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Introduction: Crohn's disease (CD) is a chronic inflammatory disease. Approximately 50% of patients with CD progressed from inflammation to fibrosis. Currently, there are no effective drugs for treating intestinal fibrosis. Biologic therapies for CD such as ustekinumab have benefited patients; however, up to 30% of patients with CD have no response to initial treatment, and the effect of ustekinumab on intestinal fibrosis is still uncertain. Therefore, it is of great significance to explore the predictive factors of ustekinumab treatment response and the effect of ustekinumab on intestinal fibrosis. Materials and methods: Public datasets--GSE207465 (blood samples) and GSE112366 and GSE207022 (intestinal samples)--were downloaded and analyzed individually (unmerged) based on the treatment response. Differentially expressed genes (DEGs) were identified by the "limma" R package and changes in immune cell infiltration were determined by the "CIBERSORT" R package in both blood and intestinal samples at week 0 (before treatment). To find predictive factors of ustekinumab treatment response, the weighted gene co-expression network analysis (WGCNA) R package was used to identify hub genes in GSE112366. Hub genes were then verified in GSE207022, and a prediction model was built by random forest algorithm. Furthermore, fibrosisrelated gene changes were analyzed in ileal samples before and after treatment with ustekinumab. Results: (1) Our analysis found that MUC1, DUOX2, LCN2, and PDZK1IP1 were hub genes in GSE112366. GSE207022 revealed that MUC1 (AUC:0.761), LCN2 (AUC:0.79), and PDZK1IP1 (AUC:0.731) were also lower in the response group. Moreover, the random forest model was shown to have strong predictive capabilities in identifying responders (AUC = 0.875). To explore the relationship between intestinal tissue and blood, we found that ITGA4 had lower expression in the intestinal and blood samples of responders. The expression of IL18R1 is also lower in responders' intestines. IL18, the ligand of IL18R1, was also found to have lower expression in the blood samples from responders vs. non-responders. (2) GSE112366 revealed a significant decrease in fibrosis-related module genes (COL4A1, TUBB6, IFITM2, SERPING1, DRAM1, NAMPT, MMP1, ZEB2, ICAM1, PFKFB3, and ACTA2) and fibrosis-related pathways (ECM-receptor interaction and PI3K-AKT pathways) after ustekinumab treatment. Conclusion: MUC1, LCN2, and PDZK1IP1 were identified as hub genes in intestinal samples, with lower expression indicating a positive prediction of ustekinumab treatment response. Moreover, ITGA4 and IL18/IL18R1 may be involved in the treatment response in blood and intestinal samples. Finally, ustekinumab treatment was shown to significantly alter fibrotic genes and pathways. [ABSTRACT FROM AUTHOR]

Obtaining new grapevine varieties with unique aromas has been a long-standing goal of breeders. Norisoprenoids are of particular interest to wine producers and researchers, as these compounds are responsible for the important varietal aromas in wine, characterized by a complex floral and fruity smell, and are likely present in all grape varieties. However, the single-nucleotide polymorphism (SNP) loci and candidate genes genetically controlling the norisoprenoid content in grape berry remain unknown. To this end, in this study, we investigated 13 norisoprenoid traits across two years in an F1 population consisting of 149 individuals from a hybrid of Vitis vinifera L. cv. Muscat Alexandria and V. vinifera L. cv. Christmas Rose. Based on 568,953 SNP markers, genome-wide association analysis revealed that 27 candidate SNP loci belonging to 18 genes were significantly associated with the concentrations of norisoprenoid components in grape berry. Among them, 13 SNPs were confirmed in a grapevine germplasm population comprising 97 varieties, including two non-synonymous mutations SNPs within the VvDXS1 and VvGGPPS genes, respectively in the isoprenoid metabolic pathway. Genotype analysis showed that the grapevine individuals with the heterozygous genotype C/T at chr5:2987350 of VvGGPPS accumulated higher average levels of 6- methyl-5-hepten-2-one and b-cyclocitral than those with the homozygous genotype C/C. Furthermore, VvGGPPS was highly expressed in individuals with high norisoprenoids concentrations. Transient overexpression of VvGGPPS in the leaves of Vitis quinquangularis and tobacco resulted in an increase in norisoprenoid concentrations. These findings indicate the importance of VvGGPPS in the genetic control of norisoprenoids in grape berries, serving as a potential molecular breeding target for aroma. [ABSTRACT FROM AUTHOR]

