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2.1. Culturing

The Culture Experiment was carried out with an initial inoculum of 9.7 x 106 E. coli ATCC 8739 cells from Passage 70 of Lee et al. (13) as the first passage in each of the 4 replicates of 10ml of 1X nutrient broth with a fixed concentration of NaCl and cultured in tightly-capped 15ml conical tubes. Subculture was performed using 1% of the previous culture on every odd day except Sunday (3 subculturing per week). NaCl concentration for the passages were as follows: Passage 1 to 15 at 3% NaCl, Passage 16 to 31 at 4% NaCl, Passage 32 to 39 at 4.5% NaCl, Passage 40 to 50 at 5% NaCl, Passage 51 to 62 at 6% NaCl, Passage 63 to 74 at 7% NaCl, and Passage 75 to 80 at 8% NaCl.



2.2. Contamination Monitoring

The most likely contaminant is Staphylococcus aureus, a Gram positive, salt tolerant commensal on human skin. The cultures were monitored routinely for contamination using Gram staining and DNA fingerprinting. The DNA fingerprinting by PCR/restriction fragment length polymorphism was performed using the procedure in a previous similar adaptation study (13) where each of the 3 primers (Primer 5, CgCgCTggC; Primer 6, gCTggCggC and Primer 7, CAggCggCg) were used as both forward and reverse primers. The PCR product was digested with 1 unit of TaqI restriction endonuclease for 16 hours at 65oC before analysis on 2% (w/v) agarose gel with 1X GelRed.



2.3. Data Analysis

The cell density of each passage at the day of subculture and 5 and 7 day post-subculture was estimated from the OD600 readings using cell size correction suggested by Sezonov et al. (28) that the size of the cells remains constant up to OD600 0.3, which is equivalent to 5 x 107 cells per millilitre. After OD600 0.3, cells size decreases and the correlation between the OD600 and the cell density changes is estimated by the following equation: cell density = 52137400 * ln(OD600 Reading) + 118718650, as described in Lee et al. (13). To estimate generation time, 10 μl of E. coli culture from each replicate (A, B, C, D) was inoculated into 1ml of 1X nutrient broth and OD600 readings taken at intervals of up to 360 minutes was used to analyze the generation time of each sample tubes. This was conducted at every 3rd passage using the correction (28) before taking the geometric mean from the 3rd hour post-inoculation.




2.4. Minimum Inhibitory Concentration

1% of E. coli culture from each replicates (A, B, C, D) were inoculated into 1ml of 1X nutrient broth supplemented with 0% (w/v) NaCl, 1% (w/v) NaCl, 3% (w/v) NaCl, 5% (w/v) NaCl, 7% (w/v) NaCl, 9% (w/v) NaCl and 11% (w/v) NaCl of different salt concentration. This was incubated for 21-23 hours at 37oC before taking OD600 readings. The readings were fitted to the following 4th order equation: OD600 = M4(%NaCl)4 + M3(%NaCl)3 + M2(%NaCl)2 + M1(%NaCl)1 + M0.



3. Results

3.1. E. coli adapts to 1% increase in NaCl in about one month.

Our results suggest that E. coli were able to grow at 11% NaCl for all four replicates after about passage 64 (Table 1, Figure 1) as there was no measured growth at 11% NaCl before passage 64. The OD600 readings at 11% NaCl increased consistently after passage 64.





Figure 1. OD600 at 11% NaCl, 21 to 23 hours post-inoculation. This graph illustrates the OD600 reading in 11% NaCl of the MIC experiment demonstrating an increased OD reading post-passage 60, suggesting that the cells are able to divide at 11% NaCl

Table 1. OD600 tabulation for minimum inhibitory concentration estimation. Representative data from each salt concentration is shown.

