Browsing by Subject "Gene Expression Profiling"

Now showing 1 - 20 of 82

Open Access
A community approach to mortality prediction in sepsis via gene expression analysis.
(Nature communications, 2018-02) Sweeney, Timothy E; Perumal, Thanneer M; Henao, Ricardo; Nichols, Marshall; Howrylak, Judith A; Choi, Augustine M; Bermejo-Martin, Jesús F; Almansa, Raquel; Tamayo, Eduardo; Davenport, Emma E; Burnham, Katie L; Hinds, Charles J; Knight, Julian C; Woods, Christopher W; Kingsmore, Stephen F; Ginsburg, Geoffrey S; Wong, Hector R; Parnell, Grant P; Tang, Benjamin; Moldawer, Lyle L; Moore, Frederick E; Omberg, Larsson; Khatri, Purvesh; Tsalik, Ephraim L; Mangravite, Lara M; Langley, Raymond J
Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance is validated in five cohorts of community-onset sepsis patients in which the models show summary AUROCs ranging from 0.765-0.89. Similar performance is observed in four cohorts of hospital-acquired sepsis. Combining the new gene-expression-based prognostic models with prior clinical severity scores leads to significant improvement in prediction of 30-day mortality as measured via AUROC and net reclassification improvement index These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis.
Open Access
A framework for integrating the songbird brain.
(J Comp Physiol A Neuroethol Sens Neural Behav Physiol, 2002-12) Jarvis, ED; Smith, VA; Wada, K; Rivas, MV; McElroy, M; Smulders, TV; Carninci, P; Hayashizaki, Y; Dietrich, F; Wu, X; McConnell, P; Yu, J; Wang, PP; Hartemink, AJ; Lin, S
Biological systems by default involve complex components with complex relationships. To decipher how biological systems work, we assume that one needs to integrate information over multiple levels of complexity. The songbird vocal communication system is ideal for such integration due to many years of ethological investigation and a discreet dedicated brain network. Here we announce the beginnings of a songbird brain integrative project that involves high-throughput, molecular, anatomical, electrophysiological and behavioral levels of analysis. We first formed a rationale for inclusion of specific biological levels of analysis, then developed high-throughput molecular technologies on songbird brains, developed technologies for combined analysis of electrophysiological activity and gene regulation in awake behaving animals, and developed bioinformatic tools that predict causal interactions within and between biological levels of organization. This integrative brain project is fitting for the interdisciplinary approaches taken in the current songbird issue of the Journal of Comparative Physiology A and is expected to be conducive to deciphering how brains generate and perceive complex behaviors.
Open Access
A molecular neuroethological approach for identifying and characterizing a cascade of behaviorally regulated genes.
(Proc Natl Acad Sci U S A, 2006-10-10) Wada, Kazuhiro; Howard, Jason T; McConnell, Patrick; Whitney, Osceola; Lints, Thierry; Rivas, Miriam V; Horita, Haruhito; Patterson, Michael A; White, Stephanie A; Scharff, Constance; Haesler, Sebastian; Zhao, Shengli; Sakaguchi, Hironobu; Hagiwara, Masatoshi; Shiraki, Toshiyuki; Hirozane-Kishikawa, Tomoko; Skene, Pate; Hayashizaki, Yoshihide; Carninci, Piero; Jarvis, Erich D
Songbirds have one of the most accessible neural systems for the study of brain mechanisms of behavior. However, neuroethological studies in songbirds have been limited by the lack of high-throughput molecular resources and gene-manipulation tools. To overcome these limitations, we constructed 21 regular, normalized, and subtracted full-length cDNA libraries from brains of zebra finches in 57 developmental and behavioral conditions in an attempt to clone as much of the brain transcriptome as possible. From these libraries, approximately 14,000 transcripts were isolated, representing an estimated 4,738 genes. With the cDNAs, we created a hierarchically organized transcriptome database and a large-scale songbird brain cDNA microarray. We used the arrays to reveal a set of 33 genes that are regulated in forebrain vocal nuclei by singing behavior. These genes clustered into four anatomical and six temporal expression patterns. Their functions spanned a large range of cellular and molecular categories, from signal transduction, trafficking, and structural, to synaptically released molecules. With the full-length cDNAs and a lentiviral vector system, we were able to overexpress, in vocal nuclei, proteins of representative singing-regulated genes in the absence of singing. This publicly accessible resource http://songbirdtranscriptome.net can now be used to study molecular neuroethological mechanisms of behavior.