α-Synuclein misfolding and aggregation play an important role in the pathogenesis of Parkinson's disease (PD). Loss of function and mutation of the PARK7/DJ-1 gene cause early-onset familial PD. DJ-1 can inhibit α-synuclein aggregation, and may function at an early step in the aggregation process. Soluble wild-type (WT) α-synuclein is mainly degraded by chaperone-mediated autophagy (CMA), and impairment of CMA is closely related to the pathogenesis of PD. Here, we investigated whether DJ-1 could reduce α-synuclein accumulation and aggregation by CMA. DJ-1 knockout mice and DJ-1 siRNA knockdown SH-SY5Y cells were used to investigate the potential mechanisms underlying the relationship between DJ-1 deficiency and α-synuclein aggregation. First, we confirmed that DJ-1 deficiency increased the accumulation and aggregation of α-synuclein in both SH-SY5Y cells and PD animal models, and overexpression of DJ-1 in vitro effectively decreased α-synuclein levels. α-Synuclein overexpression activated CMA by elevating the levels of lysosome-associated membrane protein type-2A (LAMP2A), but DJ-1 deficiency suppressed upregulation of LAMP2A. DJ-1 deficiency downregulated the level of lysosomal 70 kDa heat-shock cognate protein (HSC70) but not the levels of that in homogenates. Further studies showed that DJ-1 deficiency accelerated the degradation of LAMP2A in lysosomes, leading to the aggregation of α-synuclein. Our study suggests that DJ-1 deficiency aggravates α-synuclein aggregation by inhibiting the activation of CMA and provides further evidence of the molecular interaction between PD-related proteins via the CMA pathway. [ABSTRACT FROM AUTHOR]

We present a web-based network-construction system, CINPER (CSBL INteractive Pathway BuildER), to assist a user to build a user-specified gene network for a prokaryotic organism in an intuitive manner. CINPER builds a network model based on different types of information provided by the user and stored in the system. CINPER's prediction process has four steps: (i) collection of template networks based on (partially) known pathways of related organism(s) from the SEED or BioCyc database and the published literature; (ii) construction of an initial network model based on the template networks using the P-Map program; (iii) expansion of the initial model, based on the association information derived from operons, proteinprotein interactions, co-expression modules and phylogenetic profiles; and (iv) computational validation of the predicted models based on gene expression data. To facilitate easy applications, CINPER provides an interactive visualization environment for a user to enter, search and edit relevant data and for the system to display (partial) results and prompt for additional data. Evaluation of CINPER on 17 well-studied pathways in the MetaCyc database shows that the program achieves an average recall rate of 76% and an average precision rate of 90% on the initial models; and a higher average recall rate at 87% and an average precision rate at 28% on the final models. The reduced precision rate in the final models versus the initial models reflects the reality that the final models have large numbers of novel genes that have no experimental evidences and hence are not yet collected in the MetaCyc database. To demonstrate the usefulness of this server, we have predicted an iron homeostasis gene network of Synechocystis sp. PCC6803 using the server. The predicted models along with the server can be accessed at http://csbl.bmb.uga.edu/cinper/. [ABSTRACT FROM AUTHOR]

Methamphetamine (METH) causes memory changes, but the underlying mechanisms are poorly understood. Epigenetic mechanisms, including DNA methylation, can potentially cause synaptic changes in the brain. Oxytocin (OT) plays a central role in learning and memory, but little is known of the impact of OT on METH-associated memory changes. Here, we explored the role of OT in METH-induced epigenetic alterations that underlie spatial and cognitive memory changes. METH (2.0 mg/kg, i.p.) was administered to male C57BL/6 mice once every other day for 8 days. OT (2.5 μg, i.c.v.) or aCSF was given prior to METH. Spatial and cognitive memory were assessed. In Hip and PFC, synaptic structures and proteins were examined, levels of DNA methyltransferases (DNMTs) and methyl CpG binding protein 2 (MECP2) were determined, and the DNA methylation status at the Synaptophysin (Syn) promoter was assessed. METH enhanced spatial memory, decreased synapse length, downregulated DNMT1, DNMT3A, DNMT3B, and MECP2, and induced DNA hypomethylation at the Syn promoter in Hip. In contrast, METH reduced cognitive memory, increased synapse thickness, upregulated DNMT1, DNMT3A, and MECP2, and induced DNA hypermethylation at the Syn promoter in PFC. OT pretreatment specifically ameliorated METH-induced learning and memory alterations, normalized synapse structures, and regulated DNMTs and MECP2 to reverse the DNA methylation status changes at the Syn promoter in Hip and PFC. DNA methylation is an important gene regulatory mechanism underlying METH-induced learning and memory alterations. OT can potentially be used to specifically manipulate METH-related memory changes. [ABSTRACT FROM AUTHOR]

