Mutation in Smek2 regulating hepatic glucose metabolism causes hypersarcosinemia and hyperhomocysteinemia in rats.

Suppressor of mek1 (Dictyostelium) homolog 2 (Smek2), was identified as one of the responsible genes for diet-induced hypercholesterolemia (DIHC) of exogenously hypercholesterolemic (ExHC) rats. A deletion mutation in Smek2 leads to DIHC via impaired glycolysis in the livers of ExHC rats. The intracellular role of Smek2 remains obscure. We used microarrays to investigate Smek2 functions with ExHC and ExHC.BN-Dihc2BN congenic rats that harbor a non-pathological Smek2 allele from Brown-Norway rats on an ExHC background. Microarray analysis revealed that Smek2 dysfunction leads to extremely low sarcosine dehydrogenase (Sardh) expression in the liver of ExHC rats. Sarcosine dehydrogenase demethylates sarcosine, a byproduct of homocysteine metabolism. The ExHC rats with dysfunctional Sardh developed hypersarcosinemia and homocysteinemia, a risk factor for atherosclerosis, with or without dietary cholesterol. The mRNA expression of Bhmt, a homocysteine metabolic enzyme and the hepatic content of betaine (trimethylglycine), a methyl donor for homocysteine methylation were low in ExHC rats. Results suggest that homocysteine metabolism rendered fragile by a shortage of betaine results in homocysteinemia, and that Smek2 dysfunction causes abnormalities in sarcosine and homocysteine metabolism.

Author Correction: Diversity in gut bacterial community of school-age children in Asia.

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Characterization of KfrA proteins encoded by a plasmid of Paenibacillus popilliae ATCC 14706(T).

A scaffold obtained from whole-genome shotgun sequencing of Paenibacillus popilliae ATCC 14706(T) shares partial homology with plasmids found in other strains of P. popilliae. PCR and sequencing for gap enclosure indicated that the scaffold originated from a 15,929-bp circular DNA. The restriction patterns of a plasmid isolated from P. popilliae ATCC 14706(T) were identical to those expected from the sequence; thus, this circular DNA was identified as a plasmid of ATCC 14706(T) and designated pPOP15.9. The plasmid encodes 17 putative open reading frames. Orfs 1, 5, 7, 8, and 9 are homologous to Orfs 11, 12, 15, 16, and 17, respectively. Orf1 and Orf11 are annotated as replication initiation proteins. Orf8 and Orf16 are homologs of KfrA, a plasmid-stabilizing protein in Gram-negative bacteria. Recombinant Orf8 and Orf16 proteins were assessed for the properties of KfrA. Indeed, they formed multimers and bound to inverted repeat sequences in upstream regions of both orf8 and orf16. A phylogenetic tree based on amino acid sequences of Orf8, Orf16 and Kfr proteins did not correlate with species lineage.

Diversity in gut bacterial community of school-age children in Asia.

Asia differs substantially among and within its regions populated by diverse ethnic groups, which maintain their own respective cultures and dietary habits. To address the diversity in their gut microbiota, we characterized the bacterial community in fecal samples obtained from 303 school-age children living in urban or rural regions in five countries spanning temperate and tropical areas of Asia. The microbiota profiled for the 303 subjects were classified into two enterotype-like clusters, each driven by Prevotella (P-type) or Bifidobacterium/Bacteroides (BB-type), respectively. Majority in China, Japan and Taiwan harbored BB-type, whereas those from Indonesia and Khon Kaen in Thailand mainly harbored P-type. The P-type microbiota was characterized by a more conserved bacterial community sharing a greater number of type-specific phylotypes. Predictive metagenomics suggests higher and lower activity of carbohydrate digestion and bile acid biosynthesis, respectively, in P-type subjects, reflecting their high intake of diets rich in resistant starch. Random-forest analysis classified their fecal species community as mirroring location of resident country, suggesting eco-geographical factors shaping gut microbiota. In particular, children living in Japan harbored a less diversified microbiota with high abundance of Bifidobacterium and less number of potentially pathogenic bacteria, which may reflect their living environment and unique diet.

