Metabolic regulation analysis of an ethanologenic Escherichia coli strain based on RT-PCR and enzymatic activities
© Orencio-Trejo et al; licensee BioMed Central Ltd. 2008
Received: 12 February 2008
Accepted: 1 May 2008
Published: 1 May 2008
A metabolic regulation study was performed, based upon measurements of enzymatic activities, fermentation performance, and RT-PCR analysis of pathways related to central carbon metabolism, in an ethanologenic Escherichia coli strain (CCE14) derived from lineage C. In comparison with previous engineered strains, this E coli derivative has a higher ethanol production rate in mineral medium, as a result of the elevated heterologous expression of the chromosomally integrated genes encoding PDC Zm and ADH Zm (pyruvate decarboxylase and alcohol dehydrogenase from Zymomonas mobilis). It is suggested that this behavior might be due to lineage differences between E. coli W and C.
This study demonstrated that the glycolytic flux is controlled, in this case, by reactions outside glycolysis, i.e., the fermentative pathways. Changes in ethanol production rate in this ethanologenic strain result in low organic acid production rates, and high glycolytic and ethanologenic fluxes, that correlate with enhanced transcription and enzymatic activity levels of PDC Zm and ADH Zm . Furthermore, a higher ethanol yield (90% of the theoretical) in glucose-mineral media was obtained with CCE14 in comparison with previous engineered E. coli strains, such as KO11, that produces a 70% yield under the same conditions.
Results suggest that a higher ethanol formation rate, caused by ahigher PDC Zm and ADH Zm activities induces a metabolic state that cells compensate through enhanced glucose transport, ATP synthesis, and NAD-NADH+H turnover rates. These results show that glycolytic enzymatic activities, present in E. coli W and C under fermentative conditions, are sufficient to contend with increases in glucose consumption and product formation rates.
Fermentative metabolism constitutes a fundamental cellular capacity for industrial biocatalysis. Endogenous organic compounds used by cells as terminal electron acceptors under oxygen deprivation are converted into biochemical products that are waste products for the cell, such as ethanol, lactate, acetate, succinate, formate and hydrogen, but represent valuable molecules to society . For example, renewable fuels from biomass, such as ethanol, constitute energy sources that preserve the environment since the carbon dioxide released from their combustion can be integrated into a photosynthetic cycle, which does not participate in a net carbon dioxide buildup into the atmosphere.
Metabolic engineering strategies have been used to modify microorganisms to convert all sugars arising from chemical-enzymatic hydrolysis of lignocellulose, such as xylose, arabinose, and glucose into ethanol. A wide variety of research approaches have been employed for this purpose; among the most effective attempts are the engineering of different Gram-negative bacteria, such as Escherichia coli [2–6], Klebsiella oxytoca [7–9] and Zymomonas mobilis [10, 11] as well as yeast, such as Saccharomyces cerevisiae [12–16]. One of the most successful strategies to develop ethanologenic bacteria was developed by Ingram and co-workers [2, 3, 6–8, 17]. In the case of E. coli, the W strain was engineered for ethanol production by integrating the pyruvate decarboxylase (pdc) and alcohol dehydrogenase (adhII) genes from Z. mobilis, under the control of the pflB promoter, to obtain strain KO11 [3, 17]. Expression from this promoter is high under anaerobic conditions [18, 19], and ethanologenic E. coli strains, such as KO11 and LY01 have shown to be efficient in the conversion of all sugars present in lignocellulosic hydrolysates into ethanol [20, 21].
Expression profiling is a powerful tool for analyzing gene transcription at a genomic scale. It can be used to compare global relative changes in gene expression that occur in response to an environmental stimulus or to compare the effects of genetic modifications on gene expression. This type of analysis can provide important information about cell physiology and has the potential to identify connections between regulatory or metabolic pathways not previously known [22, 23]. Since the physiological state and fermentation performance of a cell is dictated primarily at the protein level, transcription results should be complemented by determining specific enzyme activities to provide a better understanding of the observed phenomenon, considering that enzymatic and transcriptional regulation mechanisms are different .