Open Access
A three-dimensional culture system recapitulates placental syncytiotrophoblast development and microbial resistance.
(Science advances, 2016-03-04) McConkey, Cameron A; Delorme-Axford, Elizabeth; Nickerson, Cheryl A; Kim, Kwang Sik; Sadovsky, Yoel; Boyle, Jon P; Coyne, Carolyn B
In eutherians, the placenta acts as a barrier and conduit at the maternal-fetal interface. Syncytiotrophoblasts, the multinucleated cells that cover the placental villous tree surfaces of the human placenta, are directly bathed in maternal blood and are formed by the fusion of progenitor cytotrophoblasts that underlie them. Despite their crucial role in fetal protection, many of the events that govern trophoblast fusion and protection from microbial infection are unknown. We describe a three-dimensional (3D)-based culture model using human JEG-3 trophoblast cells that develop syncytiotrophoblast phenotypes when cocultured with human microvascular endothelial cells. JEG-3 cells cultured in this system exhibit enhanced fusogenic activity and morphological and secretory activities strikingly similar to those of primary human syncytiotrophoblasts. RNASeq analyses extend the observed functional similarities to the transcriptome, where we observed significant overlap between syncytiotrophoblast-specific genes and 3D JEG-3 cultures. Furthermore, JEG-3 cells cultured in 3D are resistant to infection by viruses and Toxoplasma gondii, which mimics the high resistance of syncytiotrophoblasts to microbial infections in vivo. Given that this system is genetically manipulatable, it provides a new platform to dissect the mechanisms involved in syncytiotrophoblast development and microbial resistance.
Open Access
Abnormal oxidative stress responses in fibroblasts from preeclampsia infants.
(PloS one, 2014-01) Yang, Penghua; Dai, Aihua; Alexenko, Andrei P; Liu, Yajun; Stephens, Amanda J; Schulz, Laura C; Schust, Danny J; Roberts, R Michael; Ezashi, Toshihiko
Background
Signs of severe oxidative stress are evident in term placentae of infants born to mothers with preeclampsia (PE), but it is unclear whether this is a cause or consequence of the disease. Here fibroblast lines were established from umbilical cords (UC) delivered by mothers who had experienced early onset PE and from controls with the goal of converting these primary cells to induced pluripotent stem cells and ultimately trophoblast. Contrary to expectations, the oxidative stress responses of these non-placental cells from PE infants were more severe than those from controls.
Methods and findings
Three features suggested that UC-derived fibroblasts from PE infants responded less well to oxidative stressors than controls: 1) While all UC provided outgrowths in 4% O2, success was significantly lower for PE cords in 20% O2; 2) PE lines established in 4% O2 proliferated more slowly than controls when switched to 20% O2; 3) PE lines were more susceptible to the pro-oxidants diethylmaleate and tert-butylhydroquinone than control lines, but, unlike controls, were not protected by glutathione. Transcriptome profiling revealed only a few genes differentially regulated between PE lines and controls in 4% O2 conditions. However, a more severely stressed phenotype than controls, particularly in the unfolded protein response, was evident when PE lines were switched suddenly to 20% O2, thus confirming the greater sensitivity of the PE fibroblasts to acute changes in oxidative stress.
