DeLA-Drug: A Deep Learning Algorithm for Automated Design of Druglike Analogues.

In this paper, we present a deep learning algorithm for automated design of druglike analogues (DeLA-Drug), a recurrent neural network (RNN) model composed of two long short-term memory (LSTM) layers and conceived for data-driven generation of similar-to-bioactive compounds. DeLA-Drug captures the syntax of SMILES strings of more than 1 million compounds belonging to the ChEMBL28 database and, by employing a new strategy called sampling with substitutions (SWS), generates molecules starting from a single user-defined query compound. Remarkably, the algorithm preserves druglikeness and synthetic accessibility of the known bioactive compounds present in the ChEMBL28 repository. The absence of any time-demanding fine-tuning procedure enables DeLA-Drug to perform a fast generation of focused libraries for further high-throughput screening and makes it a suitable tool for performing de novo design even in low-data regimes. To provide a concrete idea of its applicability, DeLA-Drug was applied to the cannabinoid receptor subtype 2 (CB2R), a known target involved in different pathological conditions such as cancer and neurodegeneration. DeLA-Drug, available as a free web platform (http://www.ba.ic.cnr.it/softwareic/deladrugportal/), can help medicinal chemists interested in generating analogues of compounds already available in their laboratories and, for this reason, good candidates for an easy and low-cost synthesis.

Structure-Based Prediction of hERG-Related Cardiotoxicity: A Benchmark Study.

Drug-induced blockade of the human ether-à-go-go-related gene (hERG) channel is today considered the main cause of cardiotoxicity in postmarketing surveillance. Hence, several ligand-based approaches were developed in the last years and are currently employed in the early stages of a drug discovery process for in silico cardiac safety assessment of drug candidates. Herein, we present the first structure-based classifiers able to discern hERG binders from nonbinders. LASSO regularized support vector machines were applied to integrate docking scores and protein-ligand interaction fingerprints. A total of 396 models were trained and validated based on: (i) high-quality experimental bioactivity information returned by 8337 curated compounds extracted from ChEMBL (version 25) and (ii) structural predictor data. Molecular docking simulations were performed using GLIDE and GOLD software programs and four different hERG structural models, namely, the recently published structures obtained by cryoelectron microscopy (PDB codes: 5VA1 and 7CN1) and two published homology models selected for comparison. Interestingly, some classifiers return performances comparable to ligand-based models in terms of area under the ROC curve (AUCMAX = 0.86 ± 0.01) and negative predictive values (NPVMAX = 0.81 ± 0.01), thus putting forward the herein proposed computational workflow as a valuable tool for predicting hERG-related cardiotoxicity without the limitations of ligand-based models, typically affected by low interpretability and a limited applicability domain. From a methodological point of view, our study represents the first example of a successful integration of docking scores and protein-ligand interaction fingerprints (IFs) through a support vector machine (SVM) LASSO regularized strategy. Finally, the study highlights the importance of using hERG structural models accounting for ligand-induced fit effects and allowed us to select the best-performing protein conformation (made available in the Supporting Information, SI) to be employed for a reliable structure-based prediction of hERG-related cardiotoxicity.

Combined microRNA and mRNA expression analysis in pediatric multiple sclerosis: an integrated approach to uncover novel pathogenic mechanisms of the disease.

