Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.     

Clustering of time-course gene expression data using functional data analysis

Clustering of gene expression data collected across time is receiving growing attention in the biological literature since time-course experiments allow one to understand dynamic biological processes and identify genes governed by the same processes. It is believed that genes demonstrating similar expression profiles over time might give an informative insight into how underlying biological mechanisms work. In this paper, we propose a method based on functional data analysis (FNDA) to cluster time-dependent gene expression profiles. Consideration of clustering problems using the FNDA setting provides ways to take time dependency into account by using basis function expansion to describe the partially observed curves. We also discuss how to choose the number of bases in the basis function expansion in FNDA. A synthetic cycle data and a real data are used to demonstrate the proposed method and some comparisons between the proposed and existing approaches using the adjusted Rand indices are made.     

Evaluation of biological monitoring markers using genomic and proteomic analysis for automobile emission inspectors and waste incinerating workers exposed to polycyclic aromatic hydrocarbons or 2,3,7,8,-tetracholrodedibenzo-p-dioxins

In this study, we investigated the effects of PAHs and dioxin on mRNA and plasma protein expression using genomic and proteomic analysis for automobile emission inspectors and waste incineration workers. About 54 workers from automobile emission inspection offices, 31 workers from waste incinerating company and 84 unexposed healthy subjects were enrolled in this study. Urine and air samples were collected and analyzed by HPLC and GC/MS. Comet assays were carried out to evaluate any DNA damage in mononuclear and polynuclear cells. A significant difference in Olive tail moments in mononuclear cells was observed between exposed and control subjects (P < 0.0001). To examine the differences of the gene expression profile in automobile emission inspectors and waste incineration workers, radioactive complementary DNA microarrays were used to evaluate changes in the expression of 1,152 total genes. The gene expression profiles showed that 11 genes were up-regulated and 4 genes were down-regulated in waste incinerating workers as compared with controls. Plasma proteins were analyzed by 2-dimentional electrophoresis with pH 3-10 NL IPG Dry strip. The protein expression profiles showed that 8 proteins were up- regulated and 1 protein, haptoglobin, was down- regulated in automobile emission inspectors and waste incineration workers. Serum paraoxonase/ arylesterase was found only in the plasma of waste incineration workers. The expression of genes and proteins involved in oxidative stress were up-regulated in both automobile emission inspectors and waste incineration workers. Several proteins, such as transthyrethin, sarcolectin and haptoglobin, that were highly up- or down-regulated, could serve as biological monitoring markers for future study.     

Rival penalized competitive learning (RPCL): a topology-determining algorithm for analyzing gene expression data

DNA arrays have become the immediate choice in the analysis of large-scale expression measurements. Understanding the expression pattern of genes provide functional information on newly identified genes by computational approaches. Gene expression pattern is an indicator of the state of the cell, and abnormal cellular states can be inferred by comparing expression profiles. Since co-regulated genes, and genes involved in a particular pathway, tend to show similar expression patterns, clustering expression patterns has become the natural method of choice to differentiate groups. However, most methods based on cluster analysis suffer from the usual problems (i) dead units, and (ii) the problem of determining the correct number of clusters (k) needed to classify the data. Selecting the k has been an open problem of pattern recognition and statistics for decades. Since clustering reveals similar patterns present in the data, fixing this number strongly influences the quality of the result. While there is no theoretical solution to this problem, the number of clusters can be decided by a heuristic clustering algorithm called rival penalized competitive learning (RPCL). We present a novel implementation of RPCL that transforms the correct number of clusters problem to the tractable problem of clustering based on the degree of similarity. This is biologically significant since our implementation clusters functionally co-regulated genes and genes that present similar patterns of expression. This new approach reveals potential genes that are co-involved in a biological process. This implementation of the RPCL algorithm is useful in differentiating groups involved in concerted functional regulation and helps to progressively home into patterns, which are closely similar.     

Identification of Phototoxic Polycyclic Aromatic Hydrocarbons in Sediments Through Sample Fractionation and QSAR Analysis

