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The role of the transcription factors LacR and LacT in the regulation of the lactose and galactose utilization pathways in Streptococcus pneumoniae

ABSTRACT: Transcriptome comparison of the Streptococcus pneumoniae strain D39 grown in the presence of either lactose or galactose with that of the strain grown in the presence of glucose, revealed the elevated expression of various genes and operons, including the lac gene cluster that is organized into two operons i.e. lac operon-I (lacABCD) and lac operon-II (lacTFEG). Deletion of the DeoR family transcriptional regulator lacR that is present downstream of the lac gene cluster, revealed elevated expression of lac operon-I, even in the absence of lactose. This suggests a function of LacR as a transcriptional repressor of lac operon-I that encodes enzymes involved in the Tagatose-6-P pathway in the absence of lactose or galactose. Deletion of lacR did not affect the expression of lac operon-II that encodes for a lactose-specific PTS. This finding was further confirmed by ?-galactosidase assays with PlacA-lacZ and PlacT-lacZ in the presence of either lactose or glucose as a sole carbon source in the medium. This suggests the presence of another transcriptional regulator in the regulation of lac operon-II, which could be the BglG-family transcriptional antiterminator LacT. We demonstrate the role of LacT as a transcriptional activator of lac operon-II in the presence of lactose and CcpA-independent regulation of the lac gene cluster in S. pneumoniae. This SuperSeries is composed of the SubSeries listed below.

ORGANISM(S): Streptococcus pneumoniae D39

PROVIDER: GSE58184 | GEO | 2014/06/20

SECONDARY ACCESSION(S): PRJNA251520

REPOSITORIES: GEO

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Project description:This a model from the article: Feedback regulation in the lactose operon: a mathematical modeling study and comparison with experimental data. Yildirim N, Mackey MC Biophys. J. 2003 12719218 , Abstract: A mathematical model for the regulation of induction in the lac operon in Escherichia coli is presented. This model takes into account the dynamics of the permease facilitating the internalization of external lactose; internal lactose; beta-galactosidase, which is involved in the conversion of lactose to allolactose, glucose and galactose; the allolactose interactions with the lac repressor; and mRNA. The final model consists of five nonlinear differential delay equations with delays due to the transcription and translation process. We have paid particular attention to the estimation of the parameters in the model. We have tested our model against two sets of beta-galactosidase activity versus time data, as well as a set of data on beta-galactosidase activity during periodic phosphate feeding. In all three cases we find excellent agreement between the data and the model predictions. Analytical and numerical studies also indicate that for physiologically realistic values of the external lactose and the bacterial growth rate, a regime exists where there may be bistable steady-state behavior, and that this corresponds to a cusp bifurcation in the model dynamics. The model reproduces the time profile of beta-galactosidase activity as shown in Fig 3 of the paper. The delay functions for transcription (M) and translation (B and P) have been implemented by introducing intermediates ( I1, I2 and I3) in the reaction scheme which then give their respective products (I1-> M, I2 ->B and I3 ->P) after an appropriate length of time. The steady state values, attained upon simulation of model equations, for Allolactose (A), mRNA (M), beta-galactosidase (B), Lactose (L), and Permease (P) match with those predicted by the paper. The model was successfully tested on Jarnac, MathSBML and COPASI This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2010 The BioModels.net Team. For more information see the terms of use . To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Project description:Salmonella is an important enteric pathogen that causes a spectrum of diseases varying from mild gastroenteritis to life threatening typhoid fever. Salmonella does not have lac operon. However, E. Coli, Salmonellaâs close relative, has lac operon. Being an enteric pathogen like E. coli, Salmonella will also benefit from lac operon. Then, why Salmonella has lost lac operon?. To address this question, lacI, an important component of lac operon was expressed in Salmonella via pTrc99A plasmid. As a control, pTrc99A without lacI was also expressed in Salmonella. The effect of LacI on the transcription profile of Salmonella was analyzed using microarray technique. Overall design The total RNA was isolated from Salmonella using âRNeasy Mini Kitâ (QIAGEN). Organism used: Salmonella enterica serovar Typhimurium LT2 * Slides: Agilentâs arrays (8x15k) AMADID: NO: 17809 * Starting material: Salmonella RNA in nuclease-free water * RNA Samples used: Wild type (WT), WT + pTrc99A+LacI (PTRC), WT + pTrc99A-LacI(Delta lac) * Labeling kit: MessageAmpâ¢ II-Bacteria RNA Amplification Kit from Ambion Cat # AM1790 * Labeling Method: T7 promoter based-linear amplification to generate labeled complementary RNA * Total RNA and cRNA Purification Kit: Qiagenâs RNeasy minikit Cat#74104 * Hybridization Kit: Agilentâs In situ Hybridzation kit 5184-3568 * RNA quality was checked using Bioanalyzer. The array slides were scanned immediately by PerkinElmer Scan array Gx Microarray scanner. The Scan array software (PerkinElmer) was used for grid wise normalization of array images. Two arrays were used with mutant and rescue experiments and dye swap experiments were included in the final analysis. The data was analysed by GeneSpring GX and Biointerpreter software from Genotypic Technology, Bangalore. The differential expression was considered if the Log 2 mean of at least -1 for the down regulated genes and +1 for the upregulated genes. We considered only the genes that were reproducible from both replicates.

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The role of the transcription factors LacR and LacT in the regulation of the lactose and galactose utilization pathways in Streptococcus pneumoniae

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