Multiple sclerosis (MS) is a complex disease of the CNS that usually affects young adults, although 3-5% of cases are diagnosed in childhood and adolescence (hence called pediatric MS, PedMS). Genetic predisposition, among other factors, seems to contribute to the risk of the onset, in pediatric as in adult ages, but few studies have investigated the genetic 'environmentally naïve' load of PedMS. The main goal of this study was to identify circulating markers (miRNAs), target genes (mRNAs) and functional pathways associated with PedMS; we also verified the impact of miRNAs on clinical features, i.e. disability and cognitive performances. The investigation was performed in 19 PedMS and 20 pediatric controls (PCs) using a High-Throughput Next-generation Sequencing (HT-NGS) approach followed by an integrated bioinformatics/biostatistics analysis. Twelve miRNAs were significantly upregulated (let-7a-5p, let-7b-5p, miR-25-3p, miR-125a-5p, miR-942-5p, miR-221-3p, miR-652-3p, miR-182-5p, miR-185-5p, miR-181a-5p, miR-320a, miR-99b-5p) and 1 miRNA was downregulated (miR-148b-3p) in PedMS compared with PCs. The interactions between the significant miRNAs and their targets uncovered predicted genes (i.e. TNFSF13B, TLR2, BACH2, KLF4) related to immunological functions, as well as genes involved in autophagy-related processes (i.e. ATG16L1, SORT1, LAMP2) and ATPase activity (i.e. ABCA1, GPX3). No significant molecular profiles were associated with any PedMS demographic/clinical features. Both miRNAs and mRNA expressions predicted the phenotypes (PedMS-PC) with an accuracy of 92% and 91%, respectively. In our view, this original strategy of contemporary miRNA/mRNA analysis may help to shed light in the genetic background of the disease, suggesting further molecular investigations in novel pathogenic mechanisms.

Functional Implications of MicroRNAs in Crohn's Disease Revealed by Integrating MicroRNA and Messenger RNA Expression Profiling.

Crohn's disease (CD) is a debilitating inflammatory bowel disease (IBD) that emerges due to the influence of genetic and environmental factors. microRNAs (miRNAs) have been identified in the tissue and sera of IBD patients and may play an important role in the induction of IBD. Our study aimed to identify differentially expressed miRNAs and miRNAs with the ability to alter transcriptome activity by comparing inflamed tissue samples with their non-inflamed counterparts. We studied changes in miRNA-mRNA interactions associated with CD by examining their differential co-expression relative to normal mucosa from the same patients. Correlation changes between the two conditions were incorporated into scores of predefined gene sets to identify biological processes with altered miRNA-mediated control. Our study identified 28 miRNAs differentially expressed (p-values < 0.01), of which 14 are up-regulated. Notably, our differential co-expression analysis highlights microRNAs (i.e., miR-4284, miR-3194 and miR-21) that have known functional interactions with key mechanisms implicated in IBD. Most of these miRNAs cannot be detected by differential expression analysis that do not take into account miRNA-mRNA interactions. The identification of differential miRNA-mRNA co-expression patterns will facilitate the investigation of the miRNA-mediated molecular mechanisms underlying CD pathogenesis and could suggest novel drug targets for validation.

Meta-Analysis of Differential Connectivity in Gene Co-Expression Networks in Multiple Sclerosis.

Differential gene expression analyses to investigate multiple sclerosis (MS) molecular pathogenesis cannot detect genes harboring genetic and/or epigenetic modifications that change the gene functions without affecting their expression. Differential co-expression network approaches may capture changes in functional interactions resulting from these alterations. We re-analyzed 595 mRNA arrays from publicly available datasets by studying changes in gene co-expression networks in MS and in response to interferon (IFN)-ß treatment. Interestingly, MS networks show a reduced connectivity relative to the healthy condition, and the treatment activates the transcription of genes and increases their connectivity in MS patients. Importantly, the analysis of changes in gene connectivity in MS patients provides new evidence of association for genes already implicated in MS by single-nucleotide polymorphism studies and that do not show differential expression. This is the case of amiloride-sensitive cation channel 1 neuronal (ACCN1) that shows a reduced number of interacting partners in MS networks, and it is known for its role in synaptic transmission and central nervous system (CNS) development. Furthermore, our study confirms a deregulation of the vitamin D system: among the transcription factors that potentially regulate the deregulated genes, we find TCF3 and SP1 that are both involved in vitamin D3-induced p27Kip1 expression. Unveiling differential network properties allows us to gain systems-level insights into disease mechanisms and may suggest putative targets for the treatment.

Integrating genetic and gene expression evidence into genome-wide association analysis of gene sets.

