Asymptotic behaviour and optimal word size for exact and approximate word matches between random sequences

BACKGROUND: The number of k-words shared between two sequences is a simple and effcient alignment-free sequence comparison method. This statistic, D(2), has been used for the clustering of EST sequences. Sequence comparison based on D(2 )is extremely fast, its runtime is proportional to the size of the sequences under scrutiny, whereas alignment-based comparisons have a worst-case run time proportional to the square of the size. Recent studies have tackled the rigorous study of the statistical distribution of D(2), and asymptotic regimes have been derived. The distribution of approximate k-word matches has also been studied. RESULTS: We have computed the D(2 )optimal word size for various sequence lengths, and for both perfect and approximate word matches. Kolmogorov-Smirnov tests show D(2 )to have a compound Poisson distribution at the optimal word size for small sequence lengths (below 400 letters) and a normal distribution at the optimal word size for large sequence lengths (above 1600 letters). We find that the D(2 )statistic outperforms BLAST in the comparison of artificially evolved sequences, and performs similarly to other methods based on exact word matches. These results obtained with randomly generated sequences are also valid for sequences derived from human genomic DNA. CONCLUSION: We have characterized the distribution of the D(2 )statistic at optimal word sizes. We find that the best trade-off between computational efficiency and accuracy is obtained with exact word matches. Given that our numerical tests have not included sequence shuffling, transposition or splicing, the improvements over existing methods reported here underestimate that expected in real sequences. Because of the linear run time and of the known normal asymptotic behavior, D(2)-based methods are most appropriate for large genomic sequences

A robustness study of parametric and non-parametric tests in model-based multifactor dimensionality reduction for epistasis detection

BACKGROUND: Applying a statistical method implies identifying underlying (model) assumptions and checking their validity in the particular context. One of these contexts is association modeling for epistasis detection. Here, depending on the technique used, violation of model assumptions may result in increased type I error, power loss, or biased parameter estimates. Remedial measures for violated underlying conditions or assumptions include data transformation or selecting a more relaxed modeling or testing strategy. Model-Based Multifactor Dimensionality Reduction (MB-MDR) for epistasis detection relies on association testing between a trait and a factor consisting of multilocus genotype information. For quantitative traits, the framework is essentially Analysis of Variance (ANOVA) that decomposes the variability in the trait amongst the different factors. In this study, we assess through simulations, the cumulative effect of deviations from normality and homoscedasticity on the overall performance of quantitative Model-Based Multifactor Dimensionality Reduction (MB-MDR) to detect 2-locus epistasis signals in the absence of main effects. METHODOLOGY: Our simulation study focuses on pure epistasis models with varying degrees of genetic influence on a quantitative trait. Conditional on a multilocus genotype, we consider quantitative trait distributions that are normal, chi-square or Student’s t with constant or non-constant phenotypic variances. All data are analyzed with MB-MDR using the built-in Student’s t-test for association, as well as a novel MB-MDR implementation based on Welch’s t-test. Traits are either left untransformed or are transformed into new traits via logarithmic, standardization or rank-based transformations, prior to MB-MDR modeling. RESULTS: Our simulation results show that MB-MDR controls type I error and false positive rates irrespective of the association test considered. Empirically-based MB-MDR power estimates for MB-MDR with Welch’s t-tests are generally lower than those for MB-MDR with Student’s t-tests. Trait transformations involving ranks tend to lead to increased power compared to the other considered data transformations. CONCLUSIONS: When performing MB-MDR screening for gene-gene interactions with quantitative traits, we recommend to first rank-transform traits to normality and then to apply MB-MDR modeling with Student’s t-tests as internal tests for association

Molecular Mimicry by an F-Box Effector of Legionella pneumophila Hijacks a Conserved Polyubiquitination Machinery within Macrophages and Protozoa