FGFR1 activation is an escape mechanism in human lung cancer cells resistant to afatinib, a pan-EGFR family kinase inhibitor.

Most NSCLC patients with EGFR mutations benefit from treatment with EGFR-TKIs, but the clinical efficacy of EGFR-TKIs is limited by the appearance of drug resistance. Multiple kinase inhibitors of EGFR family proteins such as afatinib have been newly developed to overcome such drug resistance. We established afatinib-resistant cell lines after chronic exposure of activating EGFR mutation-positive PC9 cells to afatinib. Afatinib-resistant cells showed following specific characteristics as compared to PC9: [1] Expression of EGFR family proteins and their phosphorylated molecules was markedly downregulated by selection of afatinib resistance; [2] Expression of FGFR1 and its ligand FGF2 was alternatively upregulated; [3] Treatment with anti-FGF2 neutralizing antibody blocked enhanced phosphorylation of FGFR in resistant clone; [4] Both resistant clones showed collateral sensitivity to PD173074, a small-molecule FGFR-TKIs, and treatment with either PD173074 or FGFR siRNA exacerbated suppression of both afatinib-resistant Akt and Erk phosphorylation when combined with afatinib; [5] Expression of twist was markedly augmented in resistant sublines, and twist knockdown specifically suppressed FGFR expression and cell survival. Together, enhanced expression of FGFR1 and FGF2 thus plays as an escape mechanism for cell survival of afatinib-resistant cancer cells, that may compensate the loss of EGFR-driven signaling pathway.

Phylogenetic relationship of Paenibacillus species based on putative replication origin regions and analysis of an yheCD-like sequence found in this region.

To determine the phylogenetic relationship among Paenibacillus species, putative replication origin regions were compared. In the rsmG-gyrA region, gene arrangements in Paenibacillus species were identical to those of Bacillus species, with the exception of an open reading frame (orf14) positioned between gyrB and gyrA, which was observed only in Paenibacillus species. The orf14 product was homologous to the endospore-associated proteins YheC and YheD of Bacillus subtilis. Phylogenetic analysis based on the YheCD proteins suggested that Orf14 could be categorized into the YheC group. In the Paenibacillus genome, DnaA box clusters were found in rpmH-dnaA and dnaA-dnaN intergenic regions, known as box regions C and R, respectively; this localization was similar to that observed in B. halodurans. A phylogenetic tree based on the nucleotide sequences of the whole replication origin regions suggested that P. popilliae, P. thiaminolyticus, and P. dendritiformis are closely related species.

Draft Genome Sequence of Entomopathogenic Serratia liquefaciens Strain FK01.

In the present study, we determined the draft genome sequence of the entomopathogenic bacterium Serratia liquefaciens FK01, which is highly virulent to the silkworm. The draft genome is ~5.28 Mb in size, and the G+C content is 55.8%.

Changes in transcription during recovery from heat injury in Salmonella typhimurium and effects of BCAA on recovery.

Mechanisms of recovery from heat injury in Salmonella typhimurium were elucidated. Recovery of the heat-injured S. typhimurium cells in TSB resulted in full recovery after 3 h of incubation at 37°C. The DNA microarray analysis of 30- and 60-min recovering cells resulted in an increase in transcription of 89 and 141 genes, respectively. Among them, 15 genes, with known function, seemed to be somewhat involved in recovery. They encoded proteins involved in branched-chain amino acid (BCAA) transport (livJ, livH), cell envelope integrity (ddg), heat-shock response (cpxP, rrmJ), phage shock protein (pspA), ribosome modulation factor (rmf), virulence (sseB) transcriptional regulation (rpoE, rpoH, rseA, rseB, rseC) and ArcB signal transduction (sixA) and cytoplasmic membrane protein (fxsA). Among them, the effects of BCAA supplementation on recovery from heat injury were studied to confirm the importance of the BCAA transport liv genes during recovery. It was found that supplementation of TSB with 0.1% BCAA resulted in an enhanced recovery of injured cells in comparison to those recovered in TSB without BCAA. Supplementation of BCAA at 0.1% resulted in a cell count increase 4.4-fold greater than that of the control after 1 h incubation. It seems that BCAA promoted the recovery by promoting protein synthesis either directly through their use in translation or indirectly through stimulation of protein synthesis by activation of the Lrp protein.