Previous studies have shown that plasmid-encoded levels of Z. mobilis pyruvate decarboxylase (PDC Zm ) and alcohol dehydrogenase II (ADH Zm ) in E. coli correlate with the titer and the formation rate of ethanol [24, 21, 25]. Furthermore, the introduction of this heterologous pathway has several effects on E. coli physiology under fermentative conditions, i.e., increases its growth rate and glycolytic flux when cultivated in Luria Broth with xylose  or glucose . Gene array studies have also shown that several genes from the pentose phosphate and glycolytic pathways have statistically significant higher expression levels when ethanologenic E. coli (strain KO11) ferments xylose [26, 27].
The present study was conducted to understand the role that chromosomally integrated pdc Zm and adh Zm heterologous expression has on the physiology and metabolic performance of E. coli during glucose fermentation in mineral media. The regulation of metabolic pathways, related to central carbon metabolism and fermentation performance, was studied using mainly the measurements for both the enzymatic activities of the glycolytic and fermentative pathways, as well as transcript levels from genes coding for the enzymes involved in the glycolytic, pentose phosphate, and fermentative pathways. Glucose transporters and anaerobic regulators were also analyzed using transcriptome data. Evaluation was performed using wild type E. coli C as the reference strain, and a new ethanologenic strain derived from E. coli C, CCE14 (E. coli C: pflB::pdc adhB cat). Interestingly, strain CCE14 has ca. five-fold higher values of PDC Zm and ADH Zm enzymatic activities than strain KO11 (E. coli W: pflB::pdc adhB cat, Δfrd) [3, 17]. The results show that not only the specific ethanol rate, but also the glucose consumption rate (glycolytic flux) are increased as pyruvate decarboxylase and alcohol dehydrogenase transcripts and enzymatic activities are increased. Moreover, glycolytic flux is controlled by reactions outside glycolysis.
Results and discussion
Effect of PDCZm and ADHZm activity levels on fermentation performance
Kinetic constants in anaerobic cultures
qGlc Exponential phase
qGlc Stationary phase
E. coli C
0.42 ± 0.01
2.73 ± 0.02
1.11 ± 0.11
1.28 ± 0.07
0.38 ± 0.01
3.68 ± 0.12
1.20 ± 0.10
1.07 ± 0.04
0.45 ± 0.01
3.49 ± 0.09
0.97 ± 0.06
1.39 ± 0.09
Fig 2C shows that no pyruvate was secreted by ethanologenic strains, but E. coli C produced a significant amount (> 3 g/L) of this metabolite during the stationary phase (Fig 2C). Furthermore, formate production by KO11 and E. coli C were similar, reaching up to 9 g/L when glucose was exhausted (Fig. 2D). However, formate production was lower than 2 g/L for CCE14. PDC Zm was originally selected by Ohta et al , largely because it has a very high affinity for pyruvate (Km for pyruvate 0.4 mM) [28, 29] in comparison with all competing fermentation enzymes . This fact and our results indicate that competition occurs at the pyruvate node level, and that higher levels of PDC Zm and ADH Zm apparently allow more efficient carbon channeling through the heterologous ethanol pathway.
Specific formation rates (qP) for organic acids and ethanol during the exponential phase (gPRODUCT/gDCW h)
Carbon Recovery (%)
E. coli C
0.95 ± 0.08
1.21 ± 0.03
0.29 ± 0.03
0.58 ± 0.05
100.9 ± 0.41
0.39 ± 0.04
0.67 ± 0.04
0.28 ± 0.04
2.08 ± 0.01
104.5 ± 0.22
0.79 ± 0.04
1.59 ± 0.06
1.63 ± 0.01
98.7 ± 0.32
Specific formation rates (qP) for organic acids and ethanol during the stationary phase (gPRODUCT/gDCW h).
