Dataset Information

Transcription analysis of E. coli processed at persistent and decreasing glucose limitation in a fed-batch cultivation

ABSTRACT: A time series of whole-genome transcription profiling of E. coli K-12 W3110 was performed to study the dynamic physiological response of E. coli K-12 W3110 to limited carbon conditions. cDNA from eight time intervals after glucose limitation, representing different stages of glucose depletion, along with cDNA of an unrestricted growth were hybridized to whole-genome microarrays of E. coli K-12. Glucose concentrations were gradually reduced in a fed-batch cultivation process with constant feeding rate in a bioreactor. Major focus was put on the dynamic changes in the transcription level of genes involved in the central carbon metabolism (glycolysis, pentose phosphate pathway, TCA cycle and glyoxylate shunt), high-affinity glucose transport systems, movement, growth, and stress response. In total, 40 microarrays were hybridized. The data were statistically analysed using the software R (R, 2005) and the Limma package included (Smyth, 2005). The data were normalized “print-tip-loess”. “Multiple hypothesis testing” correction was performed with the method of Benjamini and Hochberg (Benjamini and Hochberg, 1995), which controls the “false discovery rate” (fdr). Genes were regarded as differentially expressed when the “adjusted p values” were < 0.05, therefore nominally controlling the expected fdr to less than 0.05. The reproducibility of dye swap experiments as well as biological replicates was estimated by calculating “Pearson’s correlation coefficients”. A high correlation was observed for the dye swap pairs (with averaged Pearson’s correlation coefficients of 0.89 ± 0.06 for the reference samples and of 0.87 ± 0.08 for the different points of time) as well as for biological replicates (with averaged Pearson’s correlation coefficients of 0.86 ± 0.04 for the red channel (Cy5) and 0.80 ± 0.09 for the green channel (Cy3)). Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc B 57, 289-300. Smyth, G.K. (2005). Limma: Linear models for microarray data. In Bioinformatics and Computational Biology Solutions using R and Bioconductor, R. Gentleman, Carrey, V., Dudoit, S., Irizzary, I., Huber, W., ed. (New York, Springer), pp. 397-420. R (2005). R: A language and environment for statistical computing. (R Development Core Team). Supplementary files: Data_table_A: TabelleA_Signifikante.txt Description: Data table with coefficients of the linear model for every gene which was differentially expressed for at least one point in time according to the reference sample. The statistical analysis was performed as described in Series section (GSE10307) based on the normalized log2(test/ref) ratios in the Sample records' VALUE columns. Data_table_B1: Tabelle_B1; /E. coli/, unlimited growth via glucose limitation (glucose concentration < 0.05 gL-1) Data_table_B2: Tabelle_B2; /E. coli/, unlimited growth via glucose limitation, acetate concentration = 0.35 gL-1 Data_table_B3: Tabelle_B3; /E. coli/, unlimited growth via glucose limitation, 30 min after depletion of extracellular acetate Data_table_B4: Tabelle_B4; /E. coli/, unlimited growth via glucose limitation, 50 min after depletion of extracellular acetate Data_table_B5: Tabelle_B5; /E. coli/, unlimited growth via glucose limitation, 110 min after depletion of extracellular acetate Data_table_B6: Tabelle_B6; /E. coli/, unlimited growth via glucose limitation, 170 min after depletion of extracellular acetate Data_table_B7: Tabelle_B7; /E. coli/, unlimited growth via glucose limitation, 230 min after depletion of extracellular acetate Data_table_B8: Tabelle_B8; /E. coli/, unlimited growth via glucose limitation, 350 min after depletion of extracellular acetate Description: Data_tables_B1-B8 report statistical values (A: average intensity value (1/2log2(test*ref)); M: average expression value (log2(test/ref)), t and P.value ('adjusted P.value')) for every point in time (studied conditions are described above for the corresponding table). Every differentially expressed gene of the corresponding point in time according to the reference sample is listed. Genes were regarded as differentially expressed when their 'adjusted P.values' were < 0.05, therefore nominally controlling the expected fdr to less than 0.05. The data are based on maximal three biological replicates (three independent fed-batch cultivations). RT-PCR_results_7genes.txt and RT-PCR_protocol.PDF Keywords: Time course, stress response

