Visualization of ligand-induced Gi-protein activation in chemotaxing cells.

Cell migration to chemoattractants is critically important in both normal physiology and the pathogenesis of many diseases. In GPCR-mediated chemotaxis, GPCRs transduce the gradient of an extracellular chemotactic ligand into intracellular responses via the activation of heterotrimeric G proteins. However, ligand-induced G-protein activation has not been directly imaged as yet in mammalian chemotaxing cells. We developed a Förster resonance energy transfer (FRET) probe, R10-Gi, by linking the Gi-protein α subunit to the regulator of G-protein signaling domain. The R10-Gi probe was coupled with a chemoattractant leukotriene B4 (LTB4) receptor 1 (BLT1) that induced the receptor to display a high-affinity ligand binding activity (Kd = 0.91 nM) in HEK293 cells. The R10-Gi probe exhibited an increased FRET signal in accord with the LTB4-dependent activation of Gi Furthermore, neutrophil-like differentiated human leukemia cell line 60 that expressed the intrinsic BLT1 displayed temporal Gi-protein activation in an area localized to the leading edge during chemotaxis in a shallow gradient of LTB4 These findings afford an opportunity to clarify the mechanisms underlying the subcellular regulation of Gi-protein activity, as well as GPCR-mediated ligand sensing, during chemotaxis in mammalian cells.-Masuda, K., Kitakami, J., Kozasa, T., Kodama, T., Ihara, S., Hamakubo, T. Visualization of ligand-induced Gi-protein activation in chemotaxing cells.

Direct evidence for pitavastatin induced chromatin structure change in the KLF4 gene in endothelial cells.

Statins exert atheroprotective effects through the induction of specific transcriptional factors in multiple organs. In endothelial cells, statin-dependent atheroprotective gene up-regulation is mediated by Kruppel-like factor (KLF) family transcription factors. To dissect the mechanism of gene regulation, we sought to determine molecular targets by performing microarray analyses of human umbilical vein endothelial cells (HUVECs) treated with pitavastatin, and KLF4 was determined to be the most highly induced gene. In addition, it was revealed that the atheroprotective genes induced with pitavastatin, such as nitric oxide synthase 3 (NOS3) and thrombomodulin (THBD), were suppressed by KLF4 knockdown. Myocyte enhancer factor-2 (MEF2) family activation is reported to be involved in pitavastatin-dependent KLF4 induction. We focused on MEF2C among the MEF2 family members and identified a novel functional MEF2C binding site 148 kb upstream of the KLF4 gene by chromatin immunoprecipitation along with deep sequencing (ChIP-seq) followed by luciferase assay. By applying whole genome and quantitative chromatin conformation analysis {chromatin interaction analysis with paired end tag sequencing (ChIA-PET), and real time chromosome conformation capture (3C) assay}, we observed that the MEF2C-bound enhancer and transcription start site (TSS) of KLF4 came into closer spatial proximity by pitavastatin treatment. 3D-Fluorescence in situ hybridization (FISH) imaging supported the conformational change in individual cells. Taken together, dynamic chromatin conformation change was shown to mediate pitavastatin-responsive gene induction in endothelial cells.

A simple knowledge-based mining method for exploring hidden key molecules in a human biomolecular network.

BACKGROUND: In the functional genomics analysis domain, various methodologies are available for interpreting the results produced by high-throughput biological experiments. These methods commonly use a list of genes as an analysis input, and most of them produce a more complicated list of genes or pathways as the results of the analysis. Although there are several network-based methods, which detect key nodes in the network, the results tend to include well-studied, major hub genes. RESULTS: To mine the molecules that have biological meaning but to fewer degrees than major hubs, we propose, in this study, a new network-based method for selecting these hidden key molecules based on virtual information flows circulating among the input list of genes. The human biomolecular network was constructed from the Pathway Commons database, and a calculation method based on betweenness centrality was newly developed. We validated the method with the ErbB pathway and applied it to practical cancer research data. We were able to confirm that the output genes, despite having fewer edges than major hubs, have biological meanings that were able to be invoked by the input list of genes. CONCLUSIONS: The developed method, named NetHiKe (Network-based Hidden Key molecule miner), was able to detect potential key molecules by utilizing the human biomolecular network as a knowledge base. Thus, it is hoped that this method will enhance the progress of biological data analysis in the whole-genome research era.

Path-preference cellular-automaton model for traffic flow through transit points and its application to the transcription process in human cells.