E. coli C
0.14 ± 0.07
0.26 ± 0.06
0.04 ± 0.01
0.26 ± 0.04
0.25 ± 0.02
0.12 ± 0.06
0.04 ± 0.08
0.05 ± 0.04
0.06 ± 0.01
0.01 ± 0.015
0.68 ± 0.01
0.10 ± 0.01
0.19 ± 0.02
0.03 ± 0.05
0.37 ± 0.03
Metabolic regulation at transcript level
Transcript levels of 49 genes from the CCE14 strain were analyzed in the exponential growth phase and normalized for values obtained with E. coli C. Levels of pdc Zm and adh Zm were normalized with KO11 values and analyzed for both exponential and stationary phases. A Student' t-test with a p value of ≤ 0.05 was applied to each set of normalized values in order to determine statistical significant differences in expression levels.
Glucose transport and phosphorilation
On the other hand, wild type E. coli strains, growing on micromolar concentrations of glucose, synthetize galactose and maltodextrines as autoinducers derepressing the synthesis of the high-affinity glucose transport systems (MGLB and the LAMB maltoporin), which are responsible for glucose transport under these conditions . Analyses of gene expression response in wild type E. coli from glucose non-limiting to glucose-limiting growth conditions, in chemostat cultures, have demonstrated that several genes including mglB and lamB are upregulated . Furthermore, the crp transcript is higher when E. coli experience glucose limitation  and CRP regulates genes such as mglB, lamb, glk, and ptsG . Our results show that even though cultures were growing in large amounts of glucose (40 g/L) throughout the exponential phase (Fig. 2), transcription results suggest that CCE14 was sensing partial glucose limitation. This response might be due to increases in the fermentation and glycolytic rates that in turn will induce a response to scavenge sugar through transport activation of alternative glucose transporters. Interestingly, glk transcript levels were significantly higher in CCE14. This result suggests that besides the PTS system, glucose could also be transported by MGLB and LAMB and phosphorylated by GLK. The higher glk transcript is also related to an elicited response due to the over expression of heterologous genes as demonstrated by Arora and Pederson .
As mentioned earlier, fruR (2.28-fold) was more highly expressed in CCE14. FRUR (or CRA) is a key regulator controlling the balance between glycolysis and gluconeogenesis [38–40]. Many gluconeogenic genes are activated by FRUR, while glycolytic genes such as glk, pfkA, gapA, eno, and pykF are repressed. [41, 42]. However, none of the genes studied above was repressed. Probably FRUR was partially inactivated in the presence of glucose, because fructose-1-phosphate and fructose-1,6-bisphosphate bind to FRUR and inactivate its DNA-binding capacity [43, 44].
In general, only slight changes were detected in the transcription level of genes related to glycolysis. For instance, gapA (1.36-fold), fbaA (2.16-fold), and pgk (1.66-fold) transcript levels were higher in CCE14 strain than in E. coli C (Fig. 3). In E. coli, the gapA gene is transcribed from at least four promoters, three recognized by the RNA polymerase Eσ70 and one by the heat shock RNA polymerase Eσ32. This complex region of differentially regulated promoters allows the production of large amounts of gapA transcripts in a wide variety of environmental conditions . On the other hand, in γ-proteobacteria (E. coli, for example), the pgk and fbaA genes are cotranscriptionally expressed using two transcriptional promoters, though only one is required to get a strong production of PGK and FBA proteins in the presence of glucose . It has been proposed that when glucose is present in the growth medium, pts, gapA, and pgk genes are coordinately activated by a mechanism dependent upon the EIIGlc protein (coded by the ptsG gene) . Our results correlate with these facts, given the increases found in fbaA, pgk, and ptsG transcript levels.