ORGANISM(S): Escherichia coli str. K-12 substr. W3110

PROVIDER: GSE10307 | GEO | 2008/09/23

SECONDARY ACCESSION(S): PRJNA108529

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:A time series of whole-genome transcription profiling of E. coli K-12 W3110 was performed to study the dynamic physiological response of E. coli K-12 W3110 to limited carbon conditions. cDNA from eight time intervals after glucose limitation, representing different stages of glucose depletion, along with cDNA of an unrestricted growth were hybridized to whole-genome microarrays of E. coli K-12. Glucose concentrations were gradually reduced in a fed-batch cultivation process with constant feeding rate in a bioreactor. Major focus was put on the dynamic changes in the transcription level of genes involved in the central carbon metabolism (glycolysis, pentose phosphate pathway, TCA cycle and glyoxylate shunt), high-affinity glucose transport systems, movement, growth, and stress response. In total, 40 microarrays were hybridized. The data were statistically analysed using the software R (R, 2005) and the Limma package included (Smyth, 2005). The data were normalized â??print-tip-loessâ??. â??Multiple hypothesis testingâ?? correction was performed with the method of Benjamini and Hochberg (Benjamini and Hochberg, 1995), which controls the â??false discovery rateâ?? (fdr). Genes were regarded as differentially expressed when the â??adjusted p valuesâ?? were < 0.05, therefore nominally controlling the expected fdr to less than 0.05. The reproducibility of dye swap experiments as well as biological replicates was estimated by calculating â??Pearsonâ??s correlation coefficientsâ??. A high correlation was observed for the dye swap pairs (with averaged Pearsonâ??s correlation coefficients of 0.89 Â± 0.06 for the reference samples and of 0.87 Â± 0.08 for the different points of time) as well as for biological replicates (with averaged Pearsonâ??s correlation coefficients of 0.86 Â± 0.04 for the red channel (Cy5) and 0.80 Â± 0.09 for the green channel (Cy3)). Benjamini, Y., and Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. J R Stat Soc B 57, 289-300. Smyth, G.K. (2005). Limma: Linear models for microarray data. In Bioinformatics and Computational Biology Solutions using R and Bioconductor, R. Gentleman, Carrey, V., Dudoit, S., Irizzary, I., Huber, W., ed. (New York, Springer), pp. 397-420. R (2005). R: A language and environment for statistical computing. (R Development Core Team). Supplementary files: Data_table_A: TabelleA_Signifikante.txt Description: Data table with coefficients of the linear model for every gene which was differentially expressed for at least one point in time according to the reference sample. The statistical analysis was performed as described in Series section (GSE10307) based on the normalized log2(test/ref) ratios in the Sample records' VALUE columns. Data_table_B1: Tabelle_B1; /E. coli/, unlimited growth via glucose limitation (glucose concentration < 0.05 gL-1) Data_table_B2: Tabelle_B2; /E. coli/, unlimited growth via glucose limitation, acetate concentration = 0.35 gL-1 Data_table_B3: Tabelle_B3; /E. coli/, unlimited growth via glucose limitation, 30 min after depletion of extracellular acetate Data_table_B4: Tabelle_B4; /E. coli/, unlimited growth via glucose limitation, 50 min after depletion of extracellular acetate Data_table_B5: Tabelle_B5; /E. coli/, unlimited growth via glucose limitation, 110 min after depletion of extracellular acetate Data_table_B6: Tabelle_B6; /E. coli/, unlimited growth via glucose limitation, 170 min after depletion of extracellular acetate Data_table_B7: Tabelle_B7; /E. coli/, unlimited growth via glucose limitation, 230 min after depletion of extracellular acetate Data_table_B8: Tabelle_B8; /E. coli/, unlimited growth via glucose limitation, 350 min after depletion of extracellular acetate Description: Data_tables_B1-B8 report statistical values (A: average intensity value (1/2log2(test*ref)); M: average expression value (log2(test/ref)), t and P.value ('adjusted P.value')) for every point in time (studied conditions are described above for the corresponding table). Every differentially expressed gene of the corresponding point in time according to the reference sample is listed. Genes were regarded as differentially expressed when their 'adjusted P.values' were < 0.05, therefore nominally controlling the expected fdr to less than 0.05. The data are based on maximal three biological replicates (three independent fed-batch cultivations). RT-PCR_results_7genes.txt and RT-PCR_protocol.PDF Keywords: Time course, stress response Hybridization involved the hybridization of a common reference (unlimited growth, batch phase) on all arrays together with each sample of interest. This allowed the direct comparison of the transcripts of a time series taken during fed-batch cultivation with the unlimited reference sample. All samples were taken in duplicates and the experiments were performed as dye swap experiments. The first four samples of the time series (T1 - T4) were taken from three individual fed-batch cultivations (three biological replicates), the subsequent four samples (T5 - T8) were taken only from two individual fed-batch cultivations. On each array, the genes were spotted in duplicates. Therefore, twelve replicates (duplicates on dye swaps for three cultivations) were analyzed for T1 â?? T4 and eight replicates (duplicates on dye swaps for two cultivations) were analyzed for T5 â?? T8.

Project description:Microbial populations founded by a single clone and propagated under resource limitation can become polymorphic. We sought to understand how stable polymorphism arose in an Escherichia coli population that evolved for 765 generations under continuous glucose limitation. Apart from a 29 kb deletion in the dominant clone, no large-scale genomic changes distinguish evolved clones from their common ancestor. However, when co-evolved clones are cultured separately their transcriptional profiles differ markedly from that ancestor, and do so in ways that are consistent with our understanding of how E. coli adapts to glucose limitation. All adaptive clones exhibit reduced activity of the stationary-phase sigma factor Ï?S and increased expression of glucose transport genes, including the glycoporin LamB and the galactose transporter MglABC. Other expression differences, such as up-regulation of acetyl-CoA synthetase, are clone-specific and confirm previous reports of acetate cross-feeding in this system. When co-evolved clones are cultured together, transcription profiling reveals another class of genes whose expression in the dominant clone differs from that observed when the clone is cultured by itself. Many of these genes are part of the CpxR-mediated stress response. CpxR activation in monoculture likely results from extracellular accumulation of acetate that is removed by acetate-scavenging strains in co-culture. Targeted gene sequencing reveals that global regulatory mutations in Ï?S as well as small-scale regulatory mutations in the maltose and acetyl CoA synthetase operons contribute to the evolution of cross-feeding. Finally, we identified two mutations in the founder that likely pre-disposed the experimental population to develop specialists that thrive on overflow metabolites. Subsequent mutations that lead to specialization emphasize the importance of compensatory rather than gain-of-function mutations in this system. Observations that polymorphism readily evolves in an asexual population, that adaptive mutants arise without large-scale change in genome architecture, and that morphs have both common and unique patterns of gene expression influenced by whether they are cultured separately or together, underscore the importance of regulatory change, founder genotype, and the biotic environment in the adaptive evolution of microbes. Four isolates of E. coli evolved under long-term glucose limitation and their common ancestor were grown in Luria broth to stationary phase. Genomic DNA from each of the evolved isolates was competitively hybridized against genomic DNA from the ancestral strain.

Dataset Information

Transcription analysis of E. coli processed at persistent and decreasing glucose limitation in a fed-batch cultivation

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets