[Show abstract][Hide abstract] ABSTRACT: Background
Bacterial operons are considerably more complex than what were thought. At least their components are dynamically rather than statically defined as previously assumed. Here we present a computational study of the landscape of the transcriptional units (TUs) of E. coli K12, revealed by the available genomic and transcriptomic data, providing new understanding about the complexity of TUs as a whole encoded in the genome of E. coli K12.
Results and conclusion
Our main findings include that (i) different TUs may overlap with each other by sharing common genes, giving rise to clusters of overlapped TUs (TUCs) along the genomic sequence; (ii) the intergenic regions in front of the first gene of each TU tend to have more conserved sequence motifs than those of the other genes inside the TU, suggesting that TUs each have their own promoters; (iii) the terminators associated with the 3’ ends of TUCs tend to be Rho-independent terminators, substantially more often than terminators of TUs that end inside a TUC; and (iv) the functional relatedness of adjacent gene pairs in individual TUs is higher than those in TUCs, suggesting that individual TUs are more basic functional units than TUCs.
Electronic supplementary material
The online version of this article (doi:10.1186/s12859-015-0805-8) contains supplementary material, which is available to authorized users.
Full-text · Article · Nov 2015 · BMC Bioinformatics
[Show abstract][Hide abstract] ABSTRACT: Jatropha curcas L. (further referred to as Jatropha), as a rapidly emerging biofuel crop, has attracted worldwide interest. However, Jatropha is still an undomesticated plant, the true potential of this shrub has not yet been fully realized. To explore the potential of Jatropha, breeding and domestication are needed. Seed size is one of the most important traits of seed yield and has been selected since the beginning of agriculture. Increasing the seed size is a main goal of Jatropha domestication for increasing the seed yield, but the genetic regulation of seed size in Jatropha has not been fully understood.
No preview · Article · Nov 2015 · Electronic Journal of Biotechnology
[Show abstract][Hide abstract] ABSTRACT: Sheep red blood cells (SRBCs) have long been used as a model antigen for eliciting systemic immune responses, yet the basis for their adjuvant activity has been unknown. Here, we show that SRBCs failed to engage the inhibitory mouse SIRPα receptor on splenic CD4(+) dendritic cells (DCs), and this failure led to DC activation. Removal of the SIRPα ligand, CD47, from self-RBCs was sufficient to convert them into an adjuvant for adaptive immune responses. DC capture of Cd47(-/-) RBCs and DC activation occurred within minutes in a Src-family-kinase- and CD18-integrin-dependent manner. These findings provide an explanation for the adjuvant mechanism of SRBCs and reveal that splenic DCs survey blood cells for missing self-CD47, a process that might contribute to detecting and mounting immune responses against pathogen-infected RBCs.
[Show abstract][Hide abstract] ABSTRACT: The grade of a cancer is a measure of the cancer's malignancy level, and the stage of a cancer refers to the size and the extent that the cancer has spread. Here we present a computational method for prediction of gene signatures and blood/urine protein markers for breast cancer grades and stages based on RNA-seq data, which are retrieved from the TCGA breast cancer dataset and cover 111 pairs of disease and matching adjacent noncancerous tissues with pathologists-assigned stages and grades. By applying a differential expression and an SVM-based classification approach, we found that 324 and 227 genes in cancer have their expression levels consistently up-regulated vs. their matching controls in a grade- and stage-dependent manner, respectively. By using these genes, we predicted a 9-gene panel as a gene signature for distinguishing poorly differentiated from moderately and well differentiated breast cancers, and a 19-gene panel as a gene signature for discriminating between the moderately and well differentiated breast cancers. Similarly, a 30-gene panel and a 21-gene panel are predicted as gene signatures for distinguishing advanced stage (stages III-IV) from early stage (stages I-II) cancer samples and for distinguishing stage II from stage I samples, respectively. We expect these gene panels can be used as gene-expression signatures for cancer grade and stage classification. In addition, of the 324 grade-dependent genes, 188 and 66 encode proteins that are predicted to be blood-secretory and urine-excretory, respectively; and of the 227 stage-dependent genes, 123 and 51 encode proteins predicted to be blood-secretory and urine-excretory, respectively. We anticipate that some combinations of these blood and urine proteins could serve as markers for monitoring breast cancer at specific grades and stages through blood and urine tests.