The ability of Legionella pneumophila to proliferate within various protozoa in the aquatic environment and in macrophages indicates a remarkable evolution and microbial exploitation of evolutionarily conserved eukaryotic processes. Ankyrin B (AnkB) of L. pneumophila is a non-canonical F-box-containing protein, and is the only known Dot/Icm-translocated effector of L. pneumophila essential for intra-vacuolar proliferation within both macrophages and protozoan hosts. We show that the F-box domain of AnkB and the 9L10P conserved residues are essential for intracellular bacterial proliferation and for rapid acquisition of polyubiquitinated proteins by the Legionella-containing vacuole (LCV) within macrophages, Dictyostelium discoideum, and Acanthamoeba. Interestingly, translocation of AnkB and recruitment of polyubiquitinated proteins in macrophages and Acanthamoeba is rapidly triggered by extracellular bacteria within 5 min of bacterial attachment. Ectopically expressed AnkB within mammalian cells is localized to the periphery of the cell where it co-localizes with host SKP1 and recruits polyubiquitinated proteins, which results in restoration of intracellular growth to the ankB mutant similar to the parental strain. While an ectopically expressed AnkB-9L10P/AA variant is localized to the cell periphery, it does not recruit polyubiquitinated proteins and fails to trans-rescue the ankB mutant intracellular growth defect. Direct in vivo interaction of AnkB but not the AnkB-9L10P/AA variant with the host SKP1 is demonstrated. Importantly, RNAi-mediated silencing of expression of SKP1 renders the cells non-permissive for intracellular proliferation of L. pneumophila. The role of AnkB in exploitation of the polyubiquitination machinery is essential for intrapulmonary bacterial proliferation in the mouse model of Legionnaires' disease. Therefore, AnkB exhibits a novel molecular and functional mimicry of eukaryotic F-box proteins that exploits conserved polyubiquitination machinery for intracellular proliferation within evolutionarily distant hosts

Integrated genetic map and genetic analysis of a region associated with root traits on the short arm of rye chromosome 1 in bread wheat

A rye–wheat centric chromosome translocation 1RS.1BL has been widely used in wheat breeding programs around the world. Increased yield of translocation lines was probably a consequence of increased root biomass. In an effort to map loci-controlling root characteristics, homoeologous recombinants of 1RS with 1BS were used to generate a consensus genetic map comprised of 20 phenotypic and molecular markers, with an average spacing of 2.5 cM. Physically, all recombination events were located in the distal 40% of the arms. A total of 68 recombinants was used and recombination breakpoints were aligned and ordered over map intervals with all the markers, integrated together in a genetic map. This approach enabled dissection of genetic components of quantitative traits, such as root traits, present on 1S. To validate our hypothesis, phenotyping of 45-day-old wheat roots was performed in five lines including three recombinants representative of the entire short arm along with bread wheat parents ‘Pavon 76’ and Pavon 1RS.1BL. Individual root characteristics were ranked and the genotypic rank sums were subjected to Quade analysis to compare the overall rooting ability of the genotypes. It appears that the terminal 15% of the rye 1RS arm carries gene(s) for greater rooting ability in wheat

Power analysis, sample size, and assessment of statistical assumptions—improving the evidential value of lighting research

The reporting of accurate and appropriate conclusions is an essential aspect of scientific research, and failure in this endeavor can threaten the progress of cumulative knowledge. This is highlighted by the current reproducibility crisis, and this crisis disproportionately affects fields that use behavioral research methods, as in much lighting research. A sample of general and topic-specific lighting research papers was reviewed for information about sample sizes and statistical reporting. This highlighted that lighting research is generally underpowered and, given median sample sizes, is unlikely to be able to reveal small effects. Lighting research most commonly uses parametric statistical tests, but assessment of test assumptions is rarely carried out. This risks the inappropriate use of statistical tests, potentially leading to type I and type II errors. Lighting research papers also rarely report measures of effect size, and this can hamper cumulative science and power analyses required to determine appropriate sample sizes for future research studies. Addressing the issues raised in this article related to sample sizes, statistical test assumptions, and reporting of effect sizes can improve the evidential value of lighting research

Effects of adult exposure to bisphenol A on genes involved in the physiopathology of rat prefrontal cortex