Gene expression profiles in peripheral blood as a biomarker in cancer patients receiving peptide vaccination.

BACKGROUND: Because only a subset of patients show clinical responses to peptide-based cancer vaccination, it is critical to identify biomarkers for selecting patients who would most likely benefit from this treatment. METHODS: The authors characterized the gene expression profiles in peripheral blood of vaccinated patients to identify biomarkers to predict patient prognosis. Peripheral blood was obtained from advanced castration-resistant prostate cancer patients, who survived for >900 days (long-term survivors, n = 20) or died within 300 days (short-term survivors, n = 20) after treatment with personalized peptide vaccination. Gene expression profiles in prevaccination and postvaccination peripheral blood mononuclear cells (PBMCs) were assessed by DNA microarray. RESULTS: There were no statistically significant differences in the clinical or pathological features between the 2 groups. Microarray analysis of prevaccination PBMCs identified 19 genes that were differentially expressed between the short-term and long-term survivors. Among the 15 up-regulated genes in the short-term survivors, 13 genes, which were also differentially expressed in postvaccination PBMCs, were associated with gene signatures of granulocytes. When a set of 4 differentially expressed genes were selected as the best combination to determine patient survival, prognosis was correctly predicted in 12 of 13 patients in a validation set (accuracy, 92%). CONCLUSIONS: These results suggested that abnormal granulocytes present in the PBMC faction may contribute to poor prognosis in advanced prostate cancer patients receiving personalized peptide vaccination. Gene expression profiling in peripheral blood might thus be informative for devising better therapeutic strategies by predicting patient prognosis after cancer vaccines.

Identification of a two-component VirR/VirS regulon in Clostridium perfringens.

Clostridium perfringens, a Gram-positive anaerobic pathogen, is a causative agent of human gas gangrene that leads to severe rapid tissue destruction and can cause death within hours unless treated immediately. Production of several toxins is known to be controlled by the two-component VirR/VirS system involving a regulatory RNA (VR-RNA) in C. perfringens. To elucidate the precise regulatory network governed by VirR/VirS and VR-RNA, a series of microarray screening using VirR/VirS and VR-RNA-deficient mutants was performed. Finally, by qRT-PCR analysis, 147 genes (30 single genes and 21 putative operons) were confirmed to be under the control of the VirR/VirS-VR-RNA regulatory cascade. Several virulence-related genes for alpha-toxin, kappa-toxin, hyaluronidases, sialidase, and capsular polysaccharide synthesis were found. Furthermore, some genes for catalytic enzymes, various genes for transporters, and many genes for energy metabolism were also found to be controlled by the cascade. Our data indicate that the VirR/VirS-VR-RNA system is a global gene regulator that might control multiple cellular functions to survive and multiply in the host, which would turn out to be a lethal flesh-eating infection.

Analysis of PPARalpha-dependent and PPARalpha-independent transcript regulation following fenofibrate treatment of human endothelial cells.