Single variant or single gene analyses generally account for only a small proportion of the phenotypic variation in complex traits. Alternatively, gene set or pathway association analyses are playing an increasingly important role in uncovering genetic architectures of complex traits through the identification of systematic genetic interactions. Two dominant paradigms for gene set analyses are association analyses based on SNP genotypes and those based on gene expression profiles. However, gene-disease association can manifest in many ways, such as alterations of gene expression, genotype, and copy number; thus, an integrative approach combining multiple forms of evidence can more accurately and comprehensively capture pathway associations. We have developed a single statistical framework, Gene Set Association Analysis (GSAA), that simultaneously measures genome-wide patterns of genetic variation and gene expression variation to identify sets of genes enriched for differential expression and/or trait-associated genetic markers. Simulation studies illustrate that joint analyses of genomic data increase the power to detect real associations when compared with gene set methods that use only one genomic data type. The analysis of two human diseases, glioblastoma and Crohn's disease, detected abnormalities in previously identified disease-associated pathways, such as pathways related to PI3K signaling, DNA damage response, and the activation of NFKB. In addition, GSAA predicted novel pathway associations, for example, differential genetic and expression characteristics in genes from the ABC transporter family in glioblastoma and from the HLA system in Crohn's disease. These demonstrate that GSAA can help uncover biological pathways underlying human diseases and complex traits.

A comparative study of covariance selection models for the inference of gene regulatory networks.

MOTIVATION: The inference, or 'reverse-engineering', of gene regulatory networks from expression data and the description of the complex dependency structures among genes are open issues in modern molecular biology. RESULTS: In this paper we compared three regularized methods of covariance selection for the inference of gene regulatory networks, developed to circumvent the problems raising when the number of observations n is smaller than the number of genes p. The examined approaches provided three alternative estimates of the inverse covariance matrix: (a) the 'PINV' method is based on the Moore-Penrose pseudoinverse, (b) the 'RCM' method performs correlation between regression residuals and (c) 'ℓ(2C)' method maximizes a properly regularized log-likelihood function. Our extensive simulation studies showed that ℓ(2C) outperformed the other two methods having the most predictive partial correlation estimates and the highest values of sensitivity to infer conditional dependencies between genes even when a few number of observations was available. The application of this method for inferring gene networks of the isoprenoid biosynthesis pathways in Arabidopsis thaliana allowed to enlighten a negative partial correlation coefficient between the two hubs in the two isoprenoid pathways and, more importantly, provided an evidence of cross-talk between genes in the plastidial and the cytosolic pathways. When applied to gene expression data relative to a signature of HRAS oncogene in human cell cultures, the method revealed 9 genes (p-value<0.0005) directly interacting with HRAS, sharing the same Ras-responsive binding site for the transcription factor RREB1. This result suggests that the transcriptional activation of these genes is mediated by a common transcription factor downstream of Ras signaling. AVAILABILITY: Software implementing the methods in the form of Matlab scripts are available at: http://users.ba.cnr.it/issia/iesina18/CovSelModelsCodes.zip.

Transcriptome analysis reveals genes associated with stem cell activation by physical exercise in the dentate gyrus of aged p16Ink4a knockout mice.

