Q-313. Toxicity Assessment of Contaminants via Gene Expression Profiling in E. coli

A. Onnis-Hayden, G. Casadei, P. J. Beuning, K. Lewis, A. Gu;
Northeastern Univ., Boston, MA.

Background: Considering the growing list of potential contaminants in water and the synergistic effects from the presence of multiple compounds, a feasible method for evaluating the aggregate potential toxicity present in water sample is needed. This study investigated the potential of using gene expression profiling in E. coli as a tool for toxicity assessment of a diverse group of environmental pollutants in water samples. Methods: A library that consists of over 1000 genes with transcriptional fusions of GFP hosted by E. coli K12 was applied to evaluate the gene expression profile in response to a number of selected toxic pollutants, including those on the EPA priority pollutants list and other emerging pollutants such as PPCPs and EDCs (Table 1). Results: The results in Table 2 show that sensitivity of gene expression varies for different genes and the pattern of dose-response with changing toxin concentration is compound-specific. For example the gene sulA is over-expressed compared to control when 4-Nonylphenol is added, and its response increases with increasing concentration. Whereas, for 17beta estradiol, the response level did not increase as the dose concentration increased from 0.1 to 1000 μg/L and there is a concentration that yields the highest response. The induction factors for all the compounds tested ranged from 1 to 5. In addition, the global gene expression information also provided insights into the mechanism of toxic action. For ex., the antibiotic Mitomycin-C tested had high induction factors for all known SOS response genes that are involved in DNA repair. This is consistent with the fact that Mitomycin-C is a known genotoxin. Conclusions: Contaminant-induced gene expression profiling of E. coli can provide quantitative and system-functional-level toxicity assessment of pollutants. Both time and contaminant concentration should be considered during the toxicity assessment. The establishment of gene profiling data base with signature profiling specific to a compound or a class of compounds will allow simultaneous detection and identification of toxins present in water and wastewater samples.

Table 1. Compounds and concentrations tested.

ID

NAME

Category

Concentrations tested [µg/l]

Note

4NNP

4 Nonylphenol

Surfactant

10

100

400

800

in DMSO 0.0025%

Estriol

Estriol

Estrogen

0.01

0.1

10

100

in alcohol 0.00001%

17beta

17 β estradiol

Estrogen

0.1

1

10

100

in alcohol 0.00001%

BiA

Bisphenol A

Plasticizer

1

10

100

1000

in acetone 0.01%

Tri

Triclosan

Antimicrobial disinfectant

1

10

100

1000

in acetone 0.01%

Atr

Atrazine

Pesticide

0.1

1

10

100

in methanol 0.01%

MCC

MitomicinC

Antibiotic

0.1

1

10

100

in methanol 0.01%

 

Table 2. Results of dose-response tests for 17beta estradiol and 4Nonylphenol.

 

17beta estradiol

 

Reporter gene Induction factor Fi

Dose [µg/l]

sulA

recA

umuD

gadX

0.1

 

1.06

1.11

1.48

1

 

1.14

1.29

1.34

10

1

1.2

1.39

1.17

100

1.04

1.1

1.21

1.17

1000

1.11

1.2

1.2

1.18

 

4-Nonylphenol

 

Reporter gene Induction factor Fi

Dose [µg/l]

sulA

recA

umuD

gadX

10

1.47

1

1.15

1.18

100

1.43

1.07

1.2

1.11

400

1.72

1.13

 

1.24

800

2.01

1.45

1.51

2.04