Passage ([NaCl]% in media)



Replicate


[NaCl]% for Minimum Inhibitory Concentration


0%


1%


3%


5%


7%


9%


11%

11 (3%)


A

0.684

0.672

0.866

0.464

0.118

0.006

-0.004

B

0.616

0.613

0.863

0.355

0.075

0.006

-0.001

C

0.637

0.657

0.706

0.376

0.089

-0.003

-0.004

D

0.686

0.719

0.870

0.370

0.090

0.008

-0.001

30 (4%)


A

0.644

0.703

0.793

0.362

0.139

0.006

0.005

B

0.678

0.658

0.744

0.381

0.085

0.021

0.002

C

0.659

0.627

0.757

0.425

0.005

0.010

0.003

D

0.670

0.639

0.784

0.363

0.035

0.007

-0.001

49 (5%)


A

0.705

0.680

0.840

0.696

0.104

0.012

0.006

B

0.761

0.720

0.927

0.757

0.123

0.030

-0.003

C

0.919

0.705

1.354

0.792

0.158

0.064

-0.007

D

0.726

0.767

1.060

0.582

0.115

0.002

0.023

61 (6%)


A

0.471

0.515

0.771

0.433

0.049

-0.022

-0.020

B

0.432

0.446

0.732

0.461

0.078

-0.018

-0.033

C

0.54

0.561

0.628

0.444

0.085

-0.021

-0.016

D

0.985

0.569

0.760

0.431

0.124

-0.009

-0.020

72 (7%)

A

0.549

0.746

0.610

0.401

0.418

0.289

0.259

B

0.804

0.742

0.791

0.501

0.301

0.288

0.200

C

0.55

1.013

0.984

0.407

0.309

0.241

0.163

D

0.873

0.790

0.689

0.387

0.340

0.286

0.230



Figure 2. PCR-RFLP and Gram staining of Passage 72.

(A) Genomic DNA extraction and PCR using Lee et al. (2012) and 16-hour TaqI restriction endonuclease digestion showed similar profile in all 4 replicates.

(B) Gram staining showed predominately Gram negative cultures. These suggest that the culture were uncontaminated by Staphylococcus aureus (a common Gram positive salt tolerant bacterium)

This suggests that E. coli is able to grow at 11% NaCl even though they had been adapted to grow at 7-8% NaCl from passage 63. In addition, Gram staining and PCR-RFLP at Passage 72 (Figure 2) showed that the cultures are Gram negative and the PCR-RFLP profiles of all 4 replicates to be similar. This suggested that the cultures had not been contaminated with S.aureus, which is Gram positive and the most likely contaminant as S. aureus is a salt tolerant commensal found on human skin. The Area under Curve (AUC) has increased for all four replicates over 80 passages (Figure 3) when NaCl concentration is more than 7.5%. The rate of increase in ascending order is as follows: Tube A (0.003% per passage), Tube D (0.0049% per passage), Tube C (0.0094% per passage) and Tube B (0.0144% per passage).

MIC experiments were conducted every two weeks to evaluate the adaptability of E. coli. The 1/2ODMax is used as a gauge to determine the maximum cell density after 21 to 23 hours post inoculation (Figure 1). The increase in 1/2ODMax is possibly due to the fast growers proliferating faster than the slower growers. This would also result in both an increase in 1/2ODMax and AUC.



Figure 3. Area under the curve whereby the concentration of NaCl is more than 7.5%. Increasing AUC suggest that the cells are able to grow at higher salt concentrations with increasing passage counts.

3.2. Rapid Increase of E. coli population in 4% NaCl concentration

Our results suggest the number of generations is generally constant from passage 1 – 43, until it experienced a rise in number of generation from passage 16 – 21. From passage 43 onwards, the number of generations is more inconsistent compared to earlier passages (Figure 4). The coefficient of variations increased from P1 – P15 (3% NaCl) to P16 – P31 (4%NaCl). It decreased in P32 – P39 (4.5%) before increasing again in P40 – P50 (5% NaCl). From P51 onwards, it starts to decrease when NaCl reaches 6% and above (Figure 4).