Surprisingly, only the PGK enzymatic activity was higher (1.54-fold) in CCE14, whereas GAPDH activity was lower (0.64-fold) in this strain. As mentioned previously, it is possible that in the exponential phase, in spite of a higher transcript level of gapA, the low GAPDH activity could be related to a redox balance between GAPDH and higher ADH Zm and PDC Zm transcripts and enzymatic activities.
Several glycolytic genes showed no significant changes in the transcription level, and some of the transcripts and enzymatic activities did not show the same tendency. This behavior could be related to posttranscriptional regulation and RNA segmentation, leading to the production of individual mRNAs with selective stabilization. These processes allow the adaptation of gene expression to variations in environmental conditions, as has been observed in glycolytic gene expressions in B. subtilis [48, 49], Z. mobilis , and L. delbrueckii . Another explanation could be that enzyme levels are sufficient to carry out their catalytic role.
On the other hand, only the pgi transcript from CCE14 was lower than in the wild type strain. Likewise, the PGI enzymatic activity was slightly lower than that of E. coli C. Despite the importance of PGI in glycolysis, little information is available about the regulation of the pgi gene. However, due to the results in terms of glucose consumption and ethanol formation rate, the lower transcript and enzymatic activity does not cause any reduction in the glycolytic flux.
Entner-Doudoroff and pentose pathways
The zwf gene, that codes for glucose 6-P dehydrogenase, plays an important role in the control of carbon distribution at the glucose 6-phosphate node. It directs carbon flux through the oxidative branch of the pentose phosphate pathway (PPP) depending on NADP+ availability. In the CCE14 strain, the transcript level of zwf was not different to that of E. coli C (Fig. 3); however, ZWF specific enzyme activity was 7-fold higher in CCE14 (Fig. 4). Similarly, transcription of the gnd gene, which codes for phosphogluconate dehydrogenase, and one of the isoenzymes that codes for ribose-P isomerase (rpiB gene) were higher, 2.01 and 6.31-fold, respectively; while transcript of rpiA was lower, 0.71-fold. The isoenzimes transketolases (encoded by tktA and tktB genes) and transaldolase (encoded by talA and talB genes) interconnect glycolysis with the oxidative branch of PPP. Our results show that tktB and talA transcripts were lower, 0.46 and 0.56-fold, respectively, in CCE14; while tktA and talB were not different when compared to E. coli C. These results suggest that the pentose phosphate pathway is very flexible, and it is likely that overall catalytic rates are similar in the two strains tested.
Unexpectedly, genes edd that codes for 6-phosphogluconate dehydratase and eda which codes for 2-keto-3-deoxy-6-phosphogluconate aldolase in the Entner-Doudoroff pathway were more highly expressed, -2.17 and 2.24-fold, respectively, in CCE14 (Fig. 3). These results suggest that the Entner-Doudoroff pathway is functional, although it has been reported that for aerobic cultures with glucose the carbon flux through this route is not very high [52, 53]. In addition, ATP yield is lower through this pathway versus the Embden-Meyerhof pathway .
In the CCE14 strain, adhE (2.09-fold), fumB (2.13-fold), fumC (1.84-fold), frdABCD (2.84, 2.87, 2.38 2.45-fold), and pflD (3.43-fold) gene expressions were higher than in the wild type. It is known that frdABCD is induced under anaerobic conditions , though a recent study showed that this gene can be induced by glucose limitations .
It has been demonstrated that the fumB transcript is more abundant under anaerobic conditions, and that FNR is necessary as a transcriptional activator [57, 58]. In agreement with these reports, the transcription of fumB and the anaerobic regulator fnr (1.61-fold) were also more highly expressed in the CCE14 strain (Fig. 3). These results indicate that the pathways to produce succinate, formate, and ethanol (for native pathway) are active, although specific enzyme activity values of PFL and LDH and transcript levels of pflB and ldhA decreased in the exponential phase. It is important to mention that CCE14 produces formate and succinate in low concentrations. These results could indicate a competition phenomenon for pyruvate between PFL and PDC Zm . However, it is important to consider the disruption of routes to compete for the ethanol production in these conditions such as succinate and lactate pathways. We found that in cultures with high glucose concentrations (100 g/L), the production of succinate increases significantly in strain CCE14 (data no shown). This could be due to osmolarity problems or to a partial limitation of PYK enzyme causing PEP accumulation; hence, the carbon flux may be partially redirected towards succinate formation.
