As for the analysis of environmental samples, the comprehensiveness and complexity of it must be considered. Environmental samples usually contain lots of components, which are not only of diverse structures but also at quite low concentrations (Table.1) [1][2]. Therefore, a robust detection method serving the purpose of multicomponent analysis is highly meaningful when it comes to environmental analysis. To apply the well-characterization biosensors we built in multicomponent analysis, the nonexistence of synergistic or antagonistic effects, in another word, orthogonality, among inducers should be confirmed.

Biosensors were subjected to the orthogonality test, in which whether there was synergistic or antagonistic effect among inducers was tested.

Orthoganaility between inducer A (originally detected by biosensor I) and B (originally detected by biosensor II) were tested in the following manner (Fig.1). To test the effect of inducer B upon the dose-response curve of inducer A obtained by biosensor I:
(1) Fluorescence intensity of biosensor I elicited by inducer A of concentration gradient was measured as standard results (Fig.1a, Lane 1);
(2) And fluorescence intensity of biosensor I induced by inducer A of concentration gradient in the presence of a certain concentration of inducer B was measured (Fig.1a, Lane 2 and 3) and compared with the standard results.

The effect of inducer A upon the dose-response curve of inducer B obtained by biosensor II was tested vice versa (Fig.1b).

We managed to demonstrate the orthogonality among inducers of different biosensors in a more quantitative and visible way (Fig.2). X-axis represented the fluorescence intensity of biosensor I induced by inducer A, while Y-axis represented the fluorescence intensity of biosensor I induced by inducer A along with inducer B (Fig.2a). If inducer A and B were orthogonal, the fluorescence intensity should be identical no matter with or without the irrelevant inducer B. That is to say, the ideal experimental points should be aligned in a line whose slope is one (Fig.2b).

The orithogonality of inducers of XylS, NahR, HbpR and DmpR biosensors have been carefully confirmed using the test assay introduced above (Fig.3). The experimental points were processed by linear fitting and the slopes of the fitting curves were compared with 1. The closer the slope was to 1, the more orthogonal the inducers were. The results showed that inducers of biosensor XylS and NahR (Fig.3a,b), XylS and HbpR (Fig.3c,d), NahR and HbpR (Fig.3e,f), XylS and DmpR (Fig.3g,h), NahR and DmpR (Fig.3i,j), and HbpR and DmpR (Fig.3k,l) are all highly orthogonal, which is summarized in Fig.4.

In conclusion, we have confirmed the orthogonality among inducers of different biosensors, which is one of the main features we expect for our aromatics-sensing toolkit. Our sensors are well suited to multicomponent analysis.

Figure 1. Orthogonality test assay for inducer A (detected by biosensor I) and inducer B (detected by biosensor II). (a) Biosensor I was added into the test assay. Different mixtures of inducers were added into lane 1, 2, and 3 respectively as listed above. Effect of inducer B upon the dose-response curve of inducer A was tested by comparing the fluorescence intensity of biosensor I among lane 1 ,2, and 3. (b) Biosensor II was added into the test assay. Different mixtures of inducers were added into lane 1, 2, and 3 respectively as listed above. Effect of inducer A upon the dose-response curve of inducer B was tested by comparing the fluorescence intensity of biosensor II among lane 1 ,2, and 3.

Figure 2. Schematic diagram for the way we demonstrated the orthogonality between biosensors’ inducers. (a) The distribution of data in the X-Y plot: fluorescence intensity of biosensor in lane 1 was used as X-coordinate of experimental point; while fluorescence intensity of biosensor in lane 2 or 3 was used as Y-coordinate of the experimental point. (b) If the two inducers were orthogonal, the experimental points was supposed to be aligned in a line whose slope is one.

Figure 3. Experimental points and the linear fitting curves of the orthogonality test. The black dashed lines are with the slopes of 1, showing as the reference line. The slopes of the experimental fitting curves were showed in the upside portion of the figure, all of them were around 1. These data showed the orthogonality among inducers of biosensors(a, b) XylS and NahR; (c, d) XylS and HbpR; (e, f) NahR and HbpR, (g, h) XylS and DmpR, (i, j) NahR and DmpR, and (k, l) HbpR and DmpR. The experimental points and linear fitting curves of biosensor and its inducers are marked in different colors: XylS in red, NahR in green, HbpR in orange and DmpR in dark cyan.

Figure 4. Summary of the orthogonality among four sensors’ inducers. The inducers among biosensor XylS and NahR, XylS and HbpR, NahR and HbpR, XylS and DmpR, NahR and DmpR, and HbpR and DmpR are all highly orthogonal.

Reference:
[1] Zhang lanying, Pre-treatment Technology for Environmental Samples [M]. Beijing, Tsinghua University Press. 2008.
[2] Constantini Samara et. al. (2008) Distribution of persistent organic pollutants, polycyclic aromatic hydrocarbons and trace elements in soil and vegetation following a large scale landfill fire in northern Greece, Environment International. 34:210 – 225