Fenofibrate is a synthetic ligand for the nuclear receptor peroxisome proliferator-activated receptor (PPAR) alpha and has been widely used in the treatment of metabolic disorders, especially hyperlipemia, due to its lipid-lowering effect. The molecular mechanism of lipid-lowering is relatively well defined: an activated PPARalpha forms a PPAR-RXR heterodimer and this regulates the transcription of genes involved in energy metabolism by binding to PPAR response elements in their promoter regions, so-called "trans-activation". In addition, fenofibrate also has anti-inflammatory and anti-athrogenic effects in vascular endothelial and smooth muscle cells. We have limited information about the anti-inflammatory mechanism of fenofibrate; however, "trans-repression" which suppresses production of inflammatory cytokines and adhesion molecules probably contributes to this mechanism. Furthermore, there are reports that fenofibrate affects endothelial cells in a PPARalpha-independent manner. In order to identify PPARalpha-dependently and PPARalpha-independently regulated transcripts, we generated microarray data from human endothelial cells treated with fenofibrate, and with and without siRNA-mediated knock-down of PPARalpha. We also constructed dynamic Bayesian transcriptome networks to reveal PPARalpha-dependent and -independent pathways. Our transcriptome network analysis identified growth differentiation factor 15 (GDF15) as a hub gene having PPARalpha-independently regulated transcripts as its direct downstream children. This result suggests that GDF15 may be PPARalpha-independent master-regulator of fenofibrate action in human endothelial cells.

Unraveling dynamic activities of autocrine pathways that control drug-response transcriptome networks.

Some drugs affect secretion of secreted proteins (e.g. cytokines) released from target cells, but it remains unclear whether these proteins act in an autocrine manner and directly effect the cells on which the drugs act. In this study, we propose a computational method for testing a biological hypothesis: there exist autocrine signaling pathways that are dynamically regulated by drug response transcriptome networks and control them simultaneously. If such pathways are identified, they could be useful for revealing drug mode-of-action and identifying novel drug targets. By the node-set separation method proposed, dynamic structural changes can be embedded in transcriptome networks that enable us to find master-regulator genes or critical paths at each observed time. We then combine the protein-protein interaction network with the estimated dynamic transcriptome network to discover drug-affected autocrine pathways if they exist. The statistical significance (p-values) of the pathways are evaluated by the meta-analysis technique. The dynamics of the interactions between the transcriptome networks and the signaling pathways will be shown in this framework. We illustrate our strategy by an application using anti-hyperlipidemia drug, Fenofibrate. From over one million protein-protein interaction pathways, we extracted significant 23 autocrine-like pathways with the Bonferroni correction, including VEGF-NRP1-GIPC1-PRKCA-PPARalpha, that is one of the most significant ones and contains PPARalpha, a target of Fenofibrate.

Periodic gene expression patterns during the highly synchronized cell nucleus and organelle division cycles in the unicellular red alga Cyanidioschyzon merolae.

Previous cell cycle studies have been based on cell-nuclear proliferation only. Eukaryotic cells, however, have double membranes-bound organelles, such as the cell nucleus, mitochondrion, plastids and single-membrane-bound organelles such as ER, the Golgi body, vacuoles (lysosomes) and microbodies. Organelle proliferations, which are very important for cell functions, are poorly understood. To clarify this, we performed a microarray analysis during the cell cycle of Cyanidioschyzon merolae. C. merolae cells contain a minimum set of organelles that divide synchronously. The nuclear, mitochondrial and plastid genomes were completely sequenced. The results showed that, of 158 genes induced during the S or G2-M phase, 93 were known and contained genes related to mitochondrial division, ftsZ1-1, ftsz1-2 and mda1, and plastid division, ftsZ2-1, ftsZ2-2 and cmdnm2. Moreover, three genes, involved in vesicle trafficking between the single-membrane organelles such as vps29 and the Rab family protein, were identified and might be related to partitioning of single-membrane-bound organelles. In other genes, 46 were hypothetical and 19 were hypothetical conserved. The possibility of finding novel organelle division genes from hypothetical and hypothetical conserved genes in the S and G2-M expression groups is discussed.

Extensive genomic diversity and selective conservation of virulence-determinants in enterohemorrhagic Escherichia coli strains of O157 and non-O157 serotypes.