The vast array of in silico resources and data of high throughput profiling currently available in life sciences research offer the possibility of aiding cancer gene and drug discovery process. Here we propose to take advantage of these resources to develop a tool, TARGETgene, for efficiently identifying mutation drivers, possible therapeutic targets, and drug candidates in cancer. The simple graphical user interface enables rapid, intuitive mapping and analysis at the systems level. Users can find, select, and explore identified target genes and compounds of interest (e.g., novel cancer genes and their enriched biological processes), and validate predictions using user-defined benchmark genes (e.g., target genes detected in RNAi screens) and curated cancer genes via TARGETgene. The high-level capabilities of TARGETgene are also demonstrated through two applications in this paper. The predictions in these two applications were then satisfactorily validated by several ways, including known cancer genes, results of RNAi screens, gene function annotations, and target genes of drugs that have been used or in clinical trial in cancer treatments. TARGETgene is freely available from the Biomedical Simulations Resource web site (http://bmsr.usc.edu/Software/TARGET/TARGET.html). [ABSTRACT FROM AUTHOR]

Background: Biclustering is a powerful technique for identification of co-expressed gene groups under any (unspecified) substantial subset of given experimental conditions, which can be used for elucidation of transcriptionally co-regulated genes. Results: We have previously developed a biclustering algorithm, QUBIC, which can solve more general biclustering problems than previous biclustering algorithms. To fully utilize the analysis power the algorithm provides, we have developed a web server, QServer, for prediction, computational validation and analyses of co-expressed gene clusters. Specifically, the QServer has the following capabilities in addition to biclustering by QUBIC: (i) prediction and assessment of conserved cis regulatory motifs in promoter sequences of the predicted co-expressed genes; (ii) functional enrichment analyses of the predicted co-expressed gene clusters using Gene Ontology (GO) terms, and (iii) visualization capabilities in support of interactive biclustering analyses. QServer supports the biclustering and functional analysis for a wide range of organisms, including human, mouse, Arabidopsis, bacteria and archaea, whose underlying genome database will be continuously updated. Conclusion: We believe that QServer provides an easy-to-use and highly effective platform useful for hypothesis formulation and testing related to transcription co-regulation. [ABSTRACT FROM AUTHOR]

Background: The frequent exchange of genetic material among prokaryotes means that extracting a majority or plurality phylogenetic signal from many gene families, and the identification of gene families that are in significant conflict with the plurality signal is a frequent task in comparative genomics, and especially in phylogenomic analyses. Decomposition of gene trees into embedded quartets (unrooted trees each with four taxa) is a convenient and statistically powerful technique to address this challenging problem. This approach was shown to be useful in several studies of completely sequenced microbial genomes. Results: We present here a web server that takes a collection of gene phylogenies, decomposes them into quartets, generates a Quartet Spectrum, and draws a split network. Users are also provided with various data download options for further analyses. Each gene phylogeny is to be represented by an assessment of phylogenetic information content, such as sets of trees reconstructed from bootstrap replicates or sampled from a posterior distribution. The Quartet Decomposition server is accessible at http://quartets.uga.edu. Conclusions: The Quartet Decomposition server presented here provides a convenient means to perform Quartet Decomposition analyses and will empower users to find statistically supported phylogenetic conflicts. [ABSTRACT FROM AUTHOR]