[Show abstract][Hide abstract] ABSTRACT: Large numbers of plant cell-wall (CW)-related genes have been identified or predicted in several plant genomes such as Arabidopsis thaliana, Oryza sativa (rice), and Zea mays (maize), as results of intensive studies of these organisms in the past 2 decades. However, no such gene list has been identified in switchgrass (Panicum virgatum), a key bioenergy crop. Here, we present a computational study for prediction of CW genes in switchgrass using a two-step procedure: (i) homology mapping of all annotated CW genes in the fore-mentioned species to switchgrass, giving rise to a total of 991 genes, and (ii) candidate prediction of CW genes based on switchgrass genes co-expressed with the 991 genes under a large number of experimental conditions. Specifically, our co-expression analyses using the 991 genes as seeds led to the identification of 104 large clusters of co-expressed genes, each referred to as a co-expression module (CEM), covering 830 of the 991 genes plus 823 additional genes that are strongly co-expressed with some of the 104 CEMs. These 1653 genes represent our prediction of CW genes in switchgrass, 112 of which are homologous to predicted CW genes in Arabidopsis. Functional inference of these genes is conducted to derive the possible functional relations among these predicted CW genes. Overall, these data may offer a highly useful information source for cell-wall biologists of switchgrass as well as plants in general.
Full-text · Article · Sep 2015 · BioEnergy Research
[Show abstract][Hide abstract] ABSTRACT: Cysteine proteinase inhibitor (cystatin, CPI) is one of the most important molecules involved in plant development and defense, especially in the regulation of stress responses. However, it is still unclear whether the Jatropha curcas CPI (JcCPI) gene functions in salinity response and tolerance. In this study, the sequence of the JcCPI gene, its expression pattern, and the effects of overexpression in Escherichia coli and Nicotiana benthamiana were examined. The purpose of this study was to evaluate the regulatory role of JcCPI in salinity stress tolerance.
No preview · Article · Sep 2015 · Electronic Journal of Biotechnology
[Show abstract][Hide abstract] ABSTRACT: Triterpenoids are multifunctional secondary metabolites in plants. But little information is available concerning the actual yield, optimal extraction method and pharmacologic activity with regard to triterpenoids from Jatropha curcas leaves (TJL). Hence, response surface methodology (RSM) was used to optimize the extraction parameters. The effects of three independent variables, namely liquid-to-solid ratio, ethanol concentration and extraction time on TJL yield were investigated. TJL obtained by silica column chromatography was tested against bacterial and fungal species relevant to oral disease and wounds through broth microdilution. Antioxidant activity was assessed using the 2,2-diphenyl-2-picrylhydrazyl and 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) assays.
Preview · Article · Jan 2015 · Electronic Journal of Biotechnology
[Show abstract][Hide abstract] ABSTRACT: Gastric cancer is one of the most prevalent and aggressive cancers worldwide, and its molecular mechanism remains largely elusive. Here we report the genomic landscape in primary gastric adenocarcinoma of human, based on the complete genome sequences of five pairs of cancer and matching normal samples. In total, 103,464 somatic point mutations, including 407 non-synonymous ones, were identified and the most recurrent mutations were harbored by Mucins (MUC3A and MUC12) and transcription factors (ZNF717, ZNF595 and TP53). 679 genomic rearrangements were detected, which affect 355 protein-coding genes; and 76 genes show copy number changes. Through mapping the boundaries of the rearranged regions to the folded three-dimensional structure of human chromosomes, we determined that 79.6% of the chromosomal rearrangements happen among DNA fragments in close spatial proximity, especially when two endpoints stay in a similar replication phase. We demonstrated evidences that microhomology-mediated break induced replication was utilized as a mechanism in inducing ~40.9% of the identified genomic changes in gastric tumor. Our data analyses revealed potential integrations of Helicobacter pylori DNA into the gastric cancer genomes. Overall a large set of novel genomic variations were detected in these gastric cancer genomes, which may be essential to the study of the genetic basis and molecular mechanism of the gastric tumorigenesis. This article is protected by copyright. All rights reserved.