BACKGROUND: Enterohemorrhagic Escherichia coli (EHEC) O157 causes severe food-borne illness in humans. The chromosome of O157 consists of 4.1 Mb backbone sequences shared by benign E. coli K-12, and 1.4 Mb O157-specific sequences encoding many virulence determinants, such as Shiga toxin genes (stx genes) and the locus of enterocyte effacement (LEE). Non-O157 EHECs belonging to distinct clonal lineages from O157 also cause similar illness in humans. According to the 'parallel' evolution model, they have independently acquired the major virulence determinants, the stx genes and LEE. However, the genomic differences between O157 and non-O157 EHECs have not yet been systematically analyzed. RESULTS: Using microarray and whole genome PCR scanning analyses, we performed a whole genome comparison of 20 EHEC strains of O26, O111, and O103 serotypes with O157. In non-O157 EHEC strains, although genome sizes were similar with or rather larger than O157 and the backbone regions were well conserved, O157-specific regions were very poorly conserved. Around only 20% of the O157-specific genes were fully conserved in each non-O157 serotype. However, the non-O157 EHECs contained a significant number of virulence genes that are found on prophages and plasmids in O157, and also multiple prophages similar to, but significantly divergent from, those in O157. CONCLUSION: Although O157 and non-O157 EHECs have independently acquired a huge amount of serotype- or strain-specific genes by lateral gene transfer, they share an unexpectedly large number of virulence genes. Independent infections of similar but distinct bacteriophages carrying these virulence determinants are deeply involved in the evolution of O157 and non-O157 EHECs.

Computational strategy for discovering druggable gene networks from genome-wide RNA expression profiles.

We propose a computational strategy for discovering gene networks affected by a chemical compound. Two kinds of DNA microarray data are assumed to be used: One dataset is short time-course data that measure responses of genes following an experimental treatment. The other dataset is obtained by several hundred single gene knock-downs. These two datasets provide three kinds of information; (i) A gene network is estimated from time-course data by the dynamic Bayesian network model, (ii) Relationships between the knocked-down genes and their regulatees are estimated directly from knock-down microarrays and (iii) A gene network can be estimated by gene knock-down data alone using the Bayesian network model. We propose a method that combines these three kinds of information to provide an accurate gene network that most strongly relates to the mode-of-action of the chemical compound in cells. This information plays an essential role in pharmacogenomics. We illustrate this method with an actual example where human endothelial cell gene networks were generated from a novel time course of gene expression following treatment with the drug fenofibrate, and from 270 novel gene knock-downs. Finally, we succeeded in inferring the gene network related to PPAR-alpha, which is a known target of fenofibrate.

Complexity of the genomic diversity in enterohemorrhagic Escherichia coli O157 revealed by the combinational use of the O157 Sakai OligoDNA microarray and the Whole Genome PCR scanning.

Escherichia coli O157, an etiological agent of hemorrhagic colitis and hemolytic uremic syndrome, is one of the leading worldwide public health threats. Genome sequencing of two O157 strains have revealed that the chromosome is comprised of a 4.1 Mb backbone shared by K-12 and a total of 1.4 Mb O157-specific sequences. Most of the large O157-specific sequences are prophages and prophage-like elements, which have carried many virulence genes into the O157 genome. This suggests that bacteriophages have played the key roles in the emergence of O157. The Whole Genome PCR Scanning (WGPScanning) analysis of O157 strains, on the other hand, revealed a high level of genomic diversity in O157. Variation of prophages has also been suggested as a major factor generating such diversity. In this study, we analyzed the gene content of O157 strains, by an oligoDNA microarray, using the same set of strains as examined by the WGPScanning method. Although most of the strains were typical O157 : H7, they differed remarkably in gene composition, particularly in those on prophages, and we identified more than 400 'variably absent or present' genes which included virulence-related genes. This confirms the role of prophages in generating the genomic diversity, and raises a possibility that some level of variation in potential virulence is present among O157 strains. Fine comparison of the two datasets obtained by microarray and WGPScanning provided much further details on the O157 genome diversity than illustrated by each method alone, indicating the usefulness of this combinational approach in the genomic comparison of closely related strains.

Identifying drug active pathways from gene networks estimated by gene expression data.

