Benzene forms hydrogen bonds with water.

Fully rotationally resolved spectra of three isotopic species of 1:1 clusters of benzene with water (H(2)O, D(2)O, and HDO) were fit to yield moments of inertia that demonstrate unambiguously that water is positioned above the benzene plane in nearly free internal rotation with both hydrogen atoms pointing toward the pi cloud. Ab initio calculations (MP2 level of electron correlation and 6-31 G(**) basis set with basis set superposition error corrections) predict a binding energy D(e) greater, similar 1.78 kilocalories per mole. In both the experimental and theoretical structures, water is situated nearly 1 angstrom within the van der Waals contacts of the monomers, a clear manifestation of hydrogen bond formation in this simple model of aqueous-pi electron interactions.

Context-specific infinite mixtures for clustering gene expression profiles across diverse microarray dataset.

MOTIVATION: Identifying groups of co-regulated genes by monitoring their expression over various experimental conditions is complicated by the fact that such co-regulation is condition-specific. Ignoring the context-specific nature of co-regulation significantly reduces the ability of clustering procedures to detect co-expressed genes due to additional 'noise' introduced by non-informative measurements. RESULTS: We have developed a novel Bayesian hierarchical model and corresponding computational algorithms for clustering gene expression profiles across diverse experimental conditions and studies that accounts for context-specificity of gene expression patterns. The model is based on the Bayesian infinite mixtures framework and does not require a priori specification of the number of clusters. We demonstrate that explicit modeling of context-specificity results in increased accuracy of the cluster analysis by examining the specificity and sensitivity of clusters in microarray data. We also demonstrate that probabilities of co-expression derived from the posterior distribution of clusterings are valid estimates of statistical significance of created clusters. AVAILABILITY: The open-source package gimm is available at http://eh3.uc.edu/gimm.

Evolutionary Divergence of Aggregatibacter actinomycetemcomitans.

Gram-negative facultative Aggregatibacter actinomycetemcomitans is an oral pathogen associated with periodontitis. The genetic heterogeneity among A. actinomycetemcomitans strains has been long recognized. This study provides a comprehensive genomic analysis of A. actinomycetemcomitans and the closely related nonpathogenic Aggregatibacter aphrophilus. Whole genome sequencing by Illumina MiSeq platform was performed for 31 A. actinomycetemcomitans and 2 A. aphrophilus strains. Sequence similarity analysis shows a total of 3,220 unique genes across the 2 species, where 1,550 are core genes present in all genomes and 1,670 are variable genes (accessory genes) missing in at least 1 genome. Phylogenetic analysis based on 397 concatenated core genes distinguished A. aphrophilus and A. actinomycetemcomitans. The latter was in turn divided into 5 clades: clade b (serotype b), clade c (serotype c), clade e/f (serotypes e and f), clade a/d (serotypes a and d), and clade e' (serotype e strains). Accessory genes accounted for 14.1% to 23.2% of the A. actinomycetemcomitans genomes, with a majority belonging to the category of poorly characterized by Cluster of Orthologous Groups classification. These accessory genes were often organized into genomic islands (n = 387) with base composition biases, suggesting their acquisitions via horizontal gene transfer. There was a greater degree of similarity in gene content and genomic islands among strains within clades than between clades. Strains of clade e' isolated from human were found to be missing the genomic island that carries genes encoding cytolethal distending toxins. Taken together, the results suggest a pattern of sequential divergence, starting from the separation of A. aphrophilus and A. actinomycetemcomitans through gain and loss of genes and ending with the divergence of the latter species into distinct clades and serotypes. With differing constellations of genes, the A. actinomycetemcomitans clades may have evolved distinct adaptation strategies to the human oral cavity.

Comparative hybridization of an array of 21,500 ovarian cDNAs for the discovery of genes overexpressed in ovarian carcinomas.

Comparative hybridization of cDNA arrays is a powerful tool for the measurement of differences in gene expression between two or more tissues. We optimized this technique and employed it to discover genes with potential for the diagnosis of ovarian cancer. This cancer is rarely identified in time for a good prognosis after diagnosis. An array of 21,500 unknown ovarian cDNAs was hybridized with labeled first-strand cDNA from 10 ovarian tumors and six normal tissues. One hundred and thirty-four clones are overexpressed in at least five of the 10 tumors. These cDNAs were sequenced and compared to public sequence databases. One of these, the gene HE4, was found to be expressed primarily in some ovarian cancers, and is thus a potential marker of ovarian carcinoma.

