Tissue differences revealed by gene expression profiles of various cell lines

Mechanisms through which tissues are formed and maintained remain unknown but are fundamental aspects in biology. Tissue-specific gene expression is a valuable tool to study such mechanisms. But in many biomedical studies, cell lines, rather than human body tissues, are used to investigate biological mechanisms Whether or not cell lines maintain their tissue-specific characteristics after they are isolated and cultured outside the human body remains to be explored. In this study, we applied a novel computational method to identify core genes that contribute to the differentiation of cell lines from various tissues. Several advanced computational techniques, such as Monte Carlo feature selection method, incremental feature selection method, and support vector machine (SVM) algorithm, were incorporated in the proposed method, which extensively analyzed the gene expression profiles of cell lines from different tissues. As a result, we extracted a group of functional genes that can indicate the differences of cell lines in different tissues and built an optimal SVM classifier for identifying cell lines in different tissues. In addition, a set of rules for classifying cell lines were also reported, which can give a clearer picture of cell lines in different issues although its performance was not better than the optimal SVM classifier. Finally, we compared such genes with the tissue-specific genes identified by the Genotype-tissue Expression project. Results showed that most expression patterns between tissues remained in the derived cell lines despite some uniqueness that some genes show tissue specificity.     

Arabidopsis gene expression changes during cyst nematode parasitism revealed by statistical analyses of microarray expression profiles

With the availability of microarray technology, the expression profiles of thousands of genes can be monitored simultaneously to help determine the mechanisms of these biological processes. We conducted Affymetrix GeneChip microarray analyses of the Arabidopsis-cyst nematode interaction and employed a statistical procedure to analyze the resultant data, which allowed us to identify significant gene expression changes. Quantitative real-time RT-PCR assays were used to confirm the microarray analyses. The results of the expression profiling revealed 128 genes with altered steady-state mRNA levels following infection by the sugar beet cyst nematode (Heterodera schachtii; BCN), in contrast to only 12 genes that had altered expression following infection by the soybean cyst nematode (H. glycines; SCN). The expression of these 12 genes also changed following infection by BCN, i.e. we did not identify any genes regulated exclusively by SCN. The identification of 116 genes whose expression changes during successful cyst nematode parasitism by BCN suggests a potential involvement of these genes in the infection events starting with successful syncytium induction. Further characterization of these genes will permit the formulation of testable hypotheses to explain successful cyst nematode parasitism.     

Associations between HIV and human pathways revealed by protein-protein interactions and correlated gene expression profiles

Background

AIDS is one of the most devastating diseases in human history. Decades of studies have revealed host factors required for HIV infection, indicating that HIV exploits host processes for its own purposes. HIV infection leads to AIDS as well as various comorbidities. The associations between HIV and human pathways and diseases may reveal non-obvious relationships between HIV and non-HIV-defining diseases.

Principal Findings

Human biological pathways were evaluated and statistically compared against the presence of HIV host factor related genes. All of the obtained scores comparing HIV targeted genes and biological pathways were ranked. Different rank results based on overlapping genes, recovered virus-host interactions, co-expressed genes, and common interactions in human protein-protein interaction networks were obtained. Correlations between rankings suggested that these measures yielded diverse rankings. Rank combination of these ranks led to a final ranking of HIV-associated pathways, which revealed that HIV is associated with immune cell-related pathways and several cancer-related pathways. The proposed method is also applicable to the evaluation of associations between other pathogens and human pathways and diseases.

Conclusions

Our results suggest that HIV infection shares common molecular mechanisms with certain signaling pathways and cancers. Interference in apoptosis pathways and the long-term suppression of immune system functions by HIV infection might contribute to tumorigenesis. Relationships between HIV infection and human pathways of disease may aid in the identification of common drug targets for viral infections and other diseases.     