Throughout adulthood neural stem cells divide in neurogenic niches-the dentate gyrus of the hippocampus and the subventricular zone-producing progenitor cells and new neurons. Stem cells self-renew, thus preserving their pool. Furthermore, the number of stem/progenitor cells in the neurogenic niches decreases with age. We have previously demonstrated that the cyclin-dependent kinase inhibitor p16Ink4a maintains, in aged mice, the pool of dentate gyrus stem cells by preventing their activation after a neurogenic stimulus such as exercise (running). We showed that, although p16Ink4a ablation by itself does not activate stem/progenitor cells, exercise strongly induced stem cell proliferation in p16Ink4a knockout dentate gyrus, but not in wild-type. As p16Ink4a regulates stem cell self-renewal during aging, we sought to profile the dentate gyrus transcriptome from p16Ink4a wild-type and knockout aged mice, either sedentary or running for 12 days. By pairwise comparisons of differentially expressed genes and by correlative analyses through the DESeq2 software, we identified genes regulated by p16Ink4a deletion, either without stimulus (running) added, or following running. The p16Ink4a knockout basic gene signature, i.e., in sedentary mice, involves upregulation of apoptotic, neuroinflammation- and synaptic activity-associated genes, suggesting a reactive cellular state. Conversely, another set of 106 genes we identified, whose differential expression specifically reflects the pattern of proliferative response of p16 knockout stem cells to running, are involved in processes that regulate stem cell activation, such as synaptic function, neurotransmitter metabolism, stem cell proliferation control, and reactive oxygen species level regulation. Moreover, we analyzed the regulation of these stem cell-specific genes after a second running stimulus. Surprisingly, the second running neither activated stem cell proliferation in the p16Ink4a knockout dentate gyrus nor changed the expression of these genes, confirming that they are correlated to the stem cell reactivity to stimulus, a process where they may play a role regulating stem cell activation.

Activated innate immunity and the involvement of CX3CR1-fractalkine in promoting hematuria in patients with IgA nephropathy.

A hallmark of immunoglobulin A nephropathy (IgAN) is episodes of gross hematuria coinciding with mucosal infections that can represent the disease-triggering event. Here we performed a whole genomic screen of IgAN patients during gross hematuria to clarify the link between mucosal antigens and glomerular hematuria. Modulated genes showed a clear involvement of the intracellular interferon signaling, antigen-presenting pathway, and the immunoproteasome. The mRNA and protein level of the chemokine receptor characterizing cytotoxic effector lymphocytes, CX3CR1, was upregulated. In vitro antigenic stimulation of peripheral blood mononuclear cells from IgAN patients, healthy blood donors, and other nephropathies with microscopic hematuria showed that only in IgAN patients was CX3CR1 enhanced in a dose-dependent manner. A significantly higher amount of glomerular and urinary fractalkine, the only ligand of CX3CR1, was also found in IgAN patients with recurrent episodes of gross hematuria compared with other patients with microscopic or no hematuria. This suggests a predisposition for cytotoxic cell extravasation only in patients with recurrent gross hematuria. Thus, we found a defect in antigen handling in peripheral blood mononuclear cells of IgAN patients with a specific increase of CX3CR1. This constitutive upregulation of glomerular and urinary fractalkine suggests an involvement of the CX3CR1-fractalkine axis in the exacerbation of gross hematuria.

Molecular pathways undergoing dramatic transcriptomic changes during tumor development in the human colon.

BACKGROUND: The malignant transformation of precancerous colorectal lesions involves progressive alterations at both the molecular and morphologic levels, the latter consisting of increases in size and in the degree of cellular atypia. Analyzing preinvasive tumors of different sizes can therefore shed light on the sequence of these alterations. METHODS: We used a molecular pathway-based approach to analyze transcriptomic profiles of 59 colorectal tumors representing early and late preinvasive stages and the invasive stage of tumorigenesis. Random set analysis was used to identify biological pathways enriched for genes differentially regulated in tumors (compared with 59 samples of normal mucosa). RESULTS: Of the 880 canonical pathways we investigated, 112 displayed significant tumor-related upregulation or downregulation at one or more stages of tumorigenesis. This allowed us to distinguish between pathways whose dysregulation is probably necessary throughout tumorigenesis and those whose involvement specifically drives progression from one stage to the next. We were also able to pinpoint specific changes within each gene set that seem to play key roles at each transition. The early preinvasive stage was characterized by cell-cycle checkpoint activation triggered by DNA replication stress and dramatic downregulation of basic transmembrane signaling processes that maintain epithelial/stromal homeostasis in the normal mucosa. In late preinvasive lesions, there was also downregulation of signal transduction pathways (e.g., those mediated by G proteins and nuclear hormone receptors) involved in cell differentiation and upregulation of pathways governing nuclear envelope dynamics and the G2>M transition in the cell cycle. The main features of the invasive stage were activation of the G1>S transition in the cell cycle, upregulated expression of tumor-promoting microenvironmental factors, and profound dysregulation of metabolic pathways (e.g., increased aerobic glycolysis, downregulation of pathways that metabolize drugs and xenobiotics). CONCLUSIONS: Our analysis revealed specific pathways whose dysregulation might play a role in each transition of the transformation process. This is the first study in which such an approach has been used to gain further insights into colorectal tumorigenesis. Therefore, these data provide a launchpad for further exploration of the molecular characterization of colorectal tumorigenesis using systems biology approaches.