Full-text · Article · Dec 2014 · International Journal of Cancer
[Show abstract][Hide abstract] ABSTRACT: Background
Jatropha curcas is a rich reservoir of pharmaceutically active terpenoids. More than 25 terpenoids have been isolated from this plant, and their activities are anti-bacterial, anti-fungal, anti-cancer, insecticidal, rodenticidal, cytotoxic and molluscicidal. But not much is known about the pathway involved in the biosynthesis of terpenoids. The present investigation describes the cloning, characterization and subcellular localization of isopentenyl diphosphate isomerase (IPI) gene from J. curcas. IPI is one of the rate limiting enzymes in the biosynthesis of terpenoids, catalyzing the crucial interconversion of isopentenyl diphosphate (IPP) and dimethylallyl diphosphate (DMAPP).
A full-length JcIPI cDNA consisting of 1355 bp was cloned. It encoded a protein of 305 amino acids. Analysis of deduced amino acid sequence predicted the presence of conserved active sites, metal binding sites and the NUDIX motif, which were consistent with other IPIs. Phylogenetic analysis indicated a significant evolutionary relatedness with Ricinus communis. Southern blot analysis showed the presence of an IPI multigene family in J. curcas. Comparative expression analysis of tissue specific JcIPI demonstrated the highest transcript level in flowers. Abiotic factors could induce the expression of JcIPI. Subcellular distribution showed that JcIPI was localized in chloroplasts.
This is the first report of cloning and characterization of IPI from J. curcas. Our study will be of significant interest to understanding the regulatory role of IPI in the biosynthesis of terpenoids, although its function still needs further confirmation.
Preview · Article · Nov 2014 · Electronic Journal of Biotechnology
[Show abstract][Hide abstract] ABSTRACT: Increased flux through the hexosamine biosynthetic pathway and the corresponding increase in intracellular glycosylation of proteins via O-linked β-N-acetylglucosamine (O-GlcNAc) is sufficient to induce insulin resistance (IR) in multiple systems. Previously, our group used shotgun proteomics to identify multiple rodent adipocytokines and secreted proteins whose levels are modulated upon the induction of IR by indirectly and directly modulating O-GlcNAc levels. We have validated the relative levels of several of these factors using immunoblotting. Since adipocytokines levels are regulated primarily at the level of transcription and O-GlcNAc alters the function of many transcription factors, we hypothesized that elevated O-GlcNAc levels on key transcription factors are modulating secreted protein expression. Here, we show that upon the elevation of O-GlcNAc levels and the induction of IR in mature 3T3-F442a adipocytes, the transcript levels of multiple secreted proteins reflect the modulation observed at the protein level. We validate the transcript levels in male mouse models of diabetes. Using inguinal fat pads from the severely IR db/db mouse model and the mildly IR diet-induced mouse model, we have confirmed that the secreted proteins regulated by O-GlcNAc modulation in cell culture are likewise modulated in the whole animal upon a shift to IR. By comparing the promoters of similarly regulated genes, we determine that Sp1 is a common cis-acting element. Furthermore, we show that the LPL and SPARC promoters are enriched for Sp1 and O-GlcNAc modified proteins during insulin resistance in adipocytes. Thus, the O-GlcNAc modification of proteins bound to promoters, including Sp1, is linked to adipocytokine transcription during insulin resistance.