Our results showed a visible spike in the number of generations can be seen over passage 19 which is at 4% NaCl (Figure 4). The large spike indicates that there is a rapid increase in the number of generations which could be the fast growers of E. coli that adapt well to the 4% NaCl and leading to proliferation. This supports the weeding point as observed in the mean DI values and Coefficients of Variation (CV). The differences in spike for the samples (ranging from 7.6 in Tube A and 12.1 in Tube B) might be a random variation in the samples. Nevertheless, the increase in number of generations was observed in all 4 samples. The adaptability of the E. coli to the NaCl can be known and predicted by looking at the CV. A decrease in CV would indicate a more stable growth of E. coli.
3.3. Generation Time Increases as Salt Concentration Increases

All four replicates have shown an increasing rate of generation time (Figure 5). The rate of increase in ascending order is as follows: Tube C (0.427 minutes per passage), Tube A (0.6777 minutes per passage), Tube B (0.7578 minutes per passage) and Tube D (1.1781 minutes per passage). The average number of generations between each passage was 6.93, with a standard deviation of 0.66 generations. The average OD600 readings at Day 5 and 7 were 0.467 (with a standard deviation of 0.096) and 0.482 (with a standard deviation of 0.140) respectively. Two factor analysis of variance (ANOVA) on the generation time of different concentration of NaCl (treatment) and tube (A, B, C & D) demonstrated that only treatment is significant (F = 3.176, p-value = 0.01) and there is no interaction between the treatments and replicates (F = 0.936, p-value = 0.539).






Figure 4. Coefficient of variation and 2-day generations for all four tubes over 80 passages. Coefficient of variation (CV) is calculated based on the density of cells at day 2 of culture. CV is defined as quotient of standard deviation and mean. Low CV suggests low variation of the cell density at day 2 of culture.



Figure 5. Generation time of four tubes: Tube A, Tube B, Tube C and Tube D across 80 passages. OD600 readings were taken from 2 hours post-inoculation to reduce the impact of varying length of lag phase across different passages and the generation time for each passage is calculated as the geometric mean of the estimated generation time between intervals of OD600 readings from 2 to 5 hours post-inoculation.
4. Discussions

A study by Adam et al. (29) had demonstrated that the increase in resistance can be improved by repetitive exposures to increasing concentration of antibiotics. Similarly, our MIC result showing that the 1/2ODMax had increased in 3 of the 4 replicates suggesting that repetitive exposures to increasing concentration of NaCl could result in increased NaCl tolerance. Perron et al. (30) demonstrated that the speed of adaptation of E. coli to various antibiotics varies according to rate of selection where the evolving population was dependent on the rate of change of antibiotic concentration, and changed over time. Our AUC results suggest that the cells’ proportion which is able to grow at more than 7.5% NaCl as the number of passages increase. 7.5% NaCl is used as a benchmark for testing the adaptability of E. coli as there is no significant growth of E. coli at 7% NaCl (18). Cells that are able to adapt to the 7.5% NaCl have the highest adaptability within the whole population in which they will continue to proliferate resulting in the increase of AUC. Since there is an increment of about 1% NaCl every month during the course of 80 passages, these cells are able to handle the additional stress caused by the higher NaCl concentration. This suggests that the cultures diverge differently from their initial low salt environment and the range of NaCl concentrations at which E. coli adapts had shifted.

For Tube C, the 1/2ODMax varies inversely with its AUC. A reason could be that E. coli in Tube C are able to grow in a wider range of NaCl concentrations. For Tubes A, B and D, the 1/2ODMax varies directly with the AUC which suggests that the cells in Tubes A, B and D adapts at a higher salt concentration as compared to cells in Tube C. This suggests that Tube A, B and D had their salt tolerance shifted to adapt to a higher salt concentration whereas Tube C had its salt tolerance expanded in which it can grow at a wider range of salt concentration. This suggests that Tubes A, B and D had lost the low salt phenotype and unlikely to be able to grow as well in low salt environment compared with the original E. coli ATCC 8739 but Tube C seems to had acquired both high and low salt phenotypes. Our results suggest that a portion of cells (Tube C) are able to adapt to high salt diet but seems to retain preference to a low salt diet compared to others (Tubes A, B and D) which seems to adapt to a high salt phenotype. A recent study (31) had demonstrated that constant culture of E. coli in cellobiose resulted in higher efficiency in cellobiose use. As the MIC was carried out on entire populations, it may be plausible that the population in Tube C had evolved for both high and low salt preferences while the other populations (Tubes A, B and D) might have a larger population of high salt phenotype. However, the isolation of evolved cells with different salt tolerance and preference will require further study.