Several neurological and behavioral dysfunctions have been reported in animals exposed to bisphenol A (BPA). However, little is known about the impact of adult exposure to BPA on brain physiopathology. Here, we focused on prefrontal cortex (PFC) of rats, because it is an important area for cognitive control, complex behaviors and is altered in many psychopathologies. Gamma-aminobutyric acid (GABA) and serotonin (5-HT) systems are essential for PFC function. Therefore, we examined the effects of adult exposure to BPA on 5α-Reductase (5α-R) and cytochrome P450 aromatase (P450arom), enzymes that synthesize GABAA receptor modulators, and tryptophan hydroxylase (Tph), the rate-limiting enzyme in 5-HT biosynthesis. To gain better understanding of BPA’s action in the adult PFC, 84 genes involved in neurotoxicity were also analysed. Adult male and female rats were subcutaneously injected for 4 days with 50 µg/kg/day, the current reference safe dose for BPA. mRNA and protein levels of 5α-R, P450arom and Tph were quantified by real-time RT-PCR and Western blot. Genes linked to neurotoxicity were analyzed by PCR-Array technology. Adult exposure to BPA increased both P450arom and Tph2 expression in PFC of male and female, but decreased 5α-R1 expression in female. Moreover, we identified 17 genes related to PFC functions such as synaptic plasticity and memory, as potential targets of BPA. Our results provided new insights on the molecular mechanisms underlying BPA action in the physiopathology of PFC, but also raise the question about the safety of short-term exposure to it in the adulthood.This research was supported by grants from Ministerio de Ciencia e Innovación (BFU2008-05340) and by the Junta de Andalucía (CTS202-Endocronología y Metabolismo)

HMGA1 drives stem cell, inflammatory pathway, and cell cycle progression genes during lymphoid tumorigenesis

<p>Abstract</p> <p>Background</p> <p>Although the <it>high mobility group A1 </it>(<it>HMGA1</it>) gene is widely overexpressed in diverse cancers and portends a poor prognosis in some tumors, the molecular mechanisms that mediate its role in transformation have remained elusive. <it>HMGA1 </it>functions as a potent oncogene in cultured cells and induces aggressive lymphoid tumors in transgenic mice. Because HMGA1 chromatin remodeling proteins regulate transcription, <it>HMGA1 </it>is thought to drive malignant transformation by modulating expression of specific genes. Genome-wide studies to define HMGA1 transcriptional networks during tumorigenesis, however, are lacking. To define the HMGA1 transcriptome, we analyzed gene expression profiles in lymphoid cells from <it>HMGA1a </it>transgenic mice at different stages in tumorigenesis.</p> <p>Results</p> <p>RNA from lymphoid samples at 2 months (before tumors develop) and 12 months (after tumors are well-established) was screened for differential expression of > 20,000 unique genes by microarray analysis (Affymetrix) using a parametric and nonparametric approach. Differential expression was confirmed by quantitative RT-PCR in a subset of genes. Differentially expressed genes were analyzed for cellular pathways and functions using Ingenuity Pathway Analysis. Early in tumorigenesis, HMGA1 induced inflammatory pathways with NFkappaB identified as a major node. In established tumors, HMGA1 induced pathways involved in cell cycle progression, cell-mediated immune response, and cancer. At both stages in tumorigenesis, HMGA1 induced pathways involved in cellular development, hematopoiesis, and hematologic development. Gene set enrichment analysis showed that stem cell and immature T cell genes are enriched in the established tumors. To determine if these results are relevant to human tumors, we knocked-down HMGA1 in human T-cell leukemia cells and identified a subset of genes dysregulated in both the transgenic and human lymphoid tumors.</p> <p>Conclusions</p> <p>We found that <it>HMGA1 </it>induces inflammatory pathways early in lymphoid tumorigenesis and pathways involved in stem cells, cell cycle progression, and cancer in established tumors. <it>HMGA1 </it>also dyregulates genes and pathways involved in stem cells, cellular development and hematopoiesis at both early and late stages of tumorigenesis. These results provide insight into <it>HMGA1 </it>function during tumor development and point to cellular pathways that could serve as therapeutic targets in lymphoid and other human cancers with aberrant <it>HMGA1 </it>expression.</p