Metabolic regulation at the enzyme activity level
Enzyme activity levels for CCE14 strain were analyzed in exponential and stationary phases and normalized for values obtained with E. coli C (Fig. 4). Enzymatic levels for pdc Zm and adh Zm were normalized with KO11. A t-student test with a p value of ≤ 0.05 was applied to each set of normalized values to determine statistical differences in enzyme activity levels.
In the CCE14 strain, PTS and PGK enzymatic activities were higher, whereas TPI and PFL activities were lower during the exponential growth phase. These data correlate with the fact that ethanologenic strains consume glucose at a higher rate. In addition, increases in PGK activity suggest that the over expression of the genes coding for PDC Zm and ADH Zm modify the ATP/ADP balance. It is known that in aerobic conditions, a high ATP demand causes an increase in glycolytic flux in E. coli . For Lactococcus lactis, the control of glycolytic flux resides to a large extent in processes outside the pathway, such as ATP consuming reactions and glucose transport . As discussed above, the heterologous ethanologenic pathway increases glycolytic flux with the subsequent increases in ATP production and consumption. Therefore, it appears that cells tend to increase ATP formation through an increase in PGK synthesis; although no increase in PYK activity was found. ATP is also produced when acetate is formed; however, CCE14 does not produce acetate during the exponential phase. A decrease in PFL activity in CCE14 correlates with a strong reduction in formate production (Fig. 2D). On the other hand, the observed 50% reduction in the TPI specific enzyme activity does not reduce glycolytic flux. A large increase in ZWF specific activity was found, and was discussed above.
A comparison of enzymatic activity data between CCE14 and E coli C during the stationary phase, indicates higher values of PTS, FDP, GAPDH, PGK, and PYK for the ethanologenic strain. The LDH enzymatic activity was lower in CCE14. It is known that lactate dehydrogenase is allosterically activated by pyruvate . Lactate production was found only during the stationary phase of two cultures. Pyruvate formation in E. coli C correlates with lactate production (Fig. 2C–G), and lower levels of this metabolite in CCE14 correlate with a 40% lower LDH specific activity (Fig. 4). These results suggest that a higher ethanol formation rate, i.e., higher PDC Zm and ADH Zm specific activities originate higher rates of glucose transport, ATP synthesis, and NAD-NADH+H turnover.
A higher glycolytic flux in CCE14 results from increased chromosomal expression of pdc Zm and adh Zm genes and higher specific enzyme activities of heterologous PDC Zm and ADH Zm enzymes involved in ethanol formation. These results indicate that under the conditions used in this study, the glycolytic flux is controlled by reactions outside this pathway, that is, by the fermentative heterologous route. The metabolic adjustments carried out in the cell entail low organic acid production and an increase in the ethanol formation rate, as well as higher ethanol yield (90% of the theoretical) in glucose-mineral media when compared with previous engineered efficient strains, such as KO11 (70% of the theoretical yield). In spite of the higher PDC Zm and ADH Zm transcript and enzymatic activities in the CCE14 strain, the differences are mediated by higher glucose transport rates and an increase in the turnover rate of NAD-NADH+H+ and ATP.
Overall, these results also show that E. coli glycolytic enzymatic activities under fermentative conditions are sufficient to contend with increases in the rates of glucose consumption and higher transcript and enzymatic activities of the heterologous ethanol pathway. Also, the study provides the basis for the implementation of appropriate genetic modifications to increase the ethanol yield when mineral media is used; for instance, the disruption of succinate and lactate pathways that compete for ethanol production.