We all use path routing everyday as we take shortcuts to avoid traffic jams, or by using faster traffic means. Previous models of traffic flow of RNA polymerase II (RNAPII) during transcription, however, were restricted to one dimension along the DNA template. Here we report the modeling and application of traffic flow in transcription that allows preferential paths of different dimensions only restricted to visit some transit points, as previously introduced between the 5' and 3' end of the gene. According to its position, an RNAPII protein molecule prefers paths obeying two types of time-evolution rules. One is an asymmetric simple exclusion process (ASEP) along DNA, and the other is a three-dimensional jump between transit points in DNA where RNAPIIs are staying. Simulations based on our model, and comparison experimental results, reveal how RNAPII molecules are distributed at the DNA-loop-formation-related protein binding sites as well as CTCF insulator proteins (or exons). As time passes after the stimulation, the RNAPII density at these sites becomes higher. Apparent far-distance jumps in one dimension are realized by short-range three-dimensional jumps between DNA loops. We confirm the above conjecture by applying our model calculation to the SAMD4A gene by comparing the experimental results. Our probabilistic model provides possible scenarios for assembling RNAPII molecules into transcription factories, where RNAPII and related proteins cooperatively transcribe DNA.

Cellular-automaton model of the cooperative dynamics of RNA polymerase II during transcription in human cells.

RNA polymerase II (RNAPII) is the responsible motor protein for transcription. Here we report the formulation and results of a cellular automaton model of the RNAPII dynamics of gene transcription that takes account the effect of the velocity change according to the gene position, such as occurs in introns and exons. We describe RNAPII dynamics in terms of the properties in the time domain, such as elapsed time, residence time, and time intervals. We found that the RNAPII molecules move as a free-flow state, though regions of reduced velocity do exist such as exons, as far as the time interval between nearest RNAPII molecules is larger than the time required for an RNAPII passing the exclusion length in the velocity reduction region. On the other hand, if the reduction is strong enough to reach a certain threshold, at the maximally reductive velocity region, a transition occurs from the RNAPII free-flow state to the states with congested and repetitive flows. We analytically obtained the conditions for these flow states and the transition threshold. From simulations of high-density RNAPII in the SAMD4A gene with the strong blockade, we confirmed the transition from free flow to the repetitive and congested flows, suggesting that the transition may serve as a regulatory mechanism of gene expression. By fitting the experimentally observed RNAPII density profile of the SAMD4A gene during the course of transcription of the normal and altered gene (in knock-down cells) with or without roadblock, we found that the RNAPII density flow is a free state. However, even in this free state, there is a long-range correlation between RNAPII molecules, ranging from 1 to 20 min, with the corresponding distance from 3 to 80 kbp, during transcription in normal cells. This long-range correlation probably relates to the higher-order DNA loop structure.

Epigenetically coordinated GATA2 binding is necessary for endothelium-specific endomucin expression.

GATA2 is well recognized as a key transcription factor and regulator of cell-type specificity and differentiation. Here, we carried out comparative chromatin immunoprecipitation with comprehensive sequencing (ChIP-seq) to determine genome-wide occupancy of GATA2 in endothelial cells and erythroids, and compared the occupancy to the respective gene expression profile in each cell type. Although GATA2 was commonly expressed in both cell types, different GATA2 bindings and distinct cell-specific gene expressions were observed. By using the ChIP-seq with epigenetic histone modifications and chromatin conformation capture assays; we elucidated the mechanistic regulation of endothelial-specific GATA2-mediated endomucin gene expression, that was regulated by the endothelial-specific chromatin loop with a GATA2-associated distal enhancer and core promoter. Knockdown of endomucin markedly attenuated endothelial cell growth, migration and tube formation. Moreover, abrogation of GATA2 in endothelium demonstrated not only a reduction of endothelial-specific markers, but also induction of mesenchymal transition promoting gene expression. Our findings provide new insights into the correlation of endothelial-expressed GATA2 binding, epigenetic modification, and the determination of endothelial cell specificity.

Proteomic analysis of native hepatocyte nuclear factor-4α (HNF4α) isoforms, phosphorylation status, and interactive cofactors.