Background: Identification of the novel genes relevant to plant cell-wall (PCW) synthesis represents a highly important and challenging problem. Although substantial efforts have been invested into studying this problem, the vast majority of the PCW related genes remain unknown. Results: Here we present a computational study focused on identification of the novel PCW genes in Arabidopsis based on the co-expression analyses of transcriptomic data collected under 351 conditions, using a bi-clustering technique. Our analysis identified 217 highly co-expressed gene clusters (modules) under some experimental conditions, each containing at least one gene annotated as PCW related according to the Purdue Cell Wall Gene Families database. These co-expression modules cover 349 known/annotated PCW genes and 2,438 new candidates. For each candidate gene, we annotated the specific PCW synthesis stages in which it is involved and predicted the detailed function. In addition, for the co-expressed genes in each module, we predicted and analyzed their cis regulatory motifs in the promoters using our motif discovery pipeline, providing strong evidence that the genes in each co-expression module are transcriptionally co-regulated. From the all co-expression modules, we infer that 108 modules are related to four major PCW synthesis components, using three complementary methods. Conclusions: We believe our approach and data presented here will be useful for further identification and characterization of PCW genes. All the predicted PCW genes, co-expression modules, motifs and their annotations are available at a web-based database: http://csbl.bmb.uga.edu/publications/materials/shanwang/CWRPdb/index. html. [ABSTRACT FROM AUTHOR]

Objective: The aim of the current study was to investigate which is the most suitable classification for colorectal cancer, log odds of positive lymph nodes (LODDS) classification or the classifications based on the number of positive lymph nodes (pN) and positive lymph node ratio(LNR) in a Chinese single institutional population. Design: Clinicopathologic and prognostic data of 1297 patients with colorectal cancer were retrospectively studied. The log-rank statistics, Cox's proportional hazards model, the Nagelkerke R2 index and a Harrell's C statistic were used. Results: Univariate and three-step multivariate analyses identified that LNR was a significant prognostic factor and LNR classification was superior to both the pN and LODDS classifications. Moreover, the results of the Nagelkerke R2 index (0.130) and a Harrell's C statistic (0.707) of LNR showed that LNR and LODDS classifications were similar and LNR was a little better than the other two classifications. Furthermore, for patients in each LNR classification, prognosis was homologous between those in different pN or LODDS classifications. However, for patients in pN1a, pN1b, LODDS2 and LODDS3 classifications, significant differences in survival were observed among patients in different LNR classifications. Conclusions: For patients with colorectal cancer, the LNR classification is more suitable than pN and LODDS classifications for prognostic assessment in a Chinese single institutional population. [ABSTRACT FROM AUTHOR]

Pathway enrichment analysis represents a key technique for analyzing high-throughput omic data, and it can help to link individual genes or proteins found to be differentially expressed under specific conditions to well-understood biological pathways. We present here a computational tool, SEAS, for pathway enrichment analysis over a given set of genes in a specified organism against the pathways (or subsystems) in the SEED database, a popular pathway database for bacteria. SEAS maps a given set of genes of a bacterium to pathway genes covered by SEED through gene ID and/or orthology mapping, and then calculates the statistical significance of the enrichment of each relevant SEED pathway by the mapped genes. Our evaluation of SEAS indicates that the program provides highly reliable pathway mapping results and identifies more organism-specific pathways than similar existing programs. SEAS is publicly released under the GPL license agreement and freely available at http://csbl.bmb.uga.edu/,xizeng/research/seas/. [ABSTRACT FROM AUTHOR]

Background: Reconstruction of biological pathways is typically done through mapping well-characterized pathways of model organisms to a target genome, through orthologous gene mapping. A limitation of such pathway-mapping approaches is that the mapped pathway models are constrained by the composition of the template pathways, e.g., some genes in a target pathway may not have corresponding genes in the template pathways, the so-called "missing gene" problem. Methods: We present a novel pathway-expansion method for identifying additional genes that are possibly involved in a target pathway after pathway mapping, to fill holes caused by missing genes as well as to expand the mapped pathway model. The basic idea of the algorithm is to identify genes in the target genome whose homologous genes share common operons with homologs of any mapped pathway genes in some reference genome, and to add such genes to the target pathway if their functions are consistent with the cellular function of the target pathway. Results: We have implemented this idea using a graph-theoretic approach and demonstrated the effectiveness of the algorithm on known pathways of E. coli in the KEGG database. On all KEGG pathways containing at least 5 genes, our method achieves an average of 60% positive predictive value (PPV) and the performance is increased with more seed genes added. Analysis shows that our method is highly robust. Conclusions: An effective method is presented to find missing genes in biological pathways of prokaryotes, which achieves high prediction reliability on E. coli at a genome level. Numerous missing genes are found to be related to knwon E. coli pathways, which can be further validated through biological experiments. Overall this method is robust and can be used for functional inference. [ABSTRACT FROM AUTHOR]