Bacterial strains, media and growth conditions
Escherichia coli strains used in this study
E. coli C
E. coli C: pflB::pdc adhB cat
E coli W: pflB::pdc adhB cat, Δfrd
Ohta et al 1991 Jarboe et al 2007
All stock cultures were stored at -70°C in Luria Broth (LB) medium  containing 40% glycerol. To develop inocula, cells were transferred twice on LB-agar plates supplemented with 20 g/L of glucose-chloramphenicol (20 μg/ml), and no chloramphenicol for E. coli C. Single colonies were transferred to overnight cultures in shake flasks (35°C, 120 rpm), containing glucose (20 g/L) in mineral M9-medium . M9-medium contains: 6 g/L Na2HPO4, 3 g/L KH2PO4, 1 g/L NH4Cl, 0.5 g/L NaCl. The following components were sterilized by filtration, and then added (per liter of final medium): 2 ml of 1 M MgSO47H2O, 1 mL of 0.1 M of CaCl2, 1 mL of 1 mg/mL thiamine-HCl. These cells were harvested in exponential growth phase by centrifugation and used to inoculate non-aerated mini-fermentors , containing 200 ml of M9-medium with 40 g/L of glucose. Starting OD600 was 0.1, chloramphenicol (0, 40 and 20 μg/ml) was included for strains C, KO11 and CCE14, (respectively), cells were cultivated at 35°C, 100 rpm, and the pH was maintained at 7 by the automatic addition of 2 N KOH. All cultures were carried out in triplicate.
Samples were periodically taken from cultures to measure optical density at 600 nm using a spectrophotometer (Beckman DU-70, Palo Alto, CA) and the dry cell weight was calculated using a previously determined conversion factor of 1 OD600 = 0.37 g/L. An HPLC system (600E quaternary bomb, 717 automatic injector, 2410 refractive index, and 996 photodiode array detectors, Waters, Milford, MA) and an Aminex HPX-87H column (300 × 7.8 mm; 9 μm) (Bio-Rad, Hercules, CA) were used to separate and quantify D-glucose, formate, acetate, succinate, and lactate concentrations. Running conditions were: mobile phase, 5 mM H2SO4, flow 0.5 ml/min, and temperature 50°C. Under these conditions glucose was detected by refractive index, and organic acids were identified by photodiode array at 210 nm. Ethanol was quantified by gas chromatography (Agilent 6850, Wilmington, D.E.), using 1-butanol as internal standard.
Preparation of cell extracts and enzymatic assays
Samples were taken at the mid-exponential and stationary phases. All operations were carried out at 4°C. 1 mL of cell culture was harvested by centrifugation at 10,000 × g for 10 min, washed twice with 1 mL of 100 mM Tris-HCl (pH 7.0) containing 20 mM KCl, 5 mM MnSO4, 2 mM DTT and 0.1 mM EDTA, and then suspended in 1 mL of the same buffer. Cells were disrupted by four sonication steps (15 s each) in an ultrasonic disrupter (Soniprep 150, UK). The cell debris was removed by centrifugation; 10 min at 10,000 × g. The resulting crude extracts were used immediately for determination of enzymatic activities and protein, or stored at -20°C.
Enzyme activities were measured spectrophotometrically at 340 nm in a thermostatically controlled (30°C) spectrophotometer (BioMate 5, ThermoSpectronic, NY). All compounds of the reaction mixtures were pipetted into 1 cm light path cuvettes, reactions were initiated by adding the cell extract or substrate to give a final volume of 1 mL. The millimolar extinction coefficient for NAD+, NADH, NADP+ and NADPH is 6.22 cm-1. mM-1.
