Structural characteristics of genomic islands associated with GMP synthases as integration hotspot among sequenced microbial genomes

2012 ◽  
Vol 36 ◽  
pp. 62-70 ◽  
Author(s):  
Lei Song ◽  
Yuting Pan ◽  
Sihong Chen ◽  
Xuehong Zhang
Keyword(s):  
Structural Characteristics ◽  
Genomic Islands ◽  
Microbial Genomes

The Comparative Analysis of Two Homologous Genomic Islands Associated with the Noncoding Sequence in Enterobacter cloacae

2013 ◽  
Vol 448-453 ◽  
pp. 3-6
Author(s):  
Jiao Zhang ◽  
Lei Song
Keyword(s):  
Structural Characteristics ◽  
Enterobacter Cloacae ◽  
Protein Assembly ◽  
Genomic Islands ◽  
Noncoding Sequence ◽  
Flanking Sequence ◽  
Hypothetical Gene ◽  
Evolution Pattern ◽  
Bacteriophage P2 ◽  
Coat Protein Assembly

The genomic islands (GIs) are usually the products of horizontal gene transfer (HGT) that is evolution pattern in prokaryote. Two homologous GIs (WSU1GINoand KU01GINo) containing the homologous integrase of Bacteriophage P2 were determined inEnterobacter cloacaethrough flanking sequence alignment of the homologous integrase. The homologous GIs were integrated into the noncoding sequence. Their common flanking sequence is 5-AAGGCTCCCTCAGGAGC-3, and their integrases share 97% similarity. About two-thirds of the nucleotide sequences between WSU1GINoand KU01GINoare highly similar. The different regions between WSU1GINoand KU01GINomainly include hypothetical gene, Phage-related tail gene, capsid gene, and baseplate assembly gene. In conclusion, the tandem arrangement of WSU1GINoand KU01GINowill be artificially constructed because of their similar structural characteristics, and phage coat protein assembly will also be analyzed.

scholarly journals Microbial genomic island discovery, visualization and analysis

2018 ◽  
Vol 20 (5) ◽  
pp. 1685-1698 ◽  
Author(s):  
Claire Bertelli ◽  
Keith E Tilley ◽  
Fiona S L Brinkman
Keyword(s):  
Gene Transfer ◽  
Large Scale ◽  
Disease Outbreaks ◽  
Genomic Islands ◽  
Data Set ◽  
Microbial Genomes ◽  
Sequence Composition ◽  
Major Mechanism ◽  
Genomic Epidemiology ◽  
Antimicrobial Resistance Genes

Abstract Horizontal gene transfer (also called lateral gene transfer) is a major mechanism for microbial genome evolution, enabling rapid adaptation and survival in specific niches. Genomic islands (GIs), commonly defined as clusters of bacterial or archaeal genes of probable horizontal origin, are of particular medical, environmental and/or industrial interest, as they disproportionately encode virulence factors and some antimicrobial resistance genes and may harbor entire metabolic pathways that confer a specific adaptation (solvent resistance, symbiosis properties, etc). As large-scale analyses of microbial genomes increases, such as for genomic epidemiology investigations of infectious disease outbreaks in public health, there is increased appreciation of the need to accurately predict and track GIs. Over the past decade, numerous computational tools have been developed to tackle the challenges inherent in accurate GI prediction. We review here the main types of GI prediction methods and discuss their advantages and limitations for a routine analysis of microbial genomes in this era of rapid whole-genome sequencing. An assessment is provided of 20 GI prediction software methods that use sequence-composition bias to identify the GIs, using a reference GI data set from 104 genomes obtained using an independent comparative genomics approach. Finally, we present guidelines to assist researchers in effectively identifying these key genomic regions.

scholarly journals Linking pangenomes and metagenomes: the Prochlorococcus metapangenome