In Fantin et al. (32), the speed of commensal E. coli adapting to nalidixic acid, ciprofloxacin and levofloxacin was found to be 7 days. Oral ciprofloxacin of varying concentration was administered over 14 days on healthy individuals. This study suggests that the speed of adaptation of E. coli may be similar in adapting to NaCl. However, by considering factors such as the difference in microbicidal effects of NaCl and antibiotics along with the conditions of the experiment, the actual speed of E. coli adapting to NaCl could be different.

Our results suggest that the rate of 1% NaCl concentration increment per month from the previous concentration does not exhibit a bacteriostatic effect as the culture remains sustainable; thus, within the growth/no-growth boundary (20). This suggests that the rate of 1% increment of NaCl concentration per month is within the tolerability of E. coli ATCC 8739 and capable of adapting to this rate of salt concentration increment. However, our results do not suggest that 1% increment per month as the maximum as this will require further study to determine the increment at each salt concentration which demonstrates bacteriostatic effect.

Our results suggest that the CV at 4% is the highest which indicates that the growth of E. coli is the most unstable during 4% NaCl (0.83% to 2.55%). This could be that ‘weeding’ of the slow replicators of E. coli is occurring during 4% NaCl. However, this weeding range is not observed at above 5% NaCl as E. coli in nutrient broth is able to reproduce actively up to 5% with no significant growth at 7% NaCl (18). This suggests that weeding is likely to span between 4% and 5% NaCl. In Hrenovic and Ivankovic (18), E. coli exhibits an absence of bacterial die-off at 3.5% salt concentration. This is primarily attributed to the enriched nutrients available in the media which seemed to be osmotolerant to E. coli. This suggests that 1X nutrient broth media used is able to delay bacterial die-off and for the halophilization of E. coli.

An increase in generation time demonstrated that the treatment affects E. coli ability to adapt and divide. This is supported by Carlucci and Pramer (21) showing that bacteria that are exposed to NaCl typically exhibit a prolonged lag phase and decreasing growth rate in increasing NaCl concentration. Although Liu et al. (33) demonstrated that bacterial cells need time to adapt to the change in environmental conditions, this is not observed in our results as the salt concentration is increased over time. However, our results suggest that the E. coli cells are able to grow at every passage despite the increase in salt concentration. This further suggests that the cells can adapt to the rate of 1% NaCl concentration increment per month.

5. Conclusion

In summary, our findings showed that E. coli is able to adapt to high salt concentrations in a relatively short amount of time. The most important practical implication of our findings is the likelihood of adaptation to medical therapies, such as antibiotics treatment, within human intestines, as well as food preservation techniques.


Acknowledgements:

We wish to thank David Gordon (Botany, Australian National University) for the discussion and input into this study, and G. Pairoh, S. Charoenlustavee and N. Tongpradith (Assumption University, Thailand) for their efforts in assisting in several subcultures. This project was sponsored by Singapore Polytechnic.



Corresponding Author:

Maurice HT Ling

Department of Zoology, The University of Melbourne,

Melbourne, Australia

Tel: +1.6055920300 and +65.96669233

E-mail: mauriceling@acm.org


References

  1. Doyle, M. P. & Erickson, M. C. (2006) Closing the Door on the Fecal Coliform Assay. Microbe, 1, 162-163.

  2. Burton, G. A., Gunnison, D. &Lanza, G. R. (1987) Survival of Pathogenic Bacteria in Various Freshwater Sediments. Applied and Environmental Microbiology, 53, 633-638.

  3. Doudoroff, M. (1940) Experiments on the adaptation of Escherichia coli to sodium chloride. The Journal of General Physiology, 23, 585.

  4. Vaas, K. F. (1938) Studies on the growth of Bacillus megatherium de Bary, Dissertation, Universiteit Leiden.

  5. Saenz, Y., Brinas, L., Dominguez, E., Ruiz, J., Zarazaga, M., Vila, J. & Torres, C. (2004) Mechanisms of resistance in multiple-antibiotic-resistant Escherichia coli strains of human, animal, and food origins. Antimicrobial Agents and Chemotherapy, 48, 3996–4001.

  6. Meng, J., Zhao, S., Doyle, M. P. & Joseph, S. W. (1998) Antibiotic resistance of Escherichia coli O157:H7 and O157:NM isolated from animals, food, and humans. Journal of Food Protection, 61, 1511-4.

  7. Kim, J. S., Heo, P., Yang, T. J., Lee, K. S., Jin, Y. S., Kim, S. K., Shin, D. &Kweon, D. H. 2011. Bacterial persisters tolerate antibiotics by not producing hydroxyl radicals. Biochemical and Biophysical Research Communications, 413, 105-10.

  8. Soufi, L., Saenz, Y., Vinue, L., Abbassi, M. S., Ruiz, E., Zarazaga, M., Ben Hassen, A., Hammami, S. & Torres, C. 2011. Escherichia coli of poultry food origin as reservoir of sulphonamide resistance genes and integrons. International Journal of Food Microbiology, 144, 497-502.

  9. Bibbal, D., Dupouy, V., Prere, M. F., Toutain, P. L. &Bousquet-Melou, A. 2009. Relatedness of Escherichia coli strains with different susceptibility phenotypes isolated from swine feces during ampicillin treatment. Applied and Environmental Microbiology, 75, 2999-3006.

  10. Bibbal, D., Dupouy, V., Ferre, J. P., Toutain, P. L., Fayet, O., Prere, M. F. & Bousquet-Melou, A. 2007. Impact of three ampicillin dosage regimens on selection of ampicillin resistance in Enterobacteriaceae and excretion of blaTEM genes in swine feces. Applied and Environmental Microbiology, 73, 4785-90.

  11. Furtula, V., Farrell, E. G., Diarrassouba, F., Rempel, H., Pritchard, J. &Diarra, M. S. 2010. Veterinary pharmaceuticals and antibiotic resistance of Escherichia coli isolates in poultry litter from commercial farms and controlled feeding trials. Poultry Science, 89, 180-8.

  12. Lee, C. H., Oon, J. S. H., Lee, K. C. & Ling, M. H. (2010) Bactome, I: Python in DNA fingerprinting. The Python Papers, 5, 6.

  13. Lee, C. H., Oon, J. S. H., Lee, K. C. & Ling, M. H. (2012) Escherichia coli ATCC 8739 adapts to the presence of sodium chloride, monosodium glutamate, and benzoic acid after extended culture. ISRN Microbiology, 2012, Article ID 965356.

  14. Nair, S. & Finkel, S. E. 2004. Dps protects cells against multiple stresses during stationary phase. Journal of Bacteriolology, 186, 4192–8.

  15. Jolivet-Gougeon, A., David-Jobert, S., Tamanai-Shacoori, Z., Menard, C. & Cormier, M. 2000. Osmotic stress-induced genetic rearrangements in Escherichia coli H10407 detected by randomly amplified polymorphic DNA analysis. Applied and Environmental Microbiology, 66, 5484-7.

  16. Burg, M. B., Ferraris, J. D. & Dmitrieva, N. I. (2007) Cellular response to hyperosmotic stresses. Physiological Reviews, 87, 1441–74.