Seasonal dynamics of prokaryotes and their associations with diatoms in the Southern Ocean as revealed by an autonomous sampler

The Southern Ocean remains one of the least explored marine environments. The investigation of temporal microbial dynamics has thus far been hampered by the limited access to this remote ocean. We present here high-resolution seasonal observations of the prokaryotic community composition during phytoplankton blooms induced by natural iron fertilization. A total of 18 seawater samples were collected by a moored remote autonomous sampler over 4 months at 5–11 day intervals in offshore surface waters (central Kerguelen Plateau). Illumina sequencing of the 16S rRNA gene revealed that among the most abundant amplicon sequence variants, SAR92 and Aurantivirga were the first bloom responders, Pseudomonadaceae, Nitrincolaceae and Polaribacter had successive peaks during the spring bloom decline, and Amylibacter increased in relative abundance later in the season. SAR11 and SUP05 were abundant prior to and after the blooms. Using network analysis, we identified two groups of diatoms representative of the spring and summer bloom that had opposite correlation patterns with prokaryotic taxa. Our study provides the first seasonal picture of microbial community dynamics in the open Southern Ocean and thereby offers biological insights to the cycling of carbon and iron, and to an important puzzling issue that is the modest nitrate decrease associated to iron fertilization.     

Mining gene expression profiles: expression signatures as cancer phenotypes

Many examples highlight the power of gene expression profiles, or signatures, to inform an understanding of biological phenotypes. This is perhaps best seen in the context of cancer, where expression signatures have tremendous power to identify new subtypes and to predict clinical outcomes. Although the ability to interpret the meaning of the individual genes in these signatures remains a challenge, this does not diminish the power of the signature to characterize biological states. The use of these signatures as surrogate phenotypes has been particularly important, linking diverse experimental systems that dissect the complexity of biological systems with the in vivo setting in a way that was not previously feasible.     

Topology of gene expression networks as revealed by data mining and modeling

MOTIVATION: Interpretation of high-throughput gene expression profiling requires a knowledge of the design principles underlying the networks that sustain cellular machinery. Recently a novel approach based on the study of network topologies has been proposed. This methodology has proven to be useful for the analysis of a variety of biological systems, including metabolic networks, networks of protein-protein interactions, and gene networks that can be derived from gene expression data. In the present paper, we focus on several important issues related to the topology of gene expression networks that have not yet been fully studied. RESULTS: The networks derived from gene expression profiles for both time series experiments in yeast and perturbation experiments in cell lines are studied. We demonstrate that independent from the experimental organism (yeast versus cell lines) and the type of experiment (time courses versus perturbations) the extracted networks have similar topological characteristics suggesting together with the results of other common principles of the structural organization of biological networks. A novel computational model of network growth that reproduces the basic design principles of the observed networks is presented. Advantage of the model is that it provides a general mechanism to generate networks with different types of topology by a variation of a few parameters. We investigate the robustness of the network structure to random damages and to deliberate removal of the most important parts of the system and show a surprising tolerance of gene expression networks to both kinds of disturbance.     

Pathways activated during human asthma exacerbation as revealed by gene expression patterns in blood

Background

Asthma exacerbations remain a major unmet clinical need. The difficulty in obtaining airway tissue and bronchoalveolar lavage samples during exacerbations has greatly hampered study of naturally occurring exacerbations. This study was conducted to determine if mRNA profiling of peripheral blood mononuclear cells (PBMCs) could provide information on the systemic molecular pathways involved during asthma exacerbations.

Methodology/Principal Findings

Over the course of one year, gene expression levels during stable asthma, exacerbation, and two weeks after an exacerbation were compared using oligonucleotide arrays. For each of 118 subjects who experienced at least one asthma exacerbation, the gene expression patterns in a sample of peripheral blood mononuclear cells collected during an exacerbation episode were compared to patterns observed in multiple samples from the same subject collected during quiescent asthma. Analysis of covariance identified genes whose levels of expression changed during exacerbations and returned to quiescent levels by two weeks. Heterogeneity among visits in expression profiles was examined using K-means clustering. Three distinct exacerbation-associated gene expression signatures were identified. One signature indicated that, even among patients without symptoms of respiratory infection, genes of innate immunity were activated. Antigen-independent T cell activation mediated by IL15 was also indicated by this signature. A second signature revealed strong evidence of lymphocyte activation through antigen receptors and subsequent downstream events of adaptive immunity. The number of genes identified in the third signature was too few to draw conclusions on the mechanisms driving those exacerbations.

Conclusions/Significance

This study has shown that analysis of PBMCs reveals systemic changes accompanying asthma exacerbation and has laid the foundation for future comparative studies using PBMCs.     