RS-SNP: a random-set method for genome-wide association studies.

BACKGROUND: The typical objective of Genome-wide association (GWA) studies is to identify single-nucleotide polymorphisms (SNPs) and corresponding genes with the strongest evidence of association (the 'most-significant SNPs/genes' approach). Borrowing ideas from micro-array data analysis, we propose a new method, named RS-SNP, for detecting sets of genes enriched in SNPs moderately associated to the phenotype. RS-SNP assesses whether the number of significant SNPs, with p-value P ≤ α, belonging to a given SNP set S is statistically significant. The rationale of proposed method is that two kinds of null hypotheses are taken into account simultaneously. In the first null model the genotype and the phenotype are assumed to be independent random variables and the null distribution is the probability of the number of significant SNPs in S greater than observed by chance. The second null model assumes the number of significant SNPs in S depends on the size of and not on the identity of the SNPs in . Statistical significance is assessed using non-parametric permutation tests. RESULTS: We applied RS-SNP to the Crohn's disease (CD) data set collected by the Wellcome Trust Case Control Consortium (WTCCC) and compared the results with GENGEN, an approach recently proposed in literature. The enrichment analysis using RS-SNP and the set of pathways contained in the MSigDB C2 CP pathway collection highlighted 86 pathways rich in SNPs weakly associated to CD. Of these, 47 were also indicated to be significant by GENGEN. Similar results were obtained using the MSigDB C5 pathway collection. Many of the pathways found to be enriched by RS-SNP have a well-known connection to CD and often with inflammatory diseases. CONCLUSIONS: The proposed method is a valuable alternative to other techniques for enrichment analysis of SNP sets. It is well founded from a theoretical and statistical perspective. Moreover, the experimental comparison with GENGEN highlights that it is more robust with respect to false positive findings.

The anti-fibrotic effect of mycophenolic acid-induced neutral endopeptidase.

Mycophenolic acid (MPA) appears to have anti-fibrotic effects, but the molecular mechanisms underlying this are unknown. We prospectively studied 35 stable kidney transplant recipients maintained on cyclosporine and azathioprine. We converted 20 patients from azathioprine to enteric-coated mycophenolate sodium (EC-MPS) and continued the remaining 15 patients on azathioprine. Exploratory mRNA expression profiling, performed on five randomly selected EC-MPS patients, revealed significant upregulation of neutral endopeptidase (NEP), which is an enzyme that degrades angiotensin II. We confirmed these microarray data by measuring levels of NEP expression in all subjects; in addition, we found that NEP gene expression correlated inversely with proteinuria. In an additional 33 patients, glomerular and tubular NEP protein levels from renal graft biopsies were significantly higher among the 13 patients receiving cyclosporine + EC-MPS than among the 12 patients receiving cyclosporine + azathioprine or 8 patients receiving cyclosporine alone. Glomerular NEP expression inversely correlated with glomerulosclerosis and proteinuria, and tubular NEP expression inversely correlated with interstitial fibrosis. Incubation of human proximal tubular cells with MPA increased NEP gene expression in a dose- and time-dependent manner. Moreover, MPA reduced angiotensin II-induced expression of the profibrotic factor plasminogen activator inhibitor-1, and a specific NEP inhibitor completely reversed this effect. Taken together, our data suggest that MPA directly induces expression of neutral endopeptidase, which may reduce proteinuria and slow the progression of renal damage in kidney transplant recipients.