Inexpensive handheld device for the construction of high-density nucleic acid arrays.

We report an easy-to-use, 384-pin handheld arraying and replicating device (ARD) for constructing high-density replicas of nucleic acids and E. coli transformants. We have modified an existing 384-pin tool to include a novel guide system to ensure vertical pin movement and enhance reproducibility. An asymmetric rectangular multiplexing frame is designed to increase the array density to 1536 dots on a standard microplate-size nylon membrane and to reduce the time and effort involved in producing array replicas. Our initial studies used the ARD to construct 1536-dot arrays of ovarian cDNA clones. We have hybridized these arrays with 32P-labeled probes, which resulted in distinctive signals for either visual interpretation or semiautomatic spot detection and signal integration.

An analysis of the dynamic range and linearity of an infrared DNA sequencer.

We are currently developing genotyping software and protocols for use on the Li-Cor model 4000(L) infrared fluorescence DNA sequencers. During the development of the genotyping software it became apparent that the potential dynamic range of the instrument was not being realized when the data collection parameters were optimized to produce a high-contrast image on the computer screen. In particular, we were unable to obtain peaks with signal to noise (S/N) greater than about 30:1 and the stronger peaks often saturated the detector. Because the numerical dynamic range available in 16-bit data collection mode exceeds 65000, our limited dynamic range of about 30 in actual data was somewhat puzzling. Hence, we undertook a study to explore the dynamic range and linearity of the Li-Cor DNA sequencer in order to minimize background fluorescence and noise as well as maximize the available S/N. Data is presented on the background and noise using different polyacrylamide gel mixes with various signal gain and offset values, and the relative contribution of the glass, gel and instrumentation to the background fluorescence is discussed. Based on these results, optimum gain and offset values were determined that maintain the background fluorescence at approximately 1-2% of the maximum dynamic range with a minimum amount of noise. Using these optimized values, we determined the detection system is linear over three orders of magnitude by titrating known quantities of an infrared fluorophore-labeled primer. In addition, we were able to detect approximately 15.2 amoles of labeled primer. The results provided by this study establish a set of guidelines for evaluating how to set the signal gain and offset in order to minimize the background and maximize the S/N and dynamic range of the Li-Cor sequencer.

Bayesian mixture model based clustering of replicated microarray data.

MOTIVATION: Identifying patterns of co-expression in microarray data by cluster analysis has been a productive approach to uncovering molecular mechanisms underlying biological processes under investigation. Using experimental replicates can generally improve the precision of the cluster analysis by reducing the experimental variability of measurements. In such situations, Bayesian mixtures allow for an efficient use of information by precisely modeling between-replicates variability. RESULTS: We developed different variants of Bayesian mixture based clustering procedures for clustering gene expression data with experimental replicates. In this approach, the statistical distribution of microarray data is described by a Bayesian mixture model. Clusters of co-expressed genes are created from the posterior distribution of clusterings, which is estimated by a Gibbs sampler. We define infinite and finite Bayesian mixture models with different between-replicates variance structures and investigate their utility by analyzing synthetic and the real-world datasets. Results of our analyses demonstrate that (1) improvements in precision achieved by performing only two experimental replicates can be dramatic when the between-replicates variability is high, (2) precise modeling of intra-gene variability is important for accurate identification of co-expressed genes and (3) the infinite mixture model with the 'elliptical' between-replicates variance structure performed overall better than any other method tested. We also introduce a heuristic modification to the Gibbs sampler based on the 'reverse annealing' principle. This modification effectively overcomes the tendency of the Gibbs sampler to converge to different modes of the posterior distribution when started from different initial positions. Finally, we demonstrate that the Bayesian infinite mixture model with 'elliptical' variance structure is capable of identifying the underlying structure of the data without knowing the 'correct' number of clusters. AVAILABILITY: The MS Windows based program named Gaussian Infinite Mixture Modeling (GIMM) implementing the Gibbs sampler and corresponding C++ code are available at http://homepages.uc.edu/~medvedm/GIMM.htm SUPPLEMENTAL INFORMATION: http://expression.microslu.washington.edu/expression/kayee/medvedovic2003/medvedovic_bioinf2003.html

Global impact of influenza virus on cellular pathways is mediated by both replication-dependent and -independent events.