Identifying New Therapeutic Targets via Modulation of Protein Corona Formation by Engineered Nanoparticles

We introduce a promising methodology to identify new therapeutic targets in cancer. Proteins bind to nanoparticles to form a protein corona. We modulate this corona by using surface-engineered nanoparticles, and identify protein composition to provide insight into disease development.Using a family of structurally homologous nanoparticles we have investigated the changes in the protein corona around surface-functionalized gold nanoparticles (AuNPs) from normal and malignant ovarian cell lysates. Proteomics analysis using mass spectrometry identified hepatoma-derived growth factor (HDGF) that is found exclusively on positively charged AuNPs ((+)AuNPs) after incubation with the lysates. We confirmed expression of HDGF in various ovarian cancer cells and validated binding selectivity to (+)AuNPs by Western blot analysis. Silencing of HDGF by siRNA resulted s inhibition in proliferation of ovarian cancer cells.We investigated the modulation of protein corona around surface-functionalized gold nanoparticles as a promising approach to identify new therapeutic targets. The potential of our method for identifying therapeutic targets was demonstrated through silencing of HDGF by siRNA, which inhibited proliferation of ovarian cancer cells. This integrated proteomics, bioinformatics, and nanotechnology strategy demonstrates that protein corona identification can be used to discover novel therapeutic targets in cancer

Inhibition of Host Vacuolar H+-ATPase Activity by a Legionella pneumophila Effector

Legionella pneumophila is an intracellular pathogen responsible for Legionnaires' disease. This bacterium uses the Dot/Icm type IV secretion system to inject a large number of bacterial proteins into host cells to facilitate the biogenesis of a phagosome permissive for its intracellular growth. Like many highly adapted intravacuolar pathogens, L. pneumophila is able to maintain a neutral pH in the lumen of its phagosome, particularly in the early phase of infection. However, in all cases, the molecular mechanisms underlying this observation remain unknown. In this report, we describe the identification and characterization of a Legionella protein termed SidK that specifically targets host v-ATPase, the multi-subunit machinery primarily responsible for organelle acidification in eukaryotic cells. Our results indicate that after being injected into infected cells by the Dot/Icm secretion system, SidK interacts with VatA, a key component of the proton pump. Such binding leads to the inhibition of ATP hydrolysis and proton translocation. When delivered into macrophages, SidK inhibits vacuole acidification and impairs the ability of the cells to digest non-pathogenic E. coli. We also show that a domain located in the N-terminal portion of SidK is responsible for its interactions with VatA. Furthermore, expression of sidK is highly induced when bacteria begin to enter new growth cycle, correlating well with the potential temporal requirement of its activity during infection. Our results indicate that direct targeting of v-ATPase by secreted proteins constitutes a virulence strategy for L. pneumophila, a vacuolar pathogen of macrophages and amoebae

Identification of Novel Genes and Pathways Regulating SREBP Transcriptional Activity

BACKGROUND: Lipid metabolism in mammals is orchestrated by a family of transcription factors called sterol regulatory element-binding proteins (SREBPs) that control the expression of genes required for the uptake and synthesis of cholesterol, fatty acids, and triglycerides. SREBPs are thus essential for insulin-induced lipogenesis and for cellular membrane homeostasis and biogenesis. Although multiple players have been identified that control the expression and activation of SREBPs, gaps remain in our understanding of how SREBPs are coordinated with other physiological pathways. METHODOLOGY: To identify novel regulators of SREBPs, we performed a genome-wide cDNA over-expression screen to identify proteins that might modulate the transcription of a luciferase gene driven from an SREBP-specific promoter. The results were verified through secondary biological assays and expression data were analyzed by a novel application of the Gene Set Enrichment Analysis (GSEA) method. CONCLUSIONS/SIGNIFICANCE: We screened 10,000 different cDNAs and identified a number of genes and pathways that have previously not been implicated in SREBP control and cellular cholesterol homeostasis. These findings further our understanding of lipid biology and should lead to new insights into lipid associated disorders