Transcriptome Analysis in a Mouse Model of Premature Aging of Dentate Gyrus: Rescue of Alpha-Synuclein Deficit by Virus-Driven Expression or by Running Restores the Defective Neurogenesis.

The dentate gyrus of the hippocampus and the subventricular zone are neurogenic niches where neural stem and progenitor cells replicate throughout life to generate new neurons. The Btg1 gene maintains the stem cells of the neurogenic niches in quiescence. The deletion of Btg1 leads to an early transient increase of stem/progenitor cells division, followed, however, by a decrease during adulthood of their proliferative capability, accompanied by apoptosis. Since a physiological decrease of neurogenesis occurs during aging, the Btg1 knockout mouse may represent a model of neural aging. We have previously observed that the defective neurogenesis of the Btg1 knockout model is rescued by the powerful neurogenic stimulus of physical exercise (running). To identify genes responsible for stem and progenitor cells maintenance, we sought here to find genes underlying this premature neural aging, and whose deregulated expression could be rescued by running. Through RNA sequencing we analyzed the transcriptomic profiles of the dentate gyrus isolated from Btg1 wild-type or Btg1 knockout adult (2-month-old) mice submitted to physical exercise or sedentary. In Btg1 knockout mice, 545 genes were deregulated, relative to wild-type, while 2081 genes were deregulated by running. We identified 42 genes whose expression was not only down-regulated in the dentate gyrus of Btg1 knockout, but was also counter-regulated to control levels by running in Btg1 knockout mice, vs. sedentary. Among these 42 counter-regulated genes, alpha-synuclein (Snca), Fos, Arc and Npas4 showed significantly greater differential regulation. These genes control neural proliferation, apoptosis, plasticity and memory and are involved in aging. In particular, Snca expression decreases during aging. We tested, therefore, whether an Snca-expressing lentivirus, by rescuing the defective Snca levels in the dentate gyrus of Btg1 knockout mice, could also reverse the aging phenotype, in particular the defective neurogenesis. We found that the exogenous expression of Snca reversed the Btg1 knockout-dependent decrease of stem cell proliferation as well as the increase of progenitor cell apoptosis. This indicates that Snca has a functional role in the process of neural aging observed in this model, and also suggests that Snca acts as a positive regulator of stem cell maintenance.

Altered modulation of WNT-beta-catenin and PI3K/Akt pathways in IgA nephropathy.

Immunoglobulin A nephropathy (IgAN) is the most common form of primary glomerulonephritis worldwide. The basic defect lies within the IgA immune system and in peripheral blood leukocytes, rather than local kidney abnormalities. To define the intracellular mechanisms leading to the disease, we conducted a microarray study to identify genes and pathways differentially modulated in peripheral blood leukocytes isolated from 12 IgAN patients and 8 healthy controls. The genes whose expression discriminated between the IgAN patients and controls were primarily involved in canonical WNT-beta-catenin and PI3K/Akt pathways. We also tested peripheral blood mononuclear cells and their subpopulations isolated from an independent group of IgAN patients and healthy controls. There were low protein levels of inversin and PTEN, key regulators of WNT-beta-catenin and PI3K/Akt, in IgAN patients, suggesting hyperactivation of these pathways. Also, there were increased phospho-Akt protein levels and nuclear beta-catenin accumulation with an enhanced peripheral blood mononuclear cell proliferation rate. Subpopulation analysis uncovered a major irregularity of WNT signaling in monocytes. Hence, hyperactivation of these pathways may provide insight into mechanisms contributing to the pathogenesis of IgAN.

On the reproducibility of results of pathway analysis in genome-wide expression studies of colorectal cancers.