Hepatocyte nuclear factor-4α (HNF4α, NR2A1) is a nuclear receptor that has a critical role in hepatocyte differentiation and the maintenance of homeostasis in the adult liver. However, a detailed understanding of native HNF4α in the steady-state remains to be elucidated. Here we report the native HNF4α isoform, phosphorylation status, and complexes in the steady-state, as shown by shotgun proteomics in HepG2 hepatocarcinoma cells. Shotgun proteomic analysis revealed the complexity of native HNF4α, including multiple phosphorylation sites and inter-isoform heterodimerization. The associating complexes identified by label-free semiquantitative proteomic analysis include the following: the DNA-dependent protein kinase catalytic subunit, histone acetyltransferase complexes, mRNA splicing complex, other nuclear receptor coactivator complexes, the chromatin remodeling complex, and the nucleosome remodeling and histone deacetylation complex. Among the associating proteins, GRB10 interacting GYF protein 2 (GIGYF2, PERQ2) is a new candidate cofactor in metabolic regulation. Moreover, an unexpected heterodimerization of HNF4α and hepatocyte nuclear factor-4γ was found. A biochemical and genomewide analysis of transcriptional regulation showed that this heterodimerization activates gene transcription. The genes thus transcribed include the cell death-inducing DEF45-like effector b (CIDEB) gene, which is an important regulator of lipid metabolism in the liver. This suggests that the analysis of the distinctive stoichiometric balance of native HNF4α and its cofactor complexes described here are important for an accurate understanding of transcriptional regulation.

Active RNA polymerases: mobile or immobile molecular machines?

It is widely assumed that active RNA polymerases track along their templates to produce a transcript. We test this using chromosome conformation capture and human genes switched on rapidly and synchronously by tumour necrosis factor alpha (TNFalpha); one is 221 kbp SAMD4A, which a polymerase takes more than 1 h to transcribe. Ten minutes after stimulation, the SAMD4A promoter comes together with other TNFalpha-responsive promoters. Subsequently, these contacts are lost as new downstream ones appear; contacts are invariably between sequences being transcribed. Super-resolution microscopy confirms that nascent transcripts (detected by RNA fluorescence in situ hybridization) co-localize at relevant times. Results are consistent with an alternative view of transcription: polymerases fixed in factories reel in their respective templates, so different parts of the templates transiently lie together.

Enhancement of bone formation ex vivo and in vivo by a helioxanthin-derivative.

To effectively treat serious bone defects using bone-regenerative medicine, a small chemical compound that potently induces bone formation must be developed. We previously reported on the osteogenic effect of 4-(4-methoxyphenyl)pyrido[40,30:4,5]thieno[2,3-b]pyridine-2-carboxamide (TH), a helioxanthin-derivative, in vitro. Here, we report on TH's osteogenic effects ex vivo and in vivo. TH-induced new bone formation in both calvarial and metatarsal organ cultures. A novel monitoring system of osteoblastic differentiation using MC3T3-E1 cells revealed that TH was released from alpha-TCP bone cement and this release continued for more than one month. Lastly, the implantation of the alpha-TCP carrier containing TH into defects in mouse skull resulted in increased new bone areas within the defects after 4 weeks. A TH-containing scaffold may help establish a more efficient bone regeneration system.

A wave of nascent transcription on activated human genes.

Genome-wide studies reveal that transcription by RNA polymerase II (Pol II) is dynamically regulated. To obtain a comprehensive view of a single transcription cycle, we switched on transcription of five long human genes (>100 kbp) with tumor necrosis factor-alpha (TNFalpha) and monitored (using microarrays, RNA fluorescence in situ hybridization, and chromatin immunoprecipitation) the appearance of nascent RNA, changes in binding of Pol II and two insulators (the cohesin subunit RAD21 and the CCCTC-binding factor CTCF), and modifications of histone H3. Activation triggers a wave of transcription that sweeps along the genes at approximately 3.1 kbp/min; splicing occurs cotranscriptionally, a major checkpoint acts several kilobases downstream of the transcription start site to regulate polymerase transit, and Pol II tends to stall at cohesin/CTCF binding sites.

The peroxisome proliferator-activated receptor gamma/retinoid X receptor alpha heterodimer targets the histone modification enzyme PR-Set7/Setd8 gene and regulates adipogenesis through a positive feedback loop.