We present a computational method for identifying genes and their regulatory pathways influenced by a drug, using microarray gene expression data collected by single gene disruptions and drug responses. The automatic identification of such genes and pathways in organisms' cells is an important problem for pharmacogenomics and the tailor-made medication. Our method estimates regulatory relationships between genes as a gene network from microarray data of gene disruptions with a Bayesian network model, then identifies the drug affected genes and their regulatory pathways on the estimated network with time course drug response microarray data. Compared to the existing method, our proposed method can identify not only the drug affected genes and the druggable genes, but also the drug responses of the pathways. For evaluating the proposed method, we conducted simulated examples based on artificial networks and expression data. Our method succeeded in identifying the pseudo drug affected genes and pathways with the high coverage greater than 80 %. We also applied our method to Saccharomyces cerevisiae drug response microarray data. In this real example, we identified the genes and the pathways that are potentially influenced by a drug. These computational experiments indicate that our method successfully identifies the drug-activated genes and pathways, and is capable of predicting undesirable side effects of the drug, identifying novel drug target genes, and understanding the unknown mechanisms of the drug.

Combining microarrays and biological knowledge for estimating gene networks via bayesian networks.

We propose a statistical method for estimating a gene network based on Bayesian networks from microarray gene expression data together with biological knowledge including protein-protein interactions, protein-DNA interactions, binding site information, existing literature and so on. Microarray data do not contain enough information for constructing gene networks accurately in many cases. Our method adds biological knowledge to the estimation method of gene networks under a Bayesian statistical framework, and also controls the trade-off between microarray information and biological knowledge automatically. We conduct Monte Carlo simulations to show the effectiveness of the proposed method. We analyze Saccharomyces cerevisiae gene expression data as an application.

Use of segment-based microarray in the analysis of global gene expression in response to various environmental stresses in the cyanobacterium Anabaena sp. PCC 7120.

We prepared microarrays that contain genomic sequences of a heterocyst-forming filamentous cyanobacterium Anabaena sp. PCC 7120. The complete genome of this cyanobacterium codes for about 5,368 protein-coding genes in the main chromosome of 6.4 Mbp. In total, 2,407 DNA segments were selected from the sequencing clones, and amplified by PCR, then spotted on glass slides in duplicate. These microarrays differ from the widely used commercial or custom-made ones for other microorganisms in that each DNA segment was 3-4 kbp long, and contained about 3-4 predicted genes on average. This feature, however, did not decrease the usefulness of the microarrays, since we were able to detect a number of potentially novel genes that are induced in response to nitrogen deprivation, low temperature and drought. In addition, we found some genomic regions in which dozens of contiguous genes are simultaneously regulated. These results suggest that these segment-based microarrays are useful especially for such large genomes as Anabaena, for which the number of genes exceeds either technical or practical limitations.

Identification of BMP and activin membrane-bound inhibitor (BAMBI), an inhibitor of transforming growth factor-beta signaling, as a target of the beta-catenin pathway in colorectal tumor cells.

The Wnt signaling pathway is activated in most human colorectal tumors. Mutational inactivation in the tumor suppressor adenomatous polyposis coli (APC), as well as activation of beta-catenin, causes the accumulation of beta-catenin, which in turn associates with the T cell factor/lymphoid enhancer factor (TCF/LEF) family of transcription factors and activates transcription of their target genes. Here we show that beta-catenin activates transcription of the BMP and activin membrane-bound inhibitor (BAMBI)/NMA gene. The expression level of BAMBI was found to be aberrantly elevated in most colorectal and hepatocellular carcinomas relative to the corresponding non-cancerous tissues. Expression of BAMBI in colorectal tumor cell lines was repressed by a dominant-negative mutant of TCF-4 or by an inhibitor of beta-catenin-TCF interaction, suggesting that beta-catenin is responsible for the aberrant expression of BAMBI in colorectal tumor cells. Furthermore, overexpression of BAMBI inhibited the response of tumor cells to transforming growth factor-beta signaling. These results suggest that beta-catenin interferes with transforming growth factor-beta-mediated growth arrest by inducing the expression of BAMBI, and this may contribute to colorectal and hepatocellular tumorigenesis.