Seasonal shifts in Fe-acquisition strategies in Southern Ocean microbial communities revealed by metagenomics and autonomous sampling

Iron (Fe) governs the cycling of organic carbon in large parts of the Southern Ocean. The strategies of diverse microbes to acquire the different chemical forms of Fe under seasonally changing organic carbon regimes remain, however, poorly understood. Here, we report high-resolution seasonal metagenomic observations from the region off Kerguelen Island (Indian Sector of the Southern Ocean) where natural Fe-fertilization induces consecutive spring and summer phytoplankton blooms. Our data illustrate pronounced, but distinct seasonal patterns in the abundance of genes implicated in the transport of different forms of Fe and organic substrates, of siderophore biosynthesis and carbohydrate-active enzymes. The seasonal dynamics suggest a temporal decoupling in the prokaryotic requirements of Fe and organic carbon during the spring phytoplankton bloom and a concerted access to these resources after the summer bloom. Taxonomic assignments revealed differences in the prokaryotic groups harbouring genes of a given Fe-related category and pronounced seasonal successions were observed. Using MAGs we could decipher the respective Fe- and organic substrate-related genes of individual taxa assigned to abundant groups. The ecological strategies related to Fe-acquisition provide insights on how this element could shape microbial community composition with potential implications on organic matter transformations in the Southern Ocean.     

Kaposi's sarcoma-associated herpesvirus latent and lytic gene expression as revealed by DNA arrays

Kaposi's sarcoma-associated herpesvirus (KSHV; human herpesvirus 8) is associated with three human tumors, Kaposi's sarcoma, primary effusion lymphoma (PEL), and multicentric Castleman's disease. KSHV encodes a number of homologs of cellular proteins involved in the cell cycle, signal transduction, and modulation of the host immune response. Of the virus complement of over 85 open reading frames (ORFs), the expression of only a minority has been characterized individually. We have constructed a nylon membrane-based DNA array which allows the expression of almost every ORF of KSHV to be measured simultaneously. A PEL-derived cell line, BC-3, was used to study the expression of KSHV during latency and after the induction of lytic replication. Cluster analysis, which arranges genes according to their expression profile, revealed a correlation between expression and assigned gene function that is consistent with the known stages of the herpesvirus life cycle. Furthermore, latent and lytic genes thought to be functionally related cluster into groups. The correlation between gene expression and function also infers possible roles for KSHV genes yet to be characterized.     

Protein expression profiles in an endosymbiotic cyanobacterium revealed by a proteomic approach

Molecular mechanisms behind adaptations in the cyanobacterium (Nostoc sp.) to a life in endosymbiosis with plants are still not clarified, nor are the interactions between the partners. To get further insights, the proteome of a Nostoc strain, freshly isolated from the symbiotic gland tissue of the angiosperm Gunnera manicata Linden, was analyzed and compared with the proteome of the same strain when free-living. Extracted proteins were separated by two-dimensional gel electrophoresis and were identified by matrix-assisted laser desorption/ionization-time of flight mass spectrometry combined with tandem mass spectrometry. Even when the higher percentage of differentiated cells (heterocysts) in symbiosis was compensated for, the majority of the proteins detected in the symbiotic cyanobacteria were present in the free-living counterpart, indicating that most cellular processes were common for both stages. However, differential expression profiling revealed a significant number of proteins to be down-regulated or missing in the symbiotic stage, while others were more abundant or only expressed in symbiosis. The differential protein expression was primarily connected to i) cell envelope-associated processes, including proteins involved in exopolysaccharide synthesis and surface and membrane associated proteins, ii) to changes in growth and metabolic activities (C and N), including upregulation of nitrogenase and proteins involved in the oxidative pentose phosphate pathway and downregulation of Calvin cycle enzymes, and iii) to the dark, microaerobic conditions offered inside the Gunnera gland cells, including changes in relative phycobiliprotein concentrations. This is the first comprehensive analysis of proteins in the symbiotic state.     