Conclusions
UC fibroblasts derived from PE infants are intrinsically less able to respond to acute oxidative stress than controls, and this phenotype is retained over many cell doublings. Whether the basis of this vulnerability is genetic or epigenetic and how it pertains to trophoblast development remains unclear, but this finding may provide a clue to the basis of the early onset, usually severe, form of PE.
Open Access
Advances to Bayesian network inference for generating causal networks from observational biological data.
(Bioinformatics, 2004-12-12) Yu, Jing; Smith, V Anne; Wang, Paul P; Hartemink, Alexander J; Jarvis, Erich D
MOTIVATION: Network inference algorithms are powerful computational tools for identifying putative causal interactions among variables from observational data. Bayesian network inference algorithms hold particular promise in that they can capture linear, non-linear, combinatorial, stochastic and other types of relationships among variables across multiple levels of biological organization. However, challenges remain when applying these algorithms to limited quantities of experimental data collected from biological systems. Here, we use a simulation approach to make advances in our dynamic Bayesian network (DBN) inference algorithm, especially in the context of limited quantities of biological data. RESULTS: We test a range of scoring metrics and search heuristics to find an effective algorithm configuration for evaluating our methodological advances. We also identify sampling intervals and levels of data discretization that allow the best recovery of the simulated networks. We develop a novel influence score for DBNs that attempts to estimate both the sign (activation or repression) and relative magnitude of interactions among variables. When faced with limited quantities of observational data, combining our influence score with moderate data interpolation reduces a significant portion of false positive interactions in the recovered networks. Together, our advances allow DBN inference algorithms to be more effective in recovering biological networks from experimentally collected data. AVAILABILITY: Source code and simulated data are available upon request. SUPPLEMENTARY INFORMATION: http://www.jarvislab.net/Bioinformatics/BNAdvances/
Open Access
Assessing the utility of thermodynamic features for microRNA target prediction under relaxed seed and no conservation requirements.
(PLoS One, 2011) Lekprasert, Parawee; Mayhew, Michael; Ohler, Uwe
BACKGROUND: Many computational microRNA target prediction tools are focused on several key features, including complementarity to 5'seed of miRNAs and evolutionary conservation. While these features allow for successful target identification, not all miRNA target sites are conserved and adhere to canonical seed complementarity. Several studies have propagated the use of energy features of mRNA:miRNA duplexes as an alternative feature. However, different independent evaluations reported conflicting results on the reliability of energy-based predictions. Here, we reassess the usefulness of energy features for mammalian target prediction, aiming to relax or eliminate the need for perfect seed matches and conservation requirement. METHODOLOGY/PRINCIPAL FINDINGS: We detect significant differences of energy features at experimentally supported human miRNA target sites and at genome-wide sites of AGO protein interaction. This trend is confirmed on datasets that assay the effect of miRNAs on mRNA and protein expression changes, and a simple linear regression model leads to significant correlation of predicted versus observed expression change. Compared to 6-mer seed matches as baseline, application of our energy-based model leads to ∼3-5-fold enrichment on highly down-regulated targets, and allows for prediction of strictly imperfect targets with enrichment above baseline. CONCLUSIONS/SIGNIFICANCE: In conclusion, our results indicate significant promise for energy-based miRNA target prediction that includes a broader range of targets without having to use conservation or impose stringent seed match rules.
Open Access
Automatic annotation of spatial expression patterns via sparse Bayesian factor models.
(PLoS Comput Biol, 2011-07) Pruteanu-Malinici, Iulian; Mace, Daniel L; Ohler, Uwe
Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D-4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions.
Open Access
Biology of intracranial aneurysms: role of inflammation.
(Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 2012-09) Chalouhi, Nohra; Ali, Muhammad S; Jabbour, Pascal M; Tjoumakaris, Stavropoula I; Gonzalez, L Fernando; Rosenwasser, Robert H; Koch, Walter J; Dumont, Aaron S
Intracranial aneurysms (IAs) linger as a potentially devastating clinical problem. Despite intense investigation, our understanding of the mechanisms leading to aneurysm development, progression and rupture remain incompletely defined. An accumulating body of evidence implicates inflammation as a critical contributor to aneurysm pathogenesis. Intracranial aneurysm formation and progression appear to result from endothelial dysfunction, a mounting inflammatory response, and vascular smooth muscle cell phenotypic modulation producing a pro-inflammatory phenotype. A later final common pathway appears to involve apoptosis of cellular constituents of the vessel wall. These changes result in degradation of the integrity of the vascular wall leading to aneurysmal dilation, progression and eventual rupture in certain aneurysms. Various aspects of the inflammatory response have been investigated as contributors to IA pathogenesis including leukocytes, complement, immunoglobulins, cytokines, and other humoral mediators. Furthermore, gene expression profiling of IA compared with control arteries has prominently featured differential expression of genes involved with immune response/inflammation. Preliminary data suggest that therapies targeting the inflammatory response may have efficacy in the future treatment of IA. Further investigation, however, is necessary to elucidate the precise role of inflammation in IA pathogenesis, which can be exploited to improve the prognosis of patients harboring IA.
Open Access
Bringing chemistry to life.
(Nature methods, 2011-07-28) Boyce, Michael; Bertozzi, Carolyn R
Open Access
Chiropteran types I and II interferon genes inferred from genome sequencing traces by a statistical gene-family assembler.
(BMC Genomics, 2010-07-21) Kepler, Thomas B; Sample, Christopher; Hudak, Kathryn; Roach, Jeffrey; Haines, Albert; Walsh, Allyson; Ramsburg, Elizabeth A
BACKGROUND: The rate of emergence of human pathogens is steadily increasing; most of these novel agents originate in wildlife. Bats, remarkably, are the natural reservoirs of many of the most pathogenic viruses in humans. There are two bat genome projects currently underway, a circumstance that promises to speed the discovery host factors important in the coevolution of bats with their viruses. These genomes, however, are not yet assembled and one of them will provide only low coverage, making the inference of most genes of immunological interest error-prone. Many more wildlife genome projects are underway and intend to provide only shallow coverage. RESULTS: We have developed a statistical method for the assembly of gene families from partial genomes. The method takes full advantage of the quality scores generated by base-calling software, incorporating them into a complete probabilistic error model, to overcome the limitation inherent in the inference of gene family members from partial sequence information. We validated the method by inferring the human IFNA genes from the genome trace archives, and used it to infer 61 type-I interferon genes, and single type-II interferon genes in the bats Pteropus vampyrus and Myotis lucifugus. We confirmed our inferences by direct cloning and sequencing of IFNA, IFNB, IFND, and IFNK in P. vampyrus, and by demonstrating transcription of some of the inferred genes by known interferon-inducing stimuli. CONCLUSION: The statistical trace assembler described here provides a reliable method for extracting information from the many available and forthcoming partial or shallow genome sequencing projects, thereby facilitating the study of a wider variety of organisms with ecological and biomedical significance to humans than would otherwise be possible.
Open Access
Comparative genomics based on massive parallel transcriptome sequencing reveals patterns of substitution and selection across 10 bird species.
(Mol Ecol, 2010-03) Künstner, Axel; Wolf, Jochen BW; Backström, Niclas; Whitney, Osceola; Balakrishnan, Christopher N; Day, Lainy; Edwards, Scott V; Janes, Daniel E; Schlinger, Barney A; Wilson, Richard K; Jarvis, Erich D; Warren, Wesley C; Ellegren, Hans
Next-generation sequencing technology provides an attractive means to obtain large-scale sequence data necessary for comparative genomic analysis. To analyse the patterns of mutation rate variation and selection intensity across the avian genome, we performed brain transcriptome sequencing using Roche 454 technology of 10 different non-model avian species. Contigs from de novo assemblies were aligned to the two available avian reference genomes, chicken and zebra finch. In total, we identified 6499 different genes across all 10 species, with approximately 1000 genes found in each full run per species. We found evidence for a higher mutation rate of the Z chromosome than of autosomes (male-biased mutation) and a negative correlation between the neutral substitution rate (d(S)) and chromosome size. Analyses of the mean d(N)/d(S) ratio (omega) of genes across chromosomes supported the Hill-Robertson effect (the effect of selection at linked loci) and point at stochastic problems with omega as an independent measure of selection. Overall, this study demonstrates the usefulness of next-generation sequencing for obtaining genomic resources for comparative genomic analysis of non-model organisms.