One of the major problems in genomics and medicine is the identification of gene networks and pathways deregulated in complex and polygenic diseases, like cancer. In this paper, we address the problem of assessing the variability of results of pathways analysis identified in different and independent genome wide expression studies, in which the same phenotypic conditions are assayed. To this end, we assessed the deregulation of 1891 curated gene sets in four independent gene expression data sets of subjects affected by colorectal cancer (CRC). In this comparison we used two well-founded statistical models for evaluating deregulation of gene networks. We found that the results of pathway analysis in expression studies are highly reproducible. Our study revealed 53 pathways identified by the two methods in all the four data sets analyzed with high statistical significance and strong biological relevance with the pathology examined. This set of pathways associated to single markers as well as to whole biological processes altered constitutes a signature of the disease which sheds light on the genetics bases of CRC.

Cannabinoid Receptor Subtype 2 (CB2R) in a Multitarget Approach: Perspective of an Innovative Strategy in Cancer and Neurodegeneration.

The cannabinoid receptor subtype 2 (CB2R) represents an interesting and new therapeutic target for its involvement in the first steps of neurodegeneration as well as in cancer onset and progression. Several studies, focused on different types of tumors, report a promising anticancer activity induced by CB2R agonists due to their ability to reduce inflammation and cell proliferation. Moreover, in neuroinflammation, the stimulation of CB2R, overexpressed in microglial cells, exerts beneficial effects in neurodegenerative disorders. With the aim to overcome current treatment limitations, new drugs can be developed by specifically modulating, together with CB2R, other targets involved in such multifactorial disorders. Building on successful case studies of already developed multitarget strategies involving CB2R, in this Perspective we aim at prompting the scientific community to consider new promising target associations involving HDACs (histone deacetylases) and σ receptors by employing modern approaches based on molecular hybridization, computational polypharmacology, and machine learning algorithms.

Comparative study of gene set enrichment methods.

BACKGROUND: The analysis of high-throughput gene expression data with respect to sets of genes rather than individual genes has many advantages. A variety of methods have been developed for assessing the enrichment of sets of genes with respect to differential expression. In this paper we provide a comparative study of four of these methods: Fisher's exact test, Gene Set Enrichment Analysis (GSEA), Random-Sets (RS), and Gene List Analysis with Prediction Accuracy (GLAPA). The first three methods use associative statistics, while the fourth uses predictive statistics. We first compare all four methods on simulated data sets to verify that Fisher's exact test is markedly worse than the other three approaches. We then validate the other three methods on seven real data sets with known genetic perturbations and then compare the methods on two cancer data sets where our a priori knowledge is limited. RESULTS: The simulation study highlights that none of the three method outperforms all others consistently. GSEA and RS are able to detect weak signals of deregulation and they perform differently when genes in a gene set are both differentially up and down regulated. GLAPA is more conservative and large differences between the two phenotypes are required to allow the method to detect differential deregulation in gene sets. This is due to the fact that the enrichment statistic in GLAPA is prediction error which is a stronger criteria than classical two sample statistic as used in RS and GSEA. This was reflected in the analysis on real data sets as GSEA and RS were seen to be significant for particular gene sets while GLAPA was not, suggesting a small effect size. We find that the rank of gene set enrichment induced by GLAPA is more similar to RS than GSEA. More importantly, the rankings of the three methods share significant overlap. CONCLUSION: The three methods considered in our study recover relevant gene sets known to be deregulated in the experimental conditions and pathologies analyzed. There are differences between the three methods and GSEA seems to be more consistent in finding enriched gene sets, although no method uniformly dominates over all data sets. Our analysis highlights the deep difference existing between associative and predictive methods for detecting enrichment and the use of both to better interpret results of pathway analysis. We close with suggestions for users of gene set methods.

Statistical assessment of discriminative features for protein-coding and non coding cross-species conserved sequence elements.