Influenza virus, the causative agent of the common flu, is a worldwide health problem with significant economic consequences. Studies of influenza virus biology have revealed elaborate mechanisms by which the virus interacts with its host cell as it inhibits the synthesis of cellular proteins, evades the innate antiviral response, and facilitates production of viral RNAs and proteins. With the advent of DNA array technology it is now possible to obtain a large-scale view of how viruses alter the environment within the host cell. In this study, the cellular response to influenza virus infection was examined by monitoring the steady-state mRNA levels for over 4,600 cellular genes. Infections with active and inactivated influenza viruses identified changes in cellular gene expression that were dependent on or independent of viral replication, respectively. Viral replication resulted in the downregulation of many cellular mRNAs, and the effect was enhanced with time postinfection. Interestingly, several genes involved in protein synthesis, transcriptional regulation, and cytokine signaling were induced by influenza virus replication, suggesting that some may play essential or accessory roles in the viral life cycle or the host cell's stress response. The gene expression pattern induced by inactivated viruses revealed induction of the cellular metallothionein genes that may represent a protective response to virus-induced oxidative stress. Genome-scale analyses of virus infections will help us to understand the complexities of virus-host interactions and may lead to the discovery of novel drug targets or antiviral therapies.

Interaction of pseudomonas aeruginosa with epithelial cells: identification of differentially regulated genes by expression microarray analysis of human cDNAs.

Pseudomonas aeruginosa is an opportunistic pathogen that plays a major role in lung function deterioration in cystic fibrosis patients. To identify critical host responses during infection, we have used high-density DNA microarrays, consisting of 1,506 human cDNA clones, to monitor gene expression in the A549 lung pneumocyte cell line during exposure to P. aeruginosa. We have identified host genes that are differentially expressed upon infection, several of which require interaction with P. aeruginosa and the expression of the major subunit of type IV pili, PilA. Differential expression of genes involved in various cellular functions was identified, and we selected the gene encoding the transcription factor interferon regulatory factor 1 (IRF-1) for further analysis. The levels of the IRF-1 transcript increased 3- to 4-fold in A549 cells after adherence by P. aeruginosa. A similar increase of IRF-1 mRNA was observed in A549 cells exposed to wild-type P. aeruginosa when compared to an isogenic, nonpiliated strain. However, this difference was abolished when serum was present during the incubation of bacteria. Exposure of A549 cells to purified P. aeruginosa lipopolysaccharide did not result in a significant increase in IRF-1 mRNA. Although the P. aeruginosa-induced increased IRF-1 expression depends on the presence of bacterial adhesin, our findings do not preclude the possibility that other bacterial products are responsible for IRF-1 activation, which is enhanced by bacterial adherence to cells. These data show that microarray technology can be an important tool for studying the complex interplay between bacterial pathogens and host.

Gene expression in Pseudomonas aeruginosa biofilms.

Bacteria often adopt a sessile biofilm lifestyle that is resistant to antimicrobial treatment. Opportunistic pathogenic bacteria like Pseudomonas aeruginosa can develop persistent infections. To gain insights into the differences between free-living P. aeruginosa cells and those in biofilms, and into the mechanisms underlying the resistance of biofilms to antibiotics, we used DNA microarrays. Here we show that, despite the striking differences in lifestyles, only about 1% of genes showed differential expression in the two growth modes; about 0.5% of genes were activated and about 0.5% were repressed in biofilms. Some of the regulated genes are known to affect antibiotic sensitivity of free-living P. aeruginosa. Exposure of biofilms to high levels of the antibiotic tobramycin caused differential expression of 20 genes. We propose that this response is critical for the development of biofilm resistance to tobramycin. Our results show that gene expression in biofilm cells is similar to that in free-living cells but there are a small number of significant differences. Our identification of biofilm-regulated genes points to mechanisms of biofilm resistance to antibiotics.

An expressed-sequence-tag database of the human prostate: sequence analysis of 1168 cDNA clones.