Open Access
Comparative genomics reveals molecular features unique to the songbird lineage.
(BMC Genomics, 2014-12-13) Wirthlin, Morgan; Lovell, Peter V; Jarvis, Erich D; Mello, Claudio V
BACKGROUND: Songbirds (oscine Passeriformes) are among the most diverse and successful vertebrate groups, comprising almost half of all known bird species. Identifying the genomic innovations that might be associated with this success, as well as with characteristic songbird traits such as vocal learning and the brain circuits that underlie this behavior, has proven difficult, in part due to the small number of avian genomes available until recently. Here we performed a comparative analysis of 48 avian genomes to identify genomic features that are unique to songbirds, as well as an initial assessment of function by investigating their tissue distribution and predicted protein domain structure. RESULTS: Using BLAT alignments and gene synteny analysis, we curated a large set of Ensembl gene models that were annotated as novel or duplicated in the most commonly studied songbird, the Zebra finch (Taeniopygia guttata), and then extended this analysis to 47 additional avian and 4 non-avian genomes. We identified 10 novel genes uniquely present in songbird genomes. A refined map of chromosomal synteny disruptions in the Zebra finch genome revealed that the majority of these novel genes localized to regions of genomic instability associated with apparent chromosomal breakpoints. Analyses of in situ hybridization and RNA-seq data revealed that a subset of songbird-unique genes is expressed in the brain and/or other tissues, and that 2 of these (YTHDC2L1 and TMRA) are highly differentially expressed in vocal learning-associated nuclei relative to the rest of the brain. CONCLUSIONS: Our study reveals novel genes unique to songbirds, including some that may subserve their unique vocal control system, substantially improves the quality of Zebra finch genome annotations, and contributes to a better understanding of how genomic features may have evolved in conjunction with the emergence of the songbird lineage.
Open Access
Comprehensive gene expression profiling and immunohistochemical studies support application of immunophenotypic algorithm for molecular subtype classification in diffuse large B-cell lymphoma: a report from the International DLBCL Rituximab-CHOP Consortium Program Study.
(Leukemia, 2012-09) Visco, C; Li, Y; Xu-Monette, ZY; Miranda, RN; Green, TM; Li, Y; Tzankov, A; Wen, W; Liu, W-M; Kahl, BS; d'Amore, ESG; Montes-Moreno, S; Dybkær, K; Chiu, A; Tam, W; Orazi, A; Zu, Y; Bhagat, G; Winter, JN; Wang, H-Y; O'Neill, S; Dunphy, CH; Hsi, ED; Zhao, XF; Go, RS; Choi, WWL; Zhou, F; Czader, M; Tong, J; Zhao, X; van Krieken, JH; Huang, Q; Ai, W; Etzell, J; Ponzoni, M; Ferreri, AJM; Piris, MA; Møller, MB; Bueso-Ramos, CE; Medeiros, LJ; Wu, L; Young, KH
Gene expression profiling (GEP) has stratified diffuse large B-cell lymphoma (DLBCL) into molecular subgroups that correspond to different stages of lymphocyte development-namely germinal center B-cell like and activated B-cell like. This classification has prognostic significance, but GEP is expensive and not readily applicable into daily practice, which has lead to immunohistochemical algorithms proposed as a surrogate for GEP analysis. We assembled tissue microarrays from 475 de novo DLBCL patients who were treated with rituximab-CHOP chemotherapy. All cases were successfully profiled by GEP on formalin-fixed, paraffin-embedded tissue samples. Sections were stained with antibodies reactive with CD10, GCET1, FOXP1, MUM1 and BCL6 and cases were classified following a rationale of sequential steps of differentiation of B cells. Cutoffs for each marker were obtained using receiver-operating characteristic curves, obviating the need for any arbitrary method. An algorithm based on the expression of CD10, FOXP1 and BCL6 was developed that had a simpler structure than other recently proposed algorithms and 92.6% concordance with GEP. In multivariate analysis, both the International Prognostic Index and our proposed algorithm were significant independent predictors of progression-free and overall survival. In conclusion, this algorithm effectively predicts prognosis of DLBCL patients matching GEP subgroups in the era of rituximab therapy.