Control of cell differentiation occurs through transcriptional mechanisms and through epigenetic modification. Using a chromatin immunoprecipitation-on-chip approach, we performed a genome-wide search for target genes of peroxisome proliferator-activated receptor gamma (PPAR gamma) and its partner protein retinoid X receptor alpha during adipogenesis. We show that these two receptors target several genes that encode histone lysine methyltransferase SET domain proteins. The histone H4 Lys 20 (H4K20) monomethyltransferase PR-Set7/Setd8 gene is upregulated by PPAR gamma during adipogenesis, and the knockdown of PR-Set7/Setd8 suppressed adipogenesis. Intriguingly, monomethylated H4K20 (H4K20me1) levels are robustly increased toward the end of differentiation. PR-Set7/Setd8 positively regulates the expression of PPAR gamma and its targets through H4K20 monomethylation. Furthermore, the activation of PPAR gamma transcriptional activity leads to the induction of H4K20me1 modification of PPAR gamma and its targets and thereby promotes adipogenesis. We also show that PPAR gamma targets PPAR gamma2 and promotes its gene expression through H4K20 monomethylation. Our results connect transcriptional regulation and epigenetic chromatin modulation through H4K20 monomethylation during adipogenesis through a feedback loop.

Genome-wide detection of human copy number variations using high-density DNA oligonucleotide arrays.

Recent reports indicate that copy number variations (CNVs) within the human genome contribute to nucleotide diversity to a larger extent than single nucleotide polymorphisms (SNPs). In addition, the contribution of CNVs to human disease susceptibility may be greater than previously expected, although a complete understanding of the phenotypic consequences of CNVs is incomplete. We have recently reported a comprehensive view of CNVs among 270 HapMap samples using high-density SNP genotyping arrays and BAC array CGH. In this report, we describe a novel algorithm using Affymetrix GeneChip Human Mapping 500K Early Access (500K EA) arrays that identified 1203 CNVs ranging in size from 960 bp to 3.4 Mb. The algorithm consists of three steps: (1) Intensity pre-processing to improve the resolution between pairwise comparisons by directly estimating the allele-specific affinity as well as to reduce signal noise by incorporating probe and target sequence characteristics via an improved version of the Genomic Imbalance Map (GIM) algorithm; (2) CNV extraction using an adapted SW-ARRAY procedure to automatically and robustly detect candidate CNV regions; and (3) copy number inference in which all pairwise comparisons are summarized to more precisely define CNV boundaries and accurately estimate CNV copy number. Independent testing of a subset of CNVs by quantitative PCR and mass spectrometry demonstrated a >90% verification rate. The use of high-resolution oligonucleotide arrays relative to other methods may allow more precise boundary information to be extracted, thereby enabling a more accurate analysis of the relationship between CNVs and other genomic features.

Packet traffic analysis of scale-free networks for large-scale network-on-chip design.

Recent progress in integrated circuit technologies requires precise evaluation between dynamic characteristics and topological architecture design. In this paper, we have investigated the performance evaluation of network-on-chip (NoC) architectures constructed with diverse scale-free network topologies by dynamic packet traffic simulation and theoretical network analysis. Topological differences of scale-free networks are evaluated by the degree-degree correlations that indicate topological tendency between the degree of a node and that of the nearest neighbors. Our simulation results quantitatively show that the NoC architecture constructed with the topology where hubs mostly connect to lower-degree nodes is found to achieve short latency and low packet loss ratio since it can disperse traffic load and avoid the extreme concentration of load on hubs.

Noise reduction from genotyping microarrays using probe level information.

Genomic copy number change is one of the important phenomenon observed in cancer and other genetic disorders. Recently oligonucleotide microarrays have been used to analyze changes in the copy number. Although high density microarrays provide genome wide useful data on copy number, they are often associated with substantial amount of experimental noise that could affect the performance of the analyses. We used the high density oligonucleotide genotyping microarrays in our experiments that uses redundant probe tiling approach for individual SNPs. We found that the noise in the genotyping microarray data is associated with several experimental steps during target preparation and devised an algorithm that takes into account those experimental parameters. Additionally, defective probes that do not hybridize well to the target and therefore could not be modified inherently were detected and omitted automatically by using the algorithm. When we applied the algorithm to actual datasets, we could reduce the noise substantially without compressing the dynamic range. Additionally, combinatorial use of our noise reduction algorithm and conventional breakpoint detection algorithm successfully detected a microamplification of c-myc which was overlooked in the raw data. The algorithm described here is freely available with the software upon request to all non-profit researchers.

Analysis of mechanism for human gammadelta T cell recognition of nonpeptide antigens.