The assay conditions for glucose:PEP phosphotransferase (PTS), 6-phosphofructosekinase (PFK), fructose-1,6-bisphosphatase (FDP), glucose phosphate isomerase (PGI), fructose bisphosphate aldolase (FDP aldolase), glyceldehyde-3-phosphate dehydrogenase (GAPDH), triose phosphate isomerase (TPI), 3-phosphoglycerate kinase (PGK), pyruvate kynase (PYK), 6-phosphogluconate dehydrogenase (ZWF), pyruvate-formate lyase (PFL), and lactate dehydrogenase (LDH) were measured based on the methods used by Peng et al . The assay conditions used for alcohol dehydrogenase (ADH Zm ) and pyruvate decarboxylase (PDC Zm ) were based on the methods reported by Conway et al . Phosphoglycerate mutase was measured based on the method of Maitra et al . Protein concentration was estimated by the Bradford method, , with bovine serum albumin used as the standard. Each assay was performed three times for the same culture, from three independent experiments. A t-student test with a p value of ≤ 0.05 was applied to each set of normalized values in order to determinate statistical differences in enzyme activity levels.
RNA extraction and cDNA synthesis
Total RNA extraction was performed using hot-phenol equilibrated with water, precipitated with 3 M sodium acetate and ethanol, and treated with DNase kit (DNA-free™, Ambion; . RNA integrity was tested by densitometry in 1.2% agarose gels. RNA quantification was performed by absorbance at 260/280 nm. cDNA was synthesized using RevertAid™ H First Strand cDNA Synthesis kit (Fermentas Inc.) and a mixture of specific DNA primers. The sequences of the primers used for cDNA synthesis were those reported by Flores et al , except for pdc Zm (5'-GACAAAGTTGCCGTCCTCGT and 5'-ATGGTAGCAACTGCGCCAC) and adh Zm (5'-TTACCCCGATGGTTTCCGT and 5'-TTCAAATGCGTGGGTCAGAG) genes. cDNA obtained in this way was used as template for RT-PCR assays. Reproducibility of this procedure was determined by performing two separate cDNA synthesis experiments from the RNA extracted for each strain. Similar results were obtained for the transcription of all genes that were measured.
Real-time PCR (RT-PCR) was performed with the ABI Prism 7000 Sequence Detection System (Perkin Elmer/Applied Biosystems, Foster City, CA), using the SYBR Green PCR Master Mix (Perkin Elmer/Applied Biosystems, Foster City, CA) and amplification conditions described by Flores et al . The primers for specific amplification were designated using the Primer Express software (Perkin Elmer/Applied Biosystems, Foster City, CA). The size of all amplimers was 101 bp. The final primer concentration, in a total volume of 15 μl, was 0.2 μM. Five nanograms of target cDNA for each gene was added to the reaction mixture. All experiments were performed in triplicate for each gene of each strain, obtaining very similar values. A non-template control reaction mixture was included for each gene. The quantification technique used to analyze data was the method described by Livak and Shmittgen . The data were normalized using the ihfB gene as an internal control (housekeeping gene). We detected the same expression level of this gene in all the strains in the conditions in which the bacteria were grown. For each analyzed gene in all strains, the transcription level of the wild type gene, considered as one, was used as the control to normalize the data. Data is reported as relative expression levels compared to the expression levels of E. coli C. A t-student test with a p value of ≤ 0.05 was applied to each set of normalized values in order to determinate statistical differences in expression levels.
We thank Dr. Lonnie O. Ingram (University of Florida) for kindly providing strain KOll and pLOI510. We thank Mercedes Enzaldo, Ricardo Ciria and Manuel Hurtado for technical support. We thank Jonathan C. Moore (University of Florida) for proofreading of the manuscript. This work was supported by the Mexican Council of Science and Technology (CONACyT) grants: CONACyT-SAGARPA 2004-C01-224, CONACyT – Estado de Morelos MOR-2004-C02-048, CONACyT 44126 and PAPIIT-DGAPA-UNAM IN220908-3. Montserrat Orencio-Trejo held a scholarship from CONACyT.
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