Open Access
Coordinated activation of candidate proto-oncogenes and cancer testes antigens via promoter demethylation in head and neck cancer and lung cancer.
(PLoS One, 2009) Smith, Ian M; Glazer, Chad A; Mithani, Suhail K; Ochs, Michael F; Sun, Wenyue; Bhan, Sheetal; Vostrov, Alexander; Abdullaev, Ziedulla; Lobanenkov, Victor; Gray, Andrew; Liu, Chunyan; Chang, Steven S; Ostrow, Kimberly L; Westra, William H; Begum, Shahnaz; Dhara, Mousumi; Califano, Joseph
BACKGROUND: Epigenetic alterations have been implicated in the pathogenesis of solid tumors, however, proto-oncogenes activated by promoter demethylation have been sporadically reported. We used an integrative method to analyze expression in primary head and neck squamous cell carcinoma (HNSCC) and pharmacologically demethylated cell lines to identify aberrantly demethylated and expressed candidate proto-oncogenes and cancer testes antigens in HNSCC. METHODOLOGY/PRINCIPAL FINDINGS: We noted coordinated promoter demethylation and simultaneous transcriptional upregulation of proto-oncogene candidates with promoter homology, and phylogenetic footprinting of these promoters demonstrated potential recognition sites for the transcription factor BORIS. Aberrant BORIS expression correlated with upregulation of candidate proto-oncogenes in multiple human malignancies including primary non-small cell lung cancers and HNSCC, induced coordinated proto-oncogene specific promoter demethylation and expression in non-tumorigenic cells, and transformed NIH3T3 cells. CONCLUSIONS/SIGNIFICANCE: Coordinated, epigenetic unmasking of multiple genes with growth promoting activity occurs in aerodigestive cancers, and BORIS is implicated in the coordinated promoter demethylation and reactivation of epigenetically silenced genes in human cancers.
Open Access
Cryptococcus neoformans Rim101 is associated with cell wall remodeling and evasion of the host immune responses.
(mBio, 2013-01) O'Meara, Teresa R; Holmer, Stephanie M; Selvig, Kyla; Dietrich, Fred; Alspaugh, J Andrew
Unlabelled
Infectious microorganisms often play a role in modulating the immune responses of their infected hosts. We demonstrate that Cryptococcus neoformans signals through the Rim101 transcription factor to regulate cell wall composition and the host-pathogen interface. In the absence of Rim101, C. neoformans exhibits an altered cell surface in response to host signals, generating an excessive and ineffective immune response that results in accelerated host death. This host immune response to the rim101Δ mutant strain is characterized by increased neutrophil influx into the infected lungs and an altered pattern of host cytokine expression compared to the response to wild-type cryptococcal infection. To identify genes associated with the observed phenotypes, we performed whole-genome RNA sequencing experiments under capsule-inducing conditions. We defined the downstream regulon of the Rim101 transcription factor and determined potential cell wall processes involved in the capsule attachment defects and altered mechanisms of virulence in the rim101Δ mutant. The cell wall generates structural stability for the cell and allows the attachment of surface molecules such as capsule polysaccharides. In turn, the capsule provides an effective mask for the immunogenic cell wall, shielding it from recognition by the host immune system.
