Inspiration and intention Build the Adaptors!

Based on the transcriptional factors we landed bio-informatically from numerous papers, we have built fine-tuned and well-characterized biosensors: XylR for BTEX (short for benzene, toluene, ethyl-benzene and xylene), XylS for benzoates, NahR for salicylates, DmpR for phenols, HbpR for biphenyls and HcaR for phenylpropionate with low basal signal, large induction ratio and wide detection range. However, transcriptional factors for aromatics containing other functional groups like alcoholic hydroxyl and aldehyde are not suitable for application in E. coli, either for their poor performance [1] or their unclear activation mechanism [2].

Previous researches that focusing on broadening the detection profiles of biosensors were mainly based on the putative structure of the transcriptional factor and homologous sequence analysis. For example, XylS protein with a mutation of Arginine to Threonine at the 45th codon could be additionally activated by benzoate with substituents at 2, 3 and 4 position of the aromatic ring, for example, the 4-Methoxybenzoate (Fig. 1a) [3]. Likewise, Victor de Lorenzo generated a combinatorial library composed of shuffled N-terminal A domains of the homologous regulators DmpR and XylR, reassembled within the XylR structure. The shuffled TF protein can sense not only xylene but also phenols (Fig. 1b) [4]. These methodologies helped to enrich the inducible ligands of a single transcription regulator. However, they still could not include alcohols and aldehydes into the detection profile of biosensor.

Therefore, new methods are needed to broaden the detection profiles of biosensors.

Here we focused on the aromatics pathways in prokaryotes because aromatic compounds of diverse structures and functional groups are interrelated by enzymes in the catabolic network (Fig. 2). We surveyed through a wide range of metabolic pathways with an eye on their potential to broaden the range of inducers. Excitedly, degradation enzymes along the pathway serve our purpose well. Like electronic adaptor that converts attributes of an otherwise incompatible device to those of another device, these enzymes could be used as “Adaptors for biosensors” to transform originally undetectable intermediates into detectable ligands, thus adding the undetectable upstream intermediates into the detection profile of the existing aromatics-response transcription regulator in the downstream (Fig. 2)!

Degradation enzymes that are comparatively small and well-studied were chosen to function as “Adaptors for biosensors”. XylB (benzaldehyde dehydrogenase) and XylC (benzyl alcohol dehydrogenase) from the toluene degradation pathway and NahF (salicylaldehyde dehydrogenase) from the naphthalene catabolic pathway originated in Pseudomonas putida caught our attention (Fig. 3). Using them as Adaptors, various benzyl alcohols, benzaldehydes and salicylaldehydes are supposed to be detected by the downstream regulator proteins namely XylS and NahR (Fig. 3).

The xyl genes of Pseudomonas putida TOL plasmid that specify catabolism of toluene are organized in two units: the upper-operon xylUWCAMBN for conversion of toluene to benzoate and the meta-operon xylXYZLTEGFJQKIH encoding enzymes for further degradation into TCA cycle intermediates [5]. The transcription factor XylR, which detects toluene, initiates transcription of genes in upper-operon [9-10], including xylB and xylC (Fig. 4).

XylB is benzyl alcohol dehydrogenase (BADH) which degrades benzyl alcohol to benzaldehyde [7]. Previous work showed the recombinant plasmid consisting of xylB gene expressed benzyl-alcohol dehydrogenase in E.coli. Protein expression level and enzyme activity from E.coli cell extracts were tested via β-lactamase assay in vitro, but the no-induced expression is 5 times higher and the induction ratio is only 2 fold [6], much worse than that in Pseudomonas putida. It is interpreted that inefficient transcription of foreign gene in E.coli [7] and the different regulatory pattern, such as transcription orientation and existence of transcription factors, alter the expression intensity of xylB gene, which influences the background signal level. So it is significant to tune the expression of XylB via selecting an appropriate Pc promoter to obtain optimal performance.

XylC is benzaldehyde dehydrogenase (BZDH) degrading benzaldehyde to benzoate in the upper operon [7]. Apart from benzaldehyde, XylC also displays activity towards methyl, nitro, methoxy, and chloro substituents of benzaldehyde [4]. This enzyme has been successfully expressed in E. coli and its catalysis ability in vitro has been proved. Additionally, the substrates of XylC inhibit enzyme activity at milli-molar concentrations [4]. Based on these previous work, we optimized the cultivate condition and appropriate inducer concentration.

According to our work concerning XylS, we have demonstrated that benzaldehyde is originally an inducer of this biosensor, but the induction ratio is apparent low comparing to benzoate. We speculated that the combination of XylS with enzyme XylC would increase the biosensor’s response to benzaldehyde, and further combination with XylB would enable XylS to detect originally undetectable compound benzyl alcohol.

After obtaining correct sequence of XylB and XylC via PCR from TOL plasmid pWW0 in Pseudomonas putida, we constructed recombinant plasmids expressing XylC and XylB respectively, in which the coding sequence locates downstream Pc promoter (Fig. 5).

The performance of XylC Adaptor was tested in following protocol. Bacteria carrying XylC enzyme was overnight-cultured in LB containing kanamycin at 37℃ and then diluted 100 fold into Minimal M9 medium added kanamycin, growing for 12 hours at 30℃ to transform benzyladehydes into benzoates. After the Minimal M9 medium was centrifuged, supernatant medium was taken out and added ampicillin to further culture XylS biosensor. Induction ratio was then obtained following test protocol 1.

The flow cytometry test confirmed our hypothesis: the induction effect of 3-methyl-benzaldehyde and 3-chlorobenzaldehyde towards XylS biosensor equipped with Adaptor XylC ameliorates evidently comparing to biosensor XylS only (Fig. 6a). Furthermore, the dose-response curves of XylS equipped with or without Adaptor XylC for 3-methyl-benzaldehyde and 3-chlorobenzaldehyde (Fig. 6b) showed that . Likewise, dose-response curves for the corresponding acids 3-methyl-benzoate and 3-chlorobenzoate were also collected (Fig. 6c), showing that adding Adaptor XylC does not largely influence the original characteristics of the biosensor.

Further equipped with XylB, the biosensor might obtain the ability to detect benzyl alcohol which cannot be detected directly by neither biosensor XylS nor XylS equipped with XylC. The experiments are undergoing.

Fig. 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.

Fig. 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.

Fig. 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.

Fig. 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