Whereas human gammadelta T cells respond to nonpeptide antigens like pyrophosphomonoesters and alkyl amines in the primary reactions, only pyrophosphomonoesters provoke proliferative responses in the secondary responses. To elucidate the differences in stimulatory activity between the two groups of nonpeptide antigens, we systematically analyzed time courses of gene expressions by microarray analyses. While 253 genes were induced by stimulation with 2-methyl-3-butenyl-1-pyrophosphate (2M3B1PP), only 35 genes were detected after stimulation with isobutyl amine. Then, gammadelta T cells expressed various cytokines like XCL1-2, CCL3-4, TNF-alpha, and IFN-gamma in response to 2M3B1PP in a time-dependent manner, while transient expressions were observed in IBA during the time period. The differences in such responsiveness are likely to originate from the activation state of NFAT, which is involved in the expression of transcription factors, EGR1-3 and NR4A1-2, and might play a crucial role in effector functions of gammadelta T cells.

Interpreting expression profiles of cancers by genome-wide survey of breadth of expression in normal tissues.

A critical and difficult part of studying cancer with DNA microarrays is data interpretation. Besides the need for data analysis algorithms, integration of additional information about genes might be useful. We performed genome-wide expression profiling of 36 types of normal human tissues and identified 2503 tissue-specific genes. We then systematically studied the expression of these genes in cancers by reanalyzing a large collection of published DNA microarray datasets. We observed that the expression level of liver-specific genes in hepatocellular carcinoma (HCC) correlates with the clinically defined degree of tumor differentiation. Through unsupervised clustering of tissue-specific genes differentially expressed in tumors, we extracted expression patterns that are characteristic of individual cell types, uncovering differences in cell lineage among tumor subtypes. We were able to detect the expression signature of hepatocytes in HCC, neuron cells in medulloblastoma, glia cells in glioma, basal and luminal epithelial cells in breast tumors, and various cell types in lung cancer samples. We also demonstrated that tissue-specific expression signatures are useful in locating the origin of metastatic tumors. Our study shows that integration of each gene's breadth of expression (BOE) in normal tissues is important for biological interpretation of the expression profiles of cancers in terms of tumor differentiation, cell lineage, and metastasis.

Identification of soluble NH2-terminal fragment of glypican-3 as a serological marker for early-stage hepatocellular carcinoma.

For detection of hepatocellular carcinoma (HCC) in patients with liver cirrhosis, serum alpha-fetoprotein has been widely used, but its sensitivity has not been satisfactory, especially in small, well-differentiated HCC, and complementary serum marker has been clinically required. Glypican-3 (GPC3), a heparan sulfate proteoglycan anchored to the plasma membrane, is a good candidate marker of HCC because it is an oncofetal protein overexpressed in HCC at both the mRNA and protein levels. In this study, we demonstrated that its NH(2)-terminal portion [soluble GPC3 (sGPC3)] is cleaved between Arg(358) and Ser(359) of GPC3 and that sGPC3 can be specifically detected in the sera of patients with HCC. Serum levels of sGPC3 were 4.84 +/- 8.91 ng/ml in HCC, significantly higher than the levels seen in liver cirrhosis (1.09 +/- 0.74 ng/ml; P < 0.01) and healthy controls (0.65 +/- 0.32 ng/ml; P < 0.001). In well- or moderately-differentiated HCC, sGPC3 was superior to alpha-fetoprotein in sensitivity, and a combination measurement of both markers improved overall sensitivity from 50% to 72%. These results indicate that sGPC3 is a novel serological marker essential for the early detection of HCC.

Identification of gene expression profile in tolerizing murine cardiac allograft by costimulatory blockade.

The induction of specific tolerance would be the ultimate achievement in transplant immunology, but the precise mechanisms of immunologic tolerance remain largely unknown. Here, we investigated global gene expression analysis in tolerizing murine cardiac allografts by means of oligonucleotide microarrays. Tolerance induction was achieved in cardiac allografts from BALB/c to C57BL/6 mice by daily intraperitoneal injection of anti-CD80 and anti-CD86 monoclonal antibodies (mAbs). Comparative analysis revealed 64 genes to be induced more extensively in the tolerizing than in the syngeneic isografts, and 16 genes than in the rejecting allografts. Two genes were specifically upregulated in the tolerizing allografts. In the tolerizing allografts there were induced marked expressions of a number of genes for pro-inflammatory factors, including interferon-gamma-inducible cytokines and chemokines, as well as apoptosis-related genes, which were also upregulated in the rejecting allografts. Moreover, these gene expression patterns continued to be upregulated more than 70 days posttransplant. These results provide evidence that immunologic tolerance can be induced and maintained in the presence of prominent pro-inflammatory gene expression in vivo.