Common gene expression strategies revealed by genome-wide analysis in yeast

Background  

Gene expression is a two-step synthesis process that ends with the necessary amount of each protein required to perform its function. Since the protein is the final product, the main focus of gene regulation should be centered on it. However, because mRNA is an intermediate step and the amounts of both mRNA and protein are controlled by their synthesis and degradation rates, the desired amount of protein can be achieved following different strategies.     

Microbial community adaptation to quaternary ammonium biocides as revealed by metagenomics

Quaternary ammonium compounds (QACs) represent widely used cationic biocides that persist in natural environments. Although microbial degradation, sensitivity and resistance to QACs have been extensively documented, a quantitative understanding of how whole communities adapt to QAC exposure remain elusive. To gain insights into these issues, we exposed a microbial community from a contaminated river sediment to varied levels of benzalkonium chlorides (BACs, a family of QACs) for 3 years. Comparative metagenomic analysis showed that the BAC‐fed communities were dramatically decreased in phylogenetic diversity compared with the control (no BAC exposure), resulting presumably from BAC toxicity, and dominated by Pseudomonas species (> 50% of the total). Time‐course metagenomics revealed that community adaptation occurred primarily via selective enrichment of BAC‐degrading Pseudomonas populations, particularly P. nitroreducens, and secondarily via amino acid substitutions and horizontal transfer of a few selected genes in the Pseudomonas populations, including a gene encoding a PAS/PAC sensor protein and ring‐hydroxylating dioxygenase genes. P. nitroreducens isolates were reproducibly recoverable from communities after prolonged periods of no‐BAC exposure, suggesting that they are robust BAC‐degraders. Our study provides new insights into the mechanisms and tempo of microbial community adaptation to QAC exposure and has implications for treating QACs in biological engineered systems.     

Phophoglucomutase first locus polymorphism as revealed by isoelectric focusing in Southern Africa

Eleven Southern African populations (representing European, Asian and Negroid populations) have been typed for the first locus phosphoglucomutase (PGM1) using isoelectric focusing (pH range 5.0-8.0) in acrylamide gels. The gene frequencies of the four common alleles at this locus in these populations were compared to those found previously in European and Negroid populations. Marked differences in gene frequencies were observed: Negroes have a lower PGM1(2-) compared with Caucasoids due to a lower PGM1(2-) frequency, Indians a relatively high PGM1(2) due to a higher frequency of the PGM1(2+) allele. The Afrikaans and Ashkenazim do not differ appreciably from their European counterparts. The appearances of the rarer PGM1(6) and PGM1(7) alleles on isoelectric focusing are described and some kinetic properties examined. The PGM2(2-1), or 'Atkinson' phenotype, can also be detected with this technique.     

Chromosome-specific spatial periodicities in gene expression revealed by spectral analysis

Recent years have seen an unprecedented surge of research activity in studies of gene expression. This extensive work, however, has been almost uniformly focused on genome-wide gene expression and has largely ignored the fundamental fact that every gene has a specific chromosome location. We propose a novel method of spectral analysis for detecting hidden periodicities in gene expression signals ordered along the length of each chromosome. Using this method, we have discovered that each chromosome in rodents and humans has a unique periodic pattern of gene expression. The uncovered spatial periodicities in gene expression are tissue-specific in the sense that the largest differences in humans were observed between two normal tissues (brain and mammary gland) as well as between their tumor counterparts (glioma and breast cancer). The smallest differences resulted from the comparison of tumors (glioma and breast cancer) with their normal counterparts. All such effects do not extend to all chromosomes but are limited to only some of them. The estimated periods and amplitudes are identical for the genes located on the positive and negative DNA strands. While precise molecular mechanisms of chromosome-specific periodicities in gene expression have yet to be unraveled, their universal presence in different tissues adds another dimension to the current understanding of the genome organization.     

Intergenomic conflict revealed by patterns of sex-biased gene expression

Intergenomic conflict can affect the distribution of genes across eukaryotic genomes. Because the phenotypic optima of males and females often differ, the fitness consequences of newly arisen alleles might not be concordant between the sexes and can be sexually antagonistic--genetic variants favored in one sex are deleterious in the other. In this article, we demonstrate that previously unexplained patterns of sex-biased gene expression in Drosophila melanogaster might have evolved by sexual antagonism, and that the majority of sex-biased expression is due to adaptive changes in males, implying that males experience stronger selection than females.