Preview · Article · Nov 2014 · Frontiers in Endocrinology
[Show abstract][Hide abstract] ABSTRACT: A computational analysis of genome-scale transcriptomic data collected on ∼1,700 tissue samples of three cancer types: breast carcinoma, colon adenocarcinoma and lung adenocarcinoma, revealed that each tissue consists of (at least) two major subpopulations of cancer cells with different capabilities to handle fluctuating O2 levels. The two populations have distinct genomic and transcriptomic characteristics, one accelerating its proliferation under hypoxic conditions and the other proliferating faster with higher O2 levels, referred to as the hypoxia and the reoxygenation subpopulations, respectively. The proportions of the two subpopulations within a cancer tissue change as the average O2 level changes. They both contribute to cancer development but in a complementary manner. The hypoxia subpopulation tends to have higher proliferation rates than the reoxygenation one as well as higher apoptosis rates; and it is largely responsible for the acidic environment that enables tissue invasion and provides protection against attacks from T-cells. In comparison, the reoxygenation subpopulation generates new extracellular matrices in support of further growth of the tumor and strengthens cell-cell adhesion to provide scaffolds to keep all the cells connected. This subpopulation also serves as the major source of growth factors for tissue growth. These data and observations strongly suggest that these two major subpopulations within each tumor work together in a conjugative relationship to allow the tumor to overcome stresses associated with the constantly changing O2 level due to repeated growth and angiogenesis. The analysis results not only reveal new insights about the population dynamics within a tumor but also have implications to our understanding of possible causes of different cancer phenotypes such as diffused versus more tightly connected tumor tissues.
[Show abstract][Hide abstract] ABSTRACT: Pancreatic cancer is the deadliest of all cancers with worst outcome and poor survival rate. Chemotherapy with gemcitabine works well for early stage cancer, but becomes ineffective for advanced-stage cancer. As such, there is a dire need for new approaches to treat this cancer. The metabolism of tumor cells is very different from that of normal cells. In particular, the differences in amino acid metabolism are gaining increasing attention in cancer biology. Selective amino acid transporters are upregulated in cancer in response to the increased demands for amino acids in tumor cells. Such tumor-selective amino acid transporters are logical druggable targets for cancer therapy. As such, pharmacologic blockade of such upregulated transporters would lead to cell death selectively in tumor cells by depriving the tumor cells of essential nutrients. With this in mind, we analyzed 8 different publically available microarray datasets in Gene Expression Omnibus for the amino acid transporters that are upregulated
[Show abstract][Hide abstract] ABSTRACT: Essential proteins are those that are indispensable to cellular survival and development. Existing methods for essential protein identification generally rely on knock-out experiments and/or the relative density of their interactions (edges) with other proteins in a Protein-Protein Interaction (PPI) network. Here, we present a computational method, called EW, to first rank protein-protein interactions in terms of their Edge Weights, and then identify sub-PPI-networks consisting of only the highly-ranked edges and predict their proteins as essential proteins. We have applied this method to publicly-available PPI data on Saccharomyces cerevisiae (Yeast) and Escherichia coli (E. coli) for essential protein identification, and demonstrated that EW achieves better performance than the state-of-the-art methods in terms of the precision-recall and Jackknife measures. The highly-ranked protein-protein interactions by our prediction tend to be biologically significant in both the Yeast and E. coli PPI networks. Further analyses on systematically perturbed Yeast and E. coli PPI networks through randomly deleting edges demonstrate that the proposed method is robust and the top-ranked edges tend to be more associated with known essential proteins than the lowly-ranked edges.
[Show abstract][Hide abstract] ABSTRACT: The availability of a large number of sequenced bacterial genomes facilitates in-depth studies about why genes (operons) in a bacterial genome are globally organized the way they are. We have previously discovered that (the relative) transcription- activation frequencies among different biological pathways encoded in a genome have a dominating role in the global arrangement of operons. One complicating factor in such a study is that some operons may be involved in multiple pathways with different activation frequencies. A quantitative model has been developed that captures this information, which tends to be minimized by the current global arrangement of operons in a bacterial (and archaeal) genome compared to possible alternative arrangements. A study is carried out here using this model on a collection of 52 closely related E. coli genomes, which revealed interesting new insights about how bacterial genomes evolve to optimally adapt to their environments through adjusting the (relative) genomic locations of the encoding operons of biological pathways once their utilization and hence transcription activation frequencies change, to maintain the above energy-efficiency property. More specifically we observed that it is the frequencies of the transcription activation of pathways relative to those of the other encoded pathways in an organism as well as the variation in the activation frequencies of a specific pathway across the related genomes that play a key role in the observed commonalities and differences in the genomic organizations of genes (and operons) encoding specific pathways across different genomes.