The human prostate is a complex glandular organ with functional development under hormonal regulation. Diseases of the prostate result in significant morbidity and mortality in the form of benign prostatic hypertrophy and prostate adenocarcinoma. The characterization of the molecular framework of the human prostate at the level of expressed genes will facilitate the understanding of normal and pathological prostate biology. The purposes of this study were to acquire an initial assessment of the qualitative and quantitative diversity of gene expression in the normal human prostate and to determine the extent that genes with prostate-restricted expression can be assessed using an expressed sequence tag approach. We have constructed a directional cDNA library from normal adult human prostate tissue and partially sequenced the 5' end of 1168 randomly selected cDNA clones, resulting in more than 400 kb of DNA sequence. Homology searches of the sequenced cDNAs against the GenBank and dbEST databases revealed that 43% of the sequences are identical to human genes whose functions are known, 5% are similar but not identical to known genes in humans or lower organisms, 5% match the mitochondrial genome, 9% are composed of interspersed DNA repeats, 30% are homologous to sequences in the dbEST database without a described function, and 6% are novel sequences. A total of 780 distinct species were identified. In addition to the 74 novel transcripts, 4 genes, prostate-specific antigen (PSA), prostate secretory protein (PSP), prostate acid phosphatase (PAP), and human glandular kallekrein 2 (HK2), have no homologous sequences in the databases that originate from sources other than prostate and thus may represent genes with prostate-restricted expression. Sequences matching PSA, PSP, and PAP each accounted for > 1% of the total ESTs and represent highly abundant transcripts, correlating with the abundance of these proteins in the prostate gland. No novel transcripts were represented by more than one EST and thus are expressed at levels much lower than the known prostate-specific genes.

Large-scale monitoring of host cell gene expression during HIV-1 infection using cDNA microarrays.

Human immunodeficiency virus type 1 (HIV-1) infection alters the expression of host cell genes at both the mRNA and protein levels. To obtain a more comprehensive view of the global effects of HIV infection of CD4-positive T-cells at the mRNA level, we performed cDNA microarray analysis on approximately 1500 cellular cDNAs at 2 and 3 days postinfection (p.i.) with HIV-1. Host cell gene expression changed little at 2 days p.i., but at 3 days p.i. 20 cellular genes were identified as differentially expressed. Genes involved in T-cell signaling, subcellular trafficking, and transcriptional regulation, as well as several uncharacterized genes, were among those whose mRNAs were differentially regulated. These results support the hypothesis that HIV-1 infection alters expression of a broad array of cellular genes and provides a framework for future functional studies on the differentially expressed mRNA products.

Snapshot of a large dynamic replicon in a halophilic archaeon: megaplasmid or minichromosome?

Extremely halophilic archaea, which flourish in hypersaline environments, are known to contain a variety of large dynamic replicons. Previously, the analysis of one such replicon, pNRC100, in Halobacterium sp. strain NRC-1, showed that it undergoes high-frequency insertion sequence (IS) element-mediated insertions and deletions, as well as inversions via recombination between 39-kb-long inverted repeats (IRs). Now, the complete sequencing of pNRC100, a 191,346-bp circle, has shown the presence of 27 IS elements representing eight families. A total of 176 ORFs or likely genes of 850-bp average size were found, 39 of which were repeated within the large IRs. More than one-half of the ORFs are likely to represent novel genes that have no known homologs in the databases. Among ORFs with previously characterized homologs, three different copies of putative plasmid replication and four copies of partitioning genes were found, suggesting that pNRC100 evolved from IS element-mediated fusions of several smaller plasmids. Consistent with this idea, putative genes typically found on plasmids, including those encoding a restriction-modification system and arsenic resistance, as well as buoyant gas-filled vesicles and a two-component regulatory system, were found on pNRC100. However, additional putative genes not expected on an extrachromosomal element, such as those encoding an electron transport chain cytochrome d oxidase, DNA nucleotide synthesis enzymes thioredoxin and thioredoxin reductase, and eukaryotic-like TATA-binding protein transcription factors and a chromosomal replication initiator protein were also found. A multi-step IS element-mediated process is proposed to account for the acquisition of these chromosomal genes. The finding of essential genes on pNRC100 and its property of resistance to curing suggest that this replicon may be evolving into a new chromosome.