Abstract

The toxicity of certain polycyclic aromatic hydrocarbons (PAHs) can be greatly increased by simultaneous exposure of test organisms to ultraviolet (UV) wavelengths present in sunlight. This phenomenon, commonly termed photoinduced toxicity, had been evaluated extensively in laboratory settings where only one chemical of concern was present. However, more recent studies have demonstrated that complex mixtures of PAHs present, for example in sediments, also can cause phototoxicity to a variety of aquatic species when the samples are tested in simulated sunlight. Unfortunately, because these types of samples can contain thousands of substituted and unsubstituted PAHs it is difficult, if not impossible, to use conventional analytical techniques to identify those responsible for photoinduced toxicity. The objective of the present study was to link two powerful ecotoxicology tools, toxicity-based fractionation techniques and QSAR models, to identify phototoxic chemicals in a sediment contaminated with PAHs emanating from an oil refinery. Extensive chromatographic fractionation of pore water from the sediment, in conjunction with toxicity testing, yielded a simplified set of sample fractions containing 12 PAHs that were identified via mass spectroscopy. Evaluation of these compounds using a recently developed QSAR model revealed that, based upon their HOMO-LUMO gap energies, about half were capable of producing photoinduced toxicity. We further evaluated the phototoxic potential of the reduced set of PAHs by determining their propensity to bioaccumulate in test organisms, through calculation of octanol-water partition coefficients for the chemicals. These studies represent a novel linkage of sample fractionation methods with QSAR models for conducting an ecological risk assessment.     

Characterization of the azinomycin B biosynthetic gene cluster revealing a different iterative type I polyketide synthase for naphthoate biosynthesis

Azinomycin B is a complex natural product containing densely assembled functionalities with potent antitumor activity. Cloning and sequence analysis of the azi gene cluster revealed an iterative type I polyketide synthase (PKS) gene, five nonribosomal peptide synthetases (NRPSs) genes and numerous genes encoding the biosynthesis of unusual building blocks and tailoring steps for azinomycin B production. Characterization of AziB as a 5-methyl-naphthoic acid (NPA) synthase showed a distinct selective reduction pattern in aromatic polyketide biosynthesis governed by bacterial iterative type I PKSs. Heterologous expression established the PKS-post modification route from 5-methyl-NPA to reach the first building block 3-methoxy-5-methyl-NPA. This proposed azinomycin B biosynthetic pathway sets the stage to investigate the enzymatic mechanisms for building structurally unique and pharmaceutically important groups, including the unprecedented azabicyclic ring system and highly active epoxide moiety.     

QSARs for Photoinduced Toxicity of Aromatic Compounds

Abstract

This paper reviews the results of a series of efforts to develop QSAR models for aromatic chemicals whose toxicity is enhanced by the ultraviolet radiation present in sunlight. Photoinduced toxicity of polycyclic aromatic hydrocarbons (PAHs) was found to be a result of competing factors: structural (such as molecular stability and light absorbance) and external (irradiation energy and intensity). These two factors interact, producing a complex, multilinear relationship between toxicity and electronic structure. The HOMO-LUMO gap provided a useful ground-state index to explain the persistence, light absorption, and eventually, the photoinduced toxicity of PAHs. The derived QSAR clearly distinguished phototoxic differences between pairs of structurally similar PAHs, such as phenanthrene and anthracene, benzo [a] anthracene and tetracene, et cetera. Those PAHs exhibiting photoinduced toxicity were consistently within a specific range of the electronic parameter. Further modeling revealed a significant correlation between molecular electronic structure of excited-state PAHs and toxicity. The effect of substituents on photoinduced acute toxicity of PAHs also was investigated. Some substituents such as alkyl and hydroxy moieties do not significantly reduce the HOMO-LUMO gap of parent PAHs. Nitro- and chloro- moieties cause more significant variations of the HOMO-LUMO gap. It is concluded that photoinduced toxicity of PAHs is mainly dictated by the electronic structure of the parent chemicals. Evaluation of the phototoxicity of flexible aromatic molecules (α-terthienyls), generally supported the PAH models.     

Cloning, sequencing and analysis of the enterocin biosynthesis gene cluster from the marine isolate ‘Streptomyces maritimus’: evidence for the derailment of an aromatic polyketide synthase

Background: Polycyclic aromatic polyketides, such as the tetracyclines and anthracyclines, are synthesized by bacterial aromatic polyketide synthases (PKSs). Such PKSs contain a single set of iteratively used individual proteins for the construction of a highly labile poly-β-carbonyl intermediate that is cyclized by associated enzymes to the core aromatic polyketide. A unique polyketide biosynthetic pathway recently identified in the marine strain ‘Streptomyces maritimus’ deviates from the normal aromatic PKS model in the generation of a diverse series of chiral, non-aromatic polyketides.Results: A 21.3 kb gene cluster encoding the biosynthesis of the enterocin and wailupemycin family of polyketides from ‘S. maritimus’ has been cloned and sequenced. The biosynthesis of these structurally diverse polyketides is encoded on a 20 open reading frames gene set containing a centrally located aromatic PKS. The architecture of this novel type II gene set differs from all other aromatic PKS clusters by the absence of cyclase and aromatase encoding genes and the presence of genes encoding the biosynthesis and attachment of the unique benzoyl-CoA starter unit. In addition to the previously reported heterologous expression of the gene set, in vitro and in vivo expression studies with the cytochrome P-450 EncR and the ketoreductase EncD, respectively, support the involvement of the cloned genes in enterocin biosynthesis.Conclusions: The enterocin biosynthesis gene cluster represents the most versatile type II PKS system investigated to date. A large series of divergent metabolites are naturally generated from the single biochemical pathway, which has several metabolic options for creating structural diversity. The absence of cyclase and aromatase gene products and the involvement of an oxygenase-catalyzed Favorskii-like rearrangement provide insight into the observed spontaneity of this pathway. This system provides the foundation for engineering hybrid expression sets in the generation of structurally novel compounds for use in drug discovery.     