A comparative study of public gene-expression data of seven types of cancers (breast, colon, kidney, lung, pancreatic, prostate and stomach cancers) was conducted with the aim of deriving marker genes, along with associated pathways, that are either common to multiple types of cancers or specific to individual cancers. The analysis results indicate that (a) each of the seven cancer types can be distinguished from its corresponding control tissue based on the expression patterns of a small number of genes, e.g., 2, 3 or 4; (b) the expression patterns of some genes can distinguish multiple cancer types from their corresponding control tissues, potentially serving as general markers for all or some groups of cancers; (c) the proteins encoded by some of these genes are predicted to be blood secretory, thus providing potential cancer markers in blood; (d) the numbers of differentially expressed genes across different cancer types in comparison with their control tissues correlate well with the five-year survival rates associated with the individual cancers; and (e) some metabolic and signaling pathways are abnormally activated or deactivated across all cancer types, while other pathways are more specific to certain cancers or groups of cancers. The novel findings of this study offer considerable insight into these seven cancer types and have the potential to provide exciting new directions for diagnostic and therapeutic development. [ABSTRACT FROM AUTHOR]

Background: MicroRNA (miRNA) play an important role in gene expression regulation. At present, the number of annotated miRNA continues to grow rapidly, in part due to advances of high-throughput sequencing techniques. Here, we use deep sequencing to characterize a population of small RNA expressed in human and rhesus macaques brain cortex. Results: Based on a total of more than 150 million sequence reads we identify 197 putative novel miRNA, in humans and rhesus macaques, that are highly conserved among mammals. These putative miRNA have significant excess of conserved target sites in genes' 3'UTRs, supporting their functional role in gene regulation. Additionally, in humans and rhesus macaques respectively, we identify 41 and 22 conserved putative miRNA originating from non-coding RNA (ncRNA) transcripts. While some of these molecules might function as conventional miRNA, others might be harmful and result in target avoidance. Conclusions: Here, we further extend the repertoire of conserved human and rhesus macaque miRNA. Even though our study is based on a single tissue, the coverage depth of our study allows identification of functional miRNA present in brain tissue at background expression levels. Therefore, our study might cover large proportion of the yet unannotated conserved miRNA present in the human genome. [ABSTRACT FROM AUTHOR]

Motivation: The computational identification of non-coding RNA (ncRNA) genes represents one of the most important and challenging problems in computational biology. Existing methods for ncRNA gene prediction rely mostly on homology information, thus limiting their applications to ncRNA genes with known homologues. [ABSTRACT FROM PUBLISHER]

Pandoraea sp. strain MCB032 was isolated as an emerging chlorobenzene degrader from a functionally stable bioreactor where species succession had occurred. In this study, two gene clusters encoding chlorobenzene metabolic functions have been cloned. Within the cbs gene cluster, CbsA and CbsB are similar to the chlorobenzene dioxygenase and the cis-chlorobenzene dihydrodiol dehydrogenase in Ralstonia sp. JS705 and shown to transform chlorobenzene to 3-chlorocatechol. The clc gene cluster shows strong similarity to the clc genes of Ralstonia sp. JS705 and encodes chlorocatechol 1,2-dioxygenase (ClcA) and other enzymes, which catalyze the conversion of chlorocatechol to 3-oxoadipate. The Michaelis constants ( Km) values of ClcA for catechol, 3-methylcatechol and 3-chlorocatechol were determined as 10.0, 8.9 and 3.4 μM, respectively. CbsX, a putative transport protein present in the cbs cluster of strain MCB032 but not in those of other chlorobenzene degraders, shows 76 and 53% identities to two previously identified transport proteins involved in toluene degradation, TbuX from Ralstonia pickettii PKO1 and TodX from Pseudomonas putida F1. The presence of the transport protein in strain MCB032 likely provides a mechanistic explanation for its higher chlorobenzene affinity and may well be the basis for the competitive advantage of this strain in the bioreactor. [ABSTRACT FROM AUTHOR]