  17. Baeza, R., Perez, A., Sanchez, V., Zamora, M., C. & Chirife, J. (2010) Evaluation of Norrish's equation for correlating the water activity of highly concentrated solutions of sugars, polyols, and polyethene glycols. Food Bioprocess Technology, 3, 87–92.

  18. Hrenovic, J. & Ivankovic, T. (2009) Survival of Escherichia coli and Acinetobacter junii at various concentrations of sodium chloride. EurAsian Journal of Biosciences, 3, 144–51.

  19. Norrish, R. S. (1966). An equation for the activity coefficients and equilibrium relative humidities of water in confectionery syrups. Journal of Food Technology, 1, 25–39.

  20. Presser, K. A., Ross, T. & Ratkowsky, D. A. (1998) Modelling the growth limits (growth/no growth interface) of Escherichia coli as a function of temperature, pH, lactic acid concentration, and water activity. Applied and Environmental Microbiology, 64, 1773-1779.

  21. Carlucci, A. F. & Pramer, D. (1960) An evaluation of factors affecting the survival of Escherichia coli in sea water: II. Salinity, pH, and nutrients. Applied Microbiology, 9, 247–50.

  22. Guraya, R., Frank, J. F. & Hassan, A. N. (1998) Effectiveness of salt, pH and diacetyl as inhibitors for Escherichia coli O157:H7 in dairy foods stored at refrigeration temperatures. Journal of Food Protection, 61, 1098-1102.

  23. Oren A. (2008) Microbial life at high salt concentrations: Phylogenetic and metabolic diversity. Saline Systems, 4, 2.

  24. Diamant, S., Eliahu, N., Rosenthal, D. & Goloubinoff, P. (2001) Chemical chaperones regulate molecular chaperones in vitro and in cells under combined salt and heat stresses. Journal of Biological Chemistry, 276, 39586–91.

  25. Ghoul, M., Pommeput, M., Moillo-Batt, A. & Cormier, M. (1989) Effect of carbonyl cyanide m-chlorophenylhydrazone on Escherichia coli halotolerance. Applied and Environmental Microbiology, 55, 1040–43.

  26. Hajmeer, M., Ceylan, E., Marsden, J. L. & Fung, D. Y. (2005) Impact of sodium chloride on Escherichia coli O157:H7 and Staphylococcus aureus analysed using transmission electron microscopy. Food Microbiology, 5, 446-52.

  27. Jay, J. M. M. (1992) E. coli gastroenterritis syndromes. Modern Food Microbiology, 4, 570-575.

  28. Sezonov, G., Joseleau-Petit, D. & D'Ari, R. (2007) Escherichia coli physiology in Luria-Bertani broth. Journal of Bacteriology, 189, 8746–49.

  29. Adam, M., Murali, B., Glenn, N. O. & Potter, S. S. (2008) Epigenetic inheritance based evolution of antibiotic resistance in bacteria. BMC Evolutionary Biology, 8, 52.

  30. Perron, G. G., Gonzalez, A. & Buckling, A. (2008) The rate of environmental change drives adaptation to an antibiotic sink. Journal of Evolutionary Biology, 21, 1724–31.

  31. Vinuselvi, P. & Lee, S. K. (2011) Engineering Escherichia coli for efficient cellobiose utilization. Applied Microbiology and Biotechnology, 92, 125-32.

  32. Fantin, B., Duxal, X., Massias, L., Alavoine, L., Chau, F., Retout, S., Andremont, A. &Mentr, F. (2009) Ciprofloxacin dosage and emergence of resistance in human commensal bacteria. Journal of Infectious Diseases, 200, 390-98.

  33. Liu, Y., Gao, W., Wang, Y., Wu, L., Liu, X., Yan, T., Alm, E., Arkin, A., Thompson, K. D., Fields, W. M. & Zhou, J. (2005) Transcriptome analysis of Shewanella oneidensis MR-1 in response to elevated salt conditions. Journal of Biotechnology, 187, 2501–07.


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