Importance
Cryptococcus neoformans is an opportunistic human pathogen that is a significant cause of death in immunocompromised individuals. There are two major causes of death due to this pathogen: meningitis due to uncontrolled fungal proliferation in the brain in the face of a weakened immune system and immune reconstitution inflammatory syndrome characterized by an overactive immune response to subclinical levels of the pathogen. In this study, we examined how C. neoformans uses the conserved Rim101 transcription factor to specifically remodel the host-pathogen interface, thus regulating the host immune response. These studies explored the complex ways in which successful microbial pathogens induce phenotypes that ensure their own survival while simultaneously controlling the nature and degree of the associated host response.
Open Access
Detecting separate time scales in genetic expression data.
(BMC Genomics, 2010-06-16) Orlando, David A; Brady, Siobhan M; Fink, Thomas MA; Benfey, Philip N; Ahnert, Sebastian E
BACKGROUND: Biological processes occur on a vast range of time scales, and many of them occur concurrently. As a result, system-wide measurements of gene expression have the potential to capture many of these processes simultaneously. The challenge however, is to separate these processes and time scales in the data. In many cases the number of processes and their time scales is unknown. This issue is particularly relevant to developmental biologists, who are interested in processes such as growth, segmentation and differentiation, which can all take place simultaneously, but on different time scales. RESULTS: We introduce a flexible and statistically rigorous method for detecting different time scales in time-series gene expression data, by identifying expression patterns that are temporally shifted between replicate datasets. We apply our approach to a Saccharomyces cerevisiae cell-cycle dataset and an Arabidopsis thaliana root developmental dataset. In both datasets our method successfully detects processes operating on several different time scales. Furthermore we show that many of these time scales can be associated with particular biological functions. CONCLUSIONS: The spatiotemporal modules identified by our method suggest the presence of multiple biological processes, acting at distinct time scales in both the Arabidopsis root and yeast. Using similar large-scale expression datasets, the identification of biological processes acting at multiple time scales in many organisms is now possible.
Restricted
Diagnosis of partial body radiation exposure in mice using peripheral blood gene expression profiles.
(PLoS One, 2010-07-12) Meadows, Sarah K; Dressman, Holly K; Daher, Pamela; Himburg, Heather; Russell, J Lauren; Doan, Phuong; Chao, Nelson J; Lucas, Joseph; Nevins, Joseph R; Chute, John P
In the event of a terrorist-mediated attack in the United States using radiological or improvised nuclear weapons, it is expected that hundreds of thousands of people could be exposed to life-threatening levels of ionizing radiation. We have recently shown that genome-wide expression analysis of the peripheral blood (PB) can generate gene expression profiles that can predict radiation exposure and distinguish the dose level of exposure following total body irradiation (TBI). However, in the event a radiation-mass casualty scenario, many victims will have heterogeneous exposure due to partial shielding and it is unknown whether PB gene expression profiles would be useful in predicting the status of partially irradiated individuals. Here, we identified gene expression profiles in the PB that were characteristic of anterior hemibody-, posterior hemibody- and single limb-irradiation at 0.5 Gy, 2 Gy and 10 Gy in C57Bl6 mice. These PB signatures predicted the radiation status of partially irradiated mice with a high level of accuracy (range 79-100%) compared to non-irradiated mice. Interestingly, PB signatures of partial body irradiation were poorly predictive of radiation status by site of injury (range 16-43%), suggesting that the PB molecular response to partial body irradiation was anatomic site specific. Importantly, PB gene signatures generated from TBI-treated mice failed completely to predict the radiation status of partially irradiated animals or non-irradiated controls. These data demonstrate that partial body irradiation, even to a single limb, generates a characteristic PB signature of radiation injury and thus may necessitate the use of multiple signatures, both partial body and total body, to accurately assess the status of an individual exposed to radiation.
Open Access
Discrimination of vanadium from zinc using gene profiling in human bronchial epithelial cells.