The yellow color of the cocoon of the silkworm Bombyx mori is controlled by three genes, Y (Yellow haemolymph), I (Yellow inhibitor) and C (Outer-layer yellow cocoon), which are located on linkage groups 2, 9 and 12, respectively. Taking advantage of a lack of crossing over in females, reciprocal backcrossed F1 (BC1) progeny were used for linkage analysis and mapping of the C gene using silkworm strains C108 and KY, which spin white and yellow cocoons, respectively. DNA was extracted from individual pupae and analyzed for simple sequence repeat (SSR) markers. The C gene was found to be linked to seven SSR markers. All the yellow cocoon individuals from a female heterozygous backcross (BC1 F) showed a heterozygous profile for SSR markers on linkage group 12, whereas individuals with light yellow cocoons showed the homozygous profile of the strain C108. Using a reciprocal heterozygous male backcross (BC1 M), we constructed a linkage map of 36.4 cM with the C gene located at the distal end, and the closest SSR marker at a distance of 13.9 cM. [ABSTRACT FROM AUTHOR]

The dibenzofuran (DF)-degrading bacterium, Janibacter terrae strain XJ-1, was isolated from sediment from East Lake in Wuhan, China. This strain grows aerobically on DF as the sole source of carbon and energy; it has a doubling time of 12 hours at 30°C; and it almost completely degraded 100 mg/L−1 DF in 5 days, producing 2,2′,3-trihydroxybiphenyl, salicylic acid, gentisic acid, and other metabolites. The dbdA (DF dioxygenase) gene cluster in the strain is almost identical to that on a large plasmid in Terrabacter sp. YK3. Unlike Janibacter sp. strain YY-1, XJ-1 accumulates gentisic acid rather than catechol as a final product of DF degradation. [ABSTRACT FROM AUTHOR]

Mapping biological pathways across microbial genomes is a highly important technique in functional studies of biological systems. Existing methods mainly rely on sequence-based orthologous gene mapping, which often leads to suboptimal mapping results because sequence-similarity information alone does not contain sufficient information for accurate identification of orthology relationship. Here we present an algorithm for pathway mapping across microbial genomes. The algorithm takes into account both sequence similarity and genomic structure information such as operons and regulons. One basic premise of our approach is that a microbial pathway could generally be decomposed into a few operons or regulons. We formulated the pathway-mapping problem to map genes across genomes to maximize their sequence similarity under the constraint that the mapped genes be grouped into a few operons, preferably coregulated in the target genome. We have developed an integer-programming algorithm for solving this constrained optimization problem and implemented the algorithm as a computer software program, P-MAP. We have tested P-MAP on a number of known homologous pathways. We conclude that using genomic structure information as constraints could greatly improve the pathway-mapping accuracy over methods that use sequence-similarity information alone. [ABSTRACT FROM AUTHOR]

We established a genetic linkage map employing 518 simple sequence repeat (SSR, or microsatellite) markers for Bombyx mori (silkworm), the economically and culturally important lepidopteran insect as part of an international genomics program. A survey of six representative silkworm strains using 2,500 (CA)n- and (CT)n-based SSR markers revealed 17-24% polymorphism, indicating a high degree of homozygosity resulting from a long history of inbreeding. Twenty-nine SSR linkage groups were established in well characterized Dazao and C108 strains based on genotyping of 189 backcross progeny derived from an Female mated with a C108 female. The clustering was further focused to 28 groups by genotyping 22 backcross progeny derived from an F1 female mated with a C108 male. This set of SSR linkage groups was further assigned to the 28 chromosomes (established linkage groups) of silkworm aided by visible mutations and cleaved amplified polymorphic sequence markers developed from previously mapped genes, cDNA sequences, and cloned random amplified polymorphic DNAs. By integrating a visible mutation p (plain, larval marking) and 29 well conserved genes of insects onto this SSR- based linkage map, a second generation consensus silkworm genetic map with a range of 7-40 markers per linkage group and a total map length of ≈3431.9 cM was constructed and its high efficiency for genotyping and potential application for synteny studies of Lepidoptera and other insects was demonstrated. [ABSTRACT FROM AUTHOR]