BACKGROUND: The identification of protein coding elements in sets of mammalian conserved elements is one of the major challenges in the current molecular biology research. Many features have been proposed for automatically distinguishing coding and non coding conserved sequences, making so necessary a systematic statistical assessment of their differences. A comprehensive study should be composed of an association study, i.e. a comparison of the distributions of the features in the two classes, and a prediction study in which the prediction accuracies of classifiers trained on single and groups of features are analyzed, conditionally to the compared species and to the sequence lengths. RESULTS: In this paper we compared distributions of a set of comparative and non comparative features and evaluated the prediction accuracy of classifiers trained for discriminating sequence elements conserved among human, mouse and rat species. The association study showed that the analyzed features are statistically different in the two classes. In order to study the influence of the sequence lengths on the feature performances, a predictive study was performed on different data sets composed of coding and non coding alignments in equal number and equally long with an ascending average length. We found that the most discriminant feature was a comparative measure indicating the proportion of synonymous nucleotide substitutions per synonymous sites. Moreover, linear discriminant classifiers trained by using comparative features in general outperformed classifiers based on intrinsic ones. Finally, the prediction accuracy of classifiers trained on comparative features increased significantly by adding intrinsic features to the set of input variables, independently on sequence length (Kolmogorov-Smirnov P-value

Effect of different light-emitting diode (LED) irradiation on the shelf life and phytonutrient content of broccoli (Brassica oleracea L. var. italica).

Broccoli (Brassica oleracea L. var. italica) is largely cultivated in southern Italy. It is an important source of phytonutrients, which are partially lost during postharvest storage. The aim of this work was to evaluate the overall effect of five different low-intensity light-emitting diodes (LEDs) on the quality parameters of broccoli florets over 20 d of cold storage. The level of ascorbic acid, chlorophylls, carotenoids, phenolic compounds and soluble proteins, as well as colour analysis, were evaluated. Green LED increased the chlorophyll and ascorbic acid content; white, red and yellow LEDs had a positive effect on the redox status of broccoli. Globally, only green LED had a statistically significant positive effect when considering all analysed parameters and could be proposed to prolong the shelf life of broccoli during cold storage.

Proteome Response of Staphylococcus xylosus DSM 20266T to Anaerobiosis and Nitrite Exposure.

The viability and competitiveness of Staphylococcus xylosus in meat mostly depend on the ability to adapt itself to rapid oxygen and nutrients depletion during meat fermentation. The utilization of nitrite instead of oxygen becomes a successful strategy for this strain to improve its performance in anaerobiosis; however, metabolic pathways of this strain underlying this adaptation, are partially known. The aim of this study was to provide an overview on proteomic changes of S. xylosus DSM 20266T cultured under anaerobiosis and nitrite exposure. Thus, two different cultures of this strain, supplemented or not with nitrite, were in vitro incubated in aerobiosis and anaerobiosis monitoring cell viability, pH, oxidation reduction potential and nitrite content. Protein extracts, obtained from cells, collected as nitrite content was depleted, were analyzed by 2DE/MALDI-TOF/TOF-MS. Results showed that DSM 20266T growth was significantly sustained by nitrite in anaerobiosis, whereas no differences were found in aerobiosis. Accordingly, nitrite content was depleted after 13 h only in anaerobiosis. At this time of sampling, a comparative proteomic analysis showed 45 differentially expressed proteins. Most differences were found between aerobic and anaerobic cultures without nitrite; the induction of glycolytic enzymes and glyoxylate cycle, the reduction of TCA enzymes, and acetate fermentation were found in anaerobiosis to produce ATP and maintain the cell redox balance. In anaerobic cultures the nitrite supplementation partially restored TCA cycle, and reduced the amount of glycolytic enzymes. These results were confirmed by phenotypic microarray that, for the first time, was carried out on cell previously adapted at the different growth conditions. Overall, metabolic changes were similar between aerobiosis and anaerobiosis NO2-adapted cells, whilst cells grown under anaerobiosis showed different assimilation profiles by confirming proteomic data; indeed, these latter extensively assimilated substrates addressed at both supplying glucose for glycolysis or fueling alternative pathways to TCA cycle. In conclusion, metabolic pathways underlying the ability of S. xylosus to adapt itself to oxygen starvation were revealed; the addition of nitrite allowed S. xylosus to take advantage of nitrite to this condition, restoring some metabolic pathway underlying aerobic behavior of the strain.