(Environmental health perspectives, 2005-12) Li, Zhuowei; Stonehuerner, Jackie; Devlin, Robert B; Huang, Yuh-Chin T
We hypothesized that gene expression profiling may discriminate vanadium from zinc in human bronchial epithelial cells (HBECs). RNA from HBECs exposed to vehicle, V (50 microM), or Zn (50 microM) for 4 hr (n = 4 paired experiments) was hybridized to Affymetrix Hu133A chips. Using one-class t-test with p < 0.01, we identified 140 and 76 genes with treatment:control ratios > or = 2.0 or < or = 0.5 for V and Zn, respectively. We then categorized these genes into functional pathways and compared the number of genes in each pathway between V and Zn using Fisher's exact test. Three pathways regulating gene transcription, inflammatory response, and cell proliferation distinguished V from Zn. When genes in these three pathways were matched with the 163 genes flagged by the same statistical filtration for V:Zn ratios, 12 genes were identified. The hierarchical clustering analysis showed that these 12 genes discriminated V from Zn and consisted of two clusters. Cluster 1 genes (ZBTB1, PML, ZNF44, SIX1, BCL6, ZNF450) were down-regulated by V and involved in gene transcription, whereas cluster 2 genes (IL8, IL1A, PTGS2, DTR, TNFAIP3, CXCL3) were up-regulated and linked to inflammatory response and cell proliferation. Also, metallothionein 1 genes (MT1F, MT1G, MT1K) were up-regulated by Zn only. Thus, using microarray analysis, we identified a small set of genes that may be used as biomarkers for discriminating V from Zn. The novel genes and pathways identified by the microarray may help us understand the pathogenesis of health effects caused by environmental V and Zn exposure.
Open Access
Dose-dependent expression of claudin-5 is a modifying factor in schizophrenia.
(Molecular psychiatry, 2018-11) Greene, C; Kealy, J; Humphries, MM; Gong, Y; Hou, J; Hudson, N; Cassidy, LM; Martiniano, R; Shashi, V; Hooper, SR; Grant, GA; Kenna, PF; Norris, K; Callaghan, CK; Islam, M dN; O'Mara, SM; Najda, Z; Campbell, SG; Pachter, JS; Thomas, J; Williams, NM; Humphries, P; Murphy, KC; Campbell, M
Schizophrenia is a neurodevelopmental disorder that affects up to 1% of the general population. Various genes show associations with schizophrenia and a very weak nominal association with the tight junction protein, claudin-5, has previously been identified. Claudin-5 is expressed in endothelial cells forming part of the blood-brain barrier (BBB). Furthermore, schizophrenia occurs in 30% of individuals with 22q11 deletion syndrome (22q11DS), a population who are haploinsufficient for the claudin-5 gene. Here, we show that a variant in the claudin-5 gene is weakly associated with schizophrenia in 22q11DS, leading to 75% less claudin-5 being expressed in endothelial cells. We also show that targeted adeno-associated virus-mediated suppression of claudin-5 in the mouse brain results in localized BBB disruption and behavioural changes. Using an inducible 'knockdown' mouse model, we further link claudin-5 suppression with psychosis through a distinct behavioural phenotype showing impairments in learning and memory, anxiety-like behaviour and sensorimotor gating. In addition, these animals develop seizures and die after 3-4 weeks of claudin-5 suppression, reinforcing the crucial role of claudin-5 in normal neurological function. Finally, we show that anti-psychotic medications dose-dependently increase claudin-5 expression in vitro and in vivo while aberrant, discontinuous expression of claudin-5 in the brains of schizophrenic patients post mortem was observed compared to age-matched controls. Together, these data suggest that BBB disruption may be a modifying factor in the development of schizophrenia and that drugs directly targeting the BBB may offer new therapeutic opportunities for treating this disorder.

Browsing by Subject "Gene Expression Profiling"

Background

Methods and findings

Conclusions

Unlabelled

Importance