Phosphonate utilization by microbes provides a potential source of phosphorus for their growth. Homologous genes for both C–P lyase and phosphonatase degradative pathways are distributed in distantly related bacterial species. The phn gene clusters for the C–P lyase pathway show great structural and compositional variation among organisms, but all contain phnG–phnM genes that are essential for C–P bond cleavage. In the γ-proteobacterium Erwinia carotovora, genes common to phosphonate biosyntheses were found in neighboring positions of those for the C–P lyase degradative pathway and in the same transcriptional direction. A gene encoding a hypothetical protein DUF1045 was found predominantly associated with the phn gene cluster and was predicted functionally related to C–P bond cleavage. Genes for phosphonate degradation are frequently located in close proximity of genes encoding transposases or other mobile elements. Phylogenetic analyses suggest that both degradative pathways have been subject to extensive lateral gene transfers during their evolution. The implications of plasmids and transposition in the evolution of phosphonate degradation are also discussed. [ABSTRACT FROM AUTHOR]

A novel tri-primer polymerase chain reaction method (TP-PCR) was developed for the construction of a fused fpg gene, in which no endonuclease and ligase were used. Instead, two templates and three specifically designed primers were applied. Results showed that pheB and gfp genes, which encodes the catechol 2, 3-dioxygenase and the green fluorescent protein (GFP), respectively, were successfully fused into an fpg gene through the rapid TP-PCR system, indicating that TP-PCR method could be a useful tool for DNA fragment fusion in which no proper endonuclease sites were available. [Copyright &y& Elsevier]

Background: Annotating genomes remains an hazardous task. Mistakes or gaps in such a complex process may occur when relevant knowledge is ignored, whether lost, forgotten or overlooked. This paper exemplifies an approach which could help to ressucitate such meaningful data. Results: We show that a set of closely related sequences which have been annotated as ornithine carbamoyltransferases are actually putrescine carbamoyltransferases. This demonstration is based on the following points : (i) use of enzymatic data which had been overlooked, (ii) rediscovery of a short NH2-terminal sequence allowing to reannotate a wrongly annotated ornithine carbamoyltransferase as a putrescine carbamoyltransferase, (iii) identification of conserved motifs allowing to distinguish unambiguously between the two kinds of carbamoyltransferases, and (iv) comparative study of the gene context of these different sequences. Conclusions: We explain why this specific case of misannotation had not yet been described and draw attention to the fact that analogous instances must be rather frequent. We urge to be especially cautious when high sequence similarity is coupled with an apparent lack of biochemical information. Moreover, from the point of view of genome annotation, proteins which have been studied experimentally but are not correlated with sequence data in current databases qualify as "orphans", just as unassigned genomic open reading frames do. The strategy we used in this paper to bridge such gaps in knowledge could work whenever it is possible to collect a body of facts about experimental data, homology, unnoticed sequence data, and accurate informations about gene context. [ABSTRACT FROM AUTHOR]

We have previously reported the development of a novel genotoxic testing system based on the transcriptional response of the yeast RNR3-lacZ reporter gene to DNA damage. This system appears to be more sensitive than other similar tests in microorganisms, and is comparable with the Ames test. In an effort to further enhance detection sensitivity, we examined the effects of altering major cell wall components on cell permeability and subsequent RNR3-lacZ sensitivity to genotoxic agents. Although inactivation of single CWP genes encoding cell wall mannoproteins had little effect, the simultaneous inactivation of both CWP1 and CWP2 had profound effects on the cell wall structure and permeability. Consequently, the RNR3-lacZ detection sensitivity is markedly enhanced, especially to high molecular weight compounds such as 4-nitroquinoline-N-oxide (> sevenfold) and phleomycin (> 13-fold). In contrast, deletion of genes encoding representative membrane components or membrane transporters had minor effects on cell permeability. We conclude that the yeast cell wall mannoproteins constitute the major barrier to environmental genotoxic agents and that their removal will significantly enhance the sensitivity of RNR-lacZ as well as other yeast-based genotoxic tests. [ABSTRACT FROM AUTHOR]