Morphogenetic and chemical stability of long-term maintained Agrobacterium-mediated transgenic Catharanthus roseus plants

Transgenic Catharanthus roseus plants (transgenic Dhawal [DT] and transgenic Nirmal [NT]) obtained from the Agrobacterium tumefaciens and Agrobacteriumrhizognenes-mediated transformations, respectively, have been maintained in vitro for 5 years. Plants were studied at regular intervals for various parameters such as plant height, leaf size, multiplication rate, alkaloid profile and presence of marker genes. DT plant gradually lost the GUS gene expression and it was not detected in the fifth year while NT plant demonstrated the presence of genes rolA, rolB and rolC even in the fifth year, indicating the more stable nature of Ri transgene. Vindoline content in the DT was two times more than in non-transformed control plants. Alkaloid and tryptophan profiles were almost constant during the 5 years. The cluster analysis revealed that the DT plant is more close to the control Nirmal plant followed by NT plant.     

Expression patterns of photoperiod and temperature regulated heading date genes in Oryza sativa

In plants, flowering is a major biological phenomenon, which is regulated by an array of interactions occurring between biotic and abiotic factors. In our study, we have compared the expression profiles of flowering genes involved in the flowering pathway, which are influenced by conditions like photoperiod and temperature from seedling to heading developmental stages in two Oryza sativa indica varieties, viz., Zhenshan 97 and Minghui 63 using a expression network approach. Using the network expression approach, we found 17 co-expressed genes having the same expression profile pattern as three key photoperiod flowering genes Hd1, Ehd1 and Hd3a. We also demonstrated that these three co-expressed genes have a similar simulation pattern as temperature flowering genes. Based on our observations, we hypothesize that photoperiod and temperature regulate flowering pathways independently. The present study provides a basis for understanding the network of co-expressed genes involved in flowering pathway and presents a way to demonstrate the behavior of specific gene sets in specific cultivars.     

Gene expression variability in mammalian embryonic stem cells using single cell RNA-seq data

BackgroundGene expression heterogeneity contributes to development as well as disease progression. Due to technological limitations, most studies to date have focused on differences in mean expression across experimental conditions, rather than differences in gene expression variance. The advent of single cell RNA sequencing has now made it feasible to study gene expression heterogeneity and to characterise genes based on their coefficient of variation.MethodsWe collected single cell gene expression profiles for 32 human and 39 mouse embryonic stem cells and studied correlation between diverse characteristics such as network connectivity and coefficient of variation (CV) across single cells. We further systematically characterised properties unique to High CV genes.ResultsHighly expressed genes tended to have a low CV and were enriched for cell cycle genes. In contrast, High CV genes were co-expressed with other High CV genes, were enriched for bivalent (H3K4me3 and H3K27me3) marked promoters and showed enrichment for response to DNA damage and DNA repair.ConclusionsTaken together, this analysis demonstrates the divergent characteristics of genes based on their CV. High CV genes tend to form co-expression clusters and they explain bivalency at least in part.     

On application of directons to functional classification of genes in prokaryotes

Functional classification of genes represents one of the most basic problems in genome analysis and annotation. Our analysis of some of the popular methods for functional classification of genes shows that these methods are not always consistent with each other and may not be specific enough for high-resolution gene functional annotations. We have developed a method to integrate genomic neighborhood information of genes with their sequence similarity information for the functional classification of prokaryotic genes. The application of our method to 93 proteobacterial genomes has shown that (i) the genomic neighborhoods are much more conserved across prokaryotic genomes than expected by chance, and such conservation can be utilized to improve functional classification of genes; (ii) while our method is consistent with the existing popular schemes as much as they are among themselves, it does provide functional classification at higher resolution and hence allows functional assignments of (new) genes at a more specific level; and (iii) our method is fairly stable when being applied to different genomes.