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4320 ◽  
Author(s):  
Tom O. Delmont ◽  
A. Murat Eren
Keyword(s):  
Sugar Metabolism ◽  
Gene Clusters ◽  
Genomic Islands ◽  
Metagenomic Data ◽  
Integrated Analysis ◽  
Marker Genes ◽  
Relative Distribution ◽  
Environmental Distribution ◽  
Microbial Genomes ◽  
Core Genes

Pangenomes offer detailed characterizations of core and accessory genes found in a set of closely related microbial genomes, generally by clustering genes based on sequence homology. In comparison, metagenomes facilitate highly resolved investigations of the relative distribution of microbial genomes and individual genes across environments through read recruitment analyses. Combining these complementary approaches can yield unique insights into the functional basis of microbial niche partitioning and fitness, however, advanced software solutions are lacking. Here we present an integrated analysis and visualization strategy that provides an interactive and reproducible framework to generate pangenomes and to study them in conjunction with metagenomes. To investigate its utility, we applied this strategy to a Prochlorococcus pangenome in the context of a large-scale marine metagenomic survey. The resulting Prochlorococcus metapangenome revealed remarkable differential abundance patterns between very closely related isolates that belonged to the same phylogenetic cluster and that differed by only a small number of gene clusters in the pangenome. While the relationships between these genomes based on gene clusters correlated with their environmental distribution patterns, phylogenetic analyses using marker genes or concatenated single-copy core genes did not recapitulate these patterns. The metapangenome also revealed a small set of core genes that mostly occurred in hypervariable genomic islands of the Prochlorococcus populations, which systematically lacked read recruitment from surface ocean metagenomes. Notably, these core gene clusters were all linked to sugar metabolism, suggesting potential benefits to Prochlorococcus from a high sequence diversity of sugar metabolism genes. The rapidly growing number of microbial genomes and increasing availability of environmental metagenomes provide new opportunities to investigate the functioning and the ecology of microbial populations, and metapangenomes can provide unique insights for any taxon and biome for which genomic and sufficiently deep metagenomic data are available.

Structural characteristics of genomic islands associated withRlmHgenes inBacillus

2017 ◽  
pp. 263-268
Author(s):  
Lingwei Su ◽  
Xuan Peng ◽  
Qingze Zha ◽  
Shidan He ◽  
Mengjie Yang ◽  
...  
Keyword(s):  
Structural Characteristics ◽  
Genomic Islands

The Structural Characteristics and Function Analysis of the Mobile Genomic Islands Flanked by Isocitrate Dehydrogenase Genes in Escherichia coli and Salmonella enterica

2012 ◽  
Vol 482-484 ◽  
pp. 2218-2222
Author(s):  
Lei Song ◽  
Xue Hong Zhang
Keyword(s):  
Escherichia Coli ◽  
Isocitrate Dehydrogenase ◽  
Salmonella Enterica ◽  
Function Analysis ◽  
Structural Characteristics ◽  
Genomic Islands ◽  
Transposase Gene ◽  
Integrase Gene ◽  
Mobile Gene ◽  
And Function

Eleven genomic islands (GIs) flanked by isocitrate dehydrogenase genes are determined in Escherichia coli and Salmonella enterica. These GIs have at least one mobile gene, such as integrase gene, transposase gene or recombinase gene. Through annotation of internal genes, these GIs are related to lambda prophage. The excisionase gene is associated with the mobile gene in some GIs. An ABC transporter, namely, sitABCD operon, is existed in some GIs and may uptake Fe2+ and Mn2+. Mn2+ is a second cofactor and an essential activator of the isocitrate dehydrogenase. The cleavage site of functional lambda integrase is 5’-TGCTGCGCCA-3’ in direct repeats at 3’-end of icd gene.The truncated lambda integrases (ECP_1132 and ECP_1135) are inactive because the transposon inserted the integrase gene by 5’-CCTGG-3’. This Fe2+/Mn2+ transport operon is predicted that is a recent product of horizontal gene transfer in E. coli because this operon is also existed in S. enterica and is not in a mobile GIs.

