonstrate that information borrowing statistics have substantially increased power compared to the t-test in small experiments.     

A global approach to identify differentially expressed genes in cDNA (two-color) microarray experiments

MOTIVATION: Currently most of the methods for identifying differentially expressed genes fall into the category of so called single-gene-analysis, performing hypothesis testing on a gene-by-gene basis. In a single-gene-analysis approach, estimating the variability of each gene is required to determine whether a gene is differentially expressed or not. Poor accuracy of variability estimation makes it difficult to identify genes with small fold-changes unless a very large number of replicate experiments are performed. RESULTS: We propose a method that can avoid the difficult task of estimating variability for each gene, while reliably identifying a group of differentially expressed genes with low false discovery rates, even when the fold-changes are very small. In this article, a new characterization of differentially expressed genes is established based on a theorem about the distribution of ranks of genes sorted by (log) ratios within each array. This characterization of differentially expressed genes based on rank is an example of all-gene-analysis instead of single gene analysis. We apply the method to a cDNA microarray dataset and many low fold-changed genes (as low as 1.3 fold-changes) are reliably identified without carrying out hypothesis testing on a gene-by-gene basis. The false discovery rate is estimated in two different ways reflecting the variability from all the genes without the complications related to multiple hypothesis testing. We also provide some comparisons between our approach and single-gene-analysis based methods. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Distinct roles of PMCA isoforms in Ca2+ homeostasis of bladder smooth muscle: evidence from PMCA gene-ablated mice

We previously showed that plasma membrane Ca²⁺-ATPase (PMCA) activity accounted for 25–30% of relaxation in bladder smooth muscle (8). Among the four PMCA isoforms only PMCA1 and PMCA4 are expressed in smooth muscle. To address the role of these isoforms, we measured cytosolic Ca²⁺ ([Ca²⁺]_i) using fura-PE3 and simultaneously measured contractility in bladder smooth muscle from wild-type (WT), Pmca1^+/–, Pmca4^+/–, Pmca4^–/–, and Pmca1^+/–Pmca4^–/– mice. There were no differences in basal [Ca²⁺]_i values between bladder preparations. KCl (80 mM) elicited both larger forces (150–190%) and increases in [Ca²⁺]_i (130–180%) in smooth muscle from Pmca1^+/– and Pmca1^+/–Pmca4^–/– bladders than those in WT or Pmca4^–/–. The responses to carbachol (CCh: 10 µM) were also greater in Pmca1^+/– (120–150%) than in WT bladders. In contrast, the responses in Pmca4^–/– and Pmca1^+/–Pmca4^–/– bladders to CCh were significantly smaller (40–50%) than WT. The rise in half-times of force and [Ca²⁺]_i increases in response to KCl and CCh, and the concomitant half-times of their decrease upon washout of agonist were prolonged in Pmca4^–/– (130–190%) and Pmca1^+/–Pmca4^–/– (120–250%) bladders, but not in Pmca1^+/– bladders with respect to WT. Our evidence indicates distinct isoform functions with the PMCA1 isoform involved in overall Ca²⁺ clearance, while PMCA4 is essential for the [Ca²⁺]_i increase and contractile response to the CCh receptor-mediated signal transduction pathway. PMCA; bladder smooth muscle; gene-altered mice     

Changes to the structure of Sphingomonas spp. communities associated with biodegradation of the herbicide isoproturon in soil

The phenyl-urea herbicide isoproturon is a major contaminant of surface and ground-water in agricultural catchments. Earlier work suggested that within-field spatial variation of isoproturon degradation rate resulted from interactions between catabolizing Sphingomonas spp. and pH. In the current study, changes to the structure of Sphingomonas communities during isoproturon catabolism were investigated using Sphingomonas-specific 16S rRNA gene primers. Growth-linked catabolism at high-pH (>7.5) sites was associated with the appearance of multiple new denaturing gradient gel electrophoresis (DGGE) bands. At low-pH sites, there was no change in DGGE banding at sites in which there was cometabolism, but at sites in which there was growth-linked catabolism, degradation was associated with the appearance of a new band not present at high pH sites. Sequencing of DGGE bands indicated that a strain related to Sphingomonas mali proliferated at low pH sites, while strain Sphingomonas sp. SRS2, a catabolic strain identified in earlier work, together with several further Sphingomonas spp., proliferated at high-pH sites. The data indicate that degradation was associated with complex changes to the structure of Sphingomonas spp. communities, the precise nature of which was spatially variable.     

Molecular pathogenesis and therapeutic targets in epithelial ovarian cancer

Ovarian cancer, the most aggressive gynecologic cancer, is the foremost cause of death from gynecologic malignancies in the developed world. Two primary reasons explain its aggressive behavior: most patients present with advanced disease at diagnosis, and die of recurrences from disease that has become resistant to conventional chemotherapies. In this paper on epithelial ovarian cancer (EOC), we will review molecular alterations associated with the few precursor lesions identified to date, followed by the more commonly recognized processes of de novo carcinogenesis, metastasis, and the development of chemoresistance. We will propose a unifying model of ovarian epithelial tumorigenesis that takes into account various hypotheses. We will also review novel approaches to overcome the major problem of chemoresistance in ovarian cancer. Finally, we will discuss advances and new challenges in the development of mouse model systems to investigate EOC precursor lesions, progression, metastasis, and chemoresistance.     

Detached and attached Arabidopsis leaf assays reveal distinctive defense responses against hemibiotrophic Colletotrichum spp

The agriculturally important genus Colletotrichum is an emerging model pathogen for studying defense in Arabidopsis. During the process of screening for novel pathogenic Colletotrichum isolates on Arabidopsis, we found significant differences in defense responses between detached and attached leaf assays. A near-adapted isolate Colletotrichum linicola A1 could launch a typical infection only on detached, but not attached, Arabidopsis leaves. Remarkably, resistance gene-like locus RCH1-mediated resistance in intact plants also was compromised in detached leaves during the attacks with the virulent reference isolate C. higginsianum. The differences in symptom development between the detached leaf and intact plant assays were further confirmed on defense-defective mutants following inoculation with C. higginsianum, where the greatest inconsistency occurred on ethylene-insensitive mutants. In intact Arabidopsis plants, both the salicylic acid- and ethylene-dependent pathways were required for resistance to C. higginsianum and were associated with induced expression of pathogenesis-related genes PR1 and PDF1.2. In contrast, disease symptom development in detached leaves appeared to be uncoupled from these defense pathways and more closely associated with senescence: an observation substantiated by coordinated gene expression analysis and disease symptom development, and chemically and genetically mimicking senescence.