MultiFun, a Multifunctional Classification Scheme for<i>Escherichia coli</i>K-12 Gene Products

Serres, Margrethe H.; Riley, Matilda White

doi:10.1089/mcg.2000.5.205

Cited by 93 publications

(95 citation statements)

References 20 publications

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“…The maximum pattern density in GC/AT content in this range occurred at the 74-kb period, containing eight localized patterns. Six of these eight pattern-rich segments were found to be significantly enriched (hypergeometric p < 0.001) with genes belonging to particular functional classes [28], which included prophage-related genes and genes encoding membrane-associated proteins (flagellar, energy production and transport, and cell-surface antigens). The enrichment of patterned regions with genes of extrachromosomal origin implies a preferred regularity in chromosome structure and nucleotide content that facilitates foreign DNA incorporation.…”

Section: Resultsmentioning

confidence: 99%

“…The analysis of additional data from E. coli K-12 MG1655 included sequence-derived biophysical parameters averaged across 1-kb segments [12], gene classifications and product locations [28], gene expression [17], gene essentiality [24], and evolutionary retention indices computed based upon homology with 32 representative bacterial sequences [24]. …”

Section: Methodsmentioning

confidence: 99%

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Long-Range Periodic Patterns in Microbial Genomes Indicate Significant Multi-Scale Chromosomal Organization

et al. 2006

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Genome organization can be studied through analysis of chromosome position-dependent patterns in sequence-derived parameters. A comprehensive analysis of such patterns in prokaryotic sequences and genome-scale functional data has yet to be performed. We detected spatial patterns in sequence-derived parameters for 163 chromosomes occurring in 135 bacterial and 16 archaeal organisms using wavelet analysis. Pattern strength was found to correlate with organism-specific features such as genome size, overall GC content, and the occurrence of known motility and chromosomal binding proteins. Given additional functional data for Escherichia coli, we found significant correlations among chromosome position dependent patterns in numerous properties, some of which are consistent with previously experimentally identified chromosome macrodomains. These results demonstrate that the large-scale organization of most sequenced genomes is significantly nonrandom, and, moreover, that this organization is likely linked to genome size, nucleotide composition, and information transfer processes. Constraints on genome evolution and design are thus not solely dependent upon information content, but also upon an intricate multi-parameter, multi-length-scale organization of the chromosome.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Long-Range Periodic Patterns in Microbial Genomes Indicate Significant Multi-Scale Chromosomal Organization

et al. 2006

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“…For the functional classification we relied on the MultiFun Classification System (Serres and Riley 2000) as implemented by MaGe (Vallenet et al 2006). Due to manual annotation efforts of our group, this database contains high-quality functional assignments for all C. metallidurans CH34 genes (Janssen et al 2010).…”

Section: Functional Classificationmentioning

confidence: 99%

Heavy metal resistance in Cupriavidus metallidurans CH34 is governed by an intricate transcriptional network

et al. 2011

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The soil bacterium Cupriavidus metallidurans CH34 contains a high number of heavy metal resistance genes making it an interesting model organism to study microbial responses to heavy metals. In this study the transcriptional response of strain CH34 was measured when challenged to sub-lethal concentrations of various essential or toxic metals. Based on the global transcriptional responses for each challenge and the overlap in upregulated genes between different metal responses, the sixteen metals were clustered in three groups. In addition, the transcriptional response of already known metal resistance genes was assessed, and new metal response gene clusters were identified. The majority of the studied metal response loci showed similar expression profiles when cells were exposed to different metals, suggesting complex interplay at transcriptional level between the different metal responses. The pronounced redundancy of these metal resistant regions-as illustrated by the large number of paralogous genes-combined with the phylogenetic distribution of these metal response regions within either evolutionary related or other metal resistant bacteria, provides important insights on the recent evolutionary forces shaping this naturally soil-dwelling bacterium into a highly metal-resistant strain well adapted to harsh and anthropogenic environments.

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“…These changes in rate differ considerably between individual proteins and between protein categories. The most pronounced differences, after grouping of the members of the proteome of E. coli in the MultiFun[44] …”

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confidence: 99%

Time-series analysis of the transcriptome and proteome of Escherichia coli upon glucose repression

Borirak

Rolfe

Koning

et al. 2015

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics

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Time-series transcript- and protein-profiles were measured upon initiation of carbon catabolite repression in Escherichia coli, in order to investigate the extent of post-transcriptional control in this prototypical response. A glucose-limited chemostat culture was used as the CCR-free reference condition. Stopping the pump and simultaneously adding a pulse of glucose, that saturated the cells for at least 1h, was used to initiate the glucose response. Samples were collected and subjected to quantitative time-series analysis of both the transcriptome (using microarray analysis) and the proteome (through a combination of 15N-metabolic labeling and mass spectrometry). Changes in the transcriptome and corresponding proteome were analyzed using statistical procedures designed specifically for time-series data. By comparison of the two sets of data, a total of 96 genes were identified that are post-transcriptionally regulated. This gene list provides candidates for future in-depth investigation of the molecular mechanisms involved in post-transcriptional regulation during carbon catabolite repression in E. coli, like the involvement of small RNAs.

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MultiFun, a Multifunctional Classification Scheme forEscherichia coliK-12 Gene Products

Cited by 93 publications

References 20 publications

Long-Range Periodic Patterns in Microbial Genomes Indicate Significant Multi-Scale Chromosomal Organization

Long-Range Periodic Patterns in Microbial Genomes Indicate Significant Multi-Scale Chromosomal Organization

Heavy metal resistance in Cupriavidus metallidurans CH34 is governed by an intricate transcriptional network

Time-series analysis of the transcriptome and proteome of Escherichia coli upon glucose repression

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