GI-Cluster: Detecting genomic islands via consensus clustering on multiple features

2018 ◽  
Vol 16 (03) ◽  
pp. 1840010 ◽  
Author(s):  
Bingxin Lu ◽  
Hon Wai Leong
Keyword(s):  
Medical Research ◽  
Supervised Learning ◽  
Genome Evolution ◽  
Computational Methods ◽  
Genomic Islands ◽  
Consensus Clustering ◽  
Multiple Features ◽  
Microbial Genomes ◽  
Comprehensive Evaluations ◽  
Genome Annotations

The accurate detection of genomic islands (GIs) in microbial genomes is important for both evolutionary study and medical research, because GIs may promote genome evolution and contain genes involved in pathogenesis. Various computational methods have been developed to predict GIs over the years. However, most of them cannot make full use of GI-associated features to achieve desirable performance. Additionally, many methods cannot be directly applied to newly sequenced genomes. We develop a new method called GI-Cluster, which provides an effective way to integrate multiple GI-related features via consensus clustering. GI-Cluster does not require training datasets or existing genome annotations, but it can still achieve comparable or better performance than supervised learning methods in comprehensive evaluations. Moreover, GI-Cluster is widely applicable, either to complete and incomplete genomes or to initial GI predictions from other programs. GI-Cluster also provides plots to visualize the distribution of predicted GIs and related features. GI-Cluster is available at https://github.com/icelu/GI_Cluster.

A High Resolution Study of G.P. Zones in Aluminum - 4.2 at % Silver

1982 ◽  
Vol 40 ◽  
pp. 722-723 ◽  
Author(s):  
R. Gronsky
Keyword(s):  
Electron Microscopy ◽  
Transmission Electron Microscopy ◽  
High Resolution ◽  
Computer Simulations ◽  
Structural Characteristics ◽  
X Ray Diffraction ◽  
X Ray ◽  
Transmission Electron ◽  
Resolution Study

The phenomenon of clustering in Al-Ag alloys has been extensively studied since the early work of Guinierl, wherein the pre-precipitation state was characterized as an assembly of spherical, ordered, silver-rich G.P. zones. Subsequent x-ray and TEM investigations yielded results in general agreement with this model. However, serious discrepancies were later revealed by the detailed x-ray diffraction - based computer simulations of Gragg and Cohen, i.e., the silver-rich clusters were instead octahedral in shape and fully disordered, atleast below 170°C. The object of the present investigation is to examine directly the structural characteristics of G.P. zones in Al-Ag by high resolution transmission electron microscopy.

SEM analysis of the change in the reaction rates with deposit structures in the copper-iron cementation system

1978 ◽  
Vol 36 (1) ◽  
pp. 456-457
Author(s):  
V. Annamalai ◽  
L.E. Murr
Keyword(s):  
Structural Characteristics ◽  
Secondary Electron Emission ◽  
Copper Deposit ◽  
Reaction Rates ◽  
Sem Analysis ◽  
Experimental Conditions ◽  
Major Drawback ◽  
Emission Mode ◽  
Scrap Iron ◽  
Image Position

Economical recovery of copper metal from leach liquors has been carried out by the simple process of cementing copper onto a suitable substrate metal, such as scrap-iron, since the 16th century. The process has, however, a major drawback of consuming more iron than stoichiometrically needed by the reaction.Therefore, many research groups started looking into the process more closely. Though it is accepted that the structural characteristics of the resultant copper deposit cause changes in reaction rates for various experimental conditions, not many systems have been systematically investigated. This paper examines the deposit structures and the kinetic data, and explains the correlations between them.A simple cementation cell along with rotating discs of pure iron (99.9%) were employed in this study to obtain the kinetic results The resultant copper deposits were studied in a Hitachi Perkin-Elmer HHS-2R scanning electron microscope operated at 25kV in the secondary electron emission mode.

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