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. 2016 May 12;11(5):e0155338.
doi: 10.1371/journal.pone.0155338. eCollection 2016.

Composing a Tumor Specific Bacterial Promoter

Igor V Deyneko  1 , Nadine Kasnitz  1 , Sara Leschner  1 , Siegfried Weiss  1   2
Affiliations

Composing a Tumor Specific Bacterial Promoter

Igor V Deyneko et al. PLoS One. .

Abstract

Systemically applied Salmonella enterica spp. have been shown to invade and colonize neoplastic tissues where it retards the growth of many tumors. This offers the possibility to use the bacteria as a vehicle for the tumor specific delivery of therapeutic molecules. Specificity of such delivery is solely depending on promoter sequences that control the production of a target molecule. We have established the functional structure of bacterial promoters that are transcriptionally active exclusively in tumor tissues after systemic application. We observed that the specific transcriptional activation is accomplished by a combination of a weak basal promoter and a strong FNR binding site. This represents a minimal set of control elements required for such activation. In natural promoters, additional DNA remodeling elements are found that alter the level of transcription quantitatively. Inefficiency of the basal promoter ensures the absence of transcription outside tumors. As a proof of concept, we compiled an artificial promoter sequence from individual motifs representing FNR and basal promoter and showed specific activation in a tumor microenvironment. Our results open possibilities for the generation of promoters with an adjusted level of expression of target proteins in particular for applications in bacterial tumor therapy.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Identification and analysis steps of tumor specific promoters.
A schematic overview. Two programs for basal promoter recognition, one based on sequence alignment kernel [11] and another on Hidden Markov Model (HMM) [12] were applied to the TSP set (DNA sequences are given in the S1 Text). As a negative control, a set of DNA fragments that do not initiate expression either in tumor or in spleen was selected (negative promoters, NP). Both programs recognize potential promoters in either dataset and the number of predictions greatly depends on user-defined threshold parameters. To evaluate the specificity of predictions, it was assumed that a basal promoter should be recognized in at least 75% of TSP and at most 50% of NPs (see Methods). This will ensure the generality and specificity of the recognized feature.
Fig 2
Fig 2. Top motifs identified in the set of tumor specific promoters and its distribution within different groups of promoters.
Values are normalized numbers of promoters in a set containing at least one motif. P-values were calculated as a binomial probability to observe the actual number of promoters with a motif in the TSP set compared to RP set. A potential overfitting effect of prediction methods can be estimated using an independent lowTSP set (see Methods).
Fig 3
Fig 3. Schematic representation of promoter structure.
Left: binding motifs for factors TGIF, FNR and NagC are shown in green, yellow and brown, respectively. Basal promoter is shown as a directed arrow. Knockout of essential nucleotides within motifs were according to the literature and are represented by crossing lines. Mutation of non-essential nucleotides within motifs was random and is represented by dashed crossing lines. Nucleotides outside motifs were mutated randomly. Right: representative flow-cytometric analyses of GFP-expression in tumor and spleen. Each green point on the blots represents GFP expression levels of an individual bacterial cell. Displayed values of expression are relative to the expression values of the original promoter P0.212_1. All nucleotide substitutions are presented in the S2 Fig.
Fig 4
Fig 4. Expression of promoters P1.6 and P0.212_1 in tumor, spleen and liver.
Homogenates were analyzed via two color flow cytometry and plating to allow normalization. Given are mean and SD. Expression of P1.6 in spleen and liver can be considered negligible compared to expression in tumor. Therefore expression of promoter P1.6 was accepted as tumor specific.
Fig 5
Fig 5. Schematic representation of artificial promoters and their expression in tumor environment.
Promoters were compiled by introduction of the respective elements taken from promoters P0.212, P1.6, P0.134 as well as consensus sequences into the template sequence. Additionally, regions around TSS were enriched for A/T to facilitate DNA melting. Expression values are relative to the expression of P0.212_1. Given are mean±SD. Only promoter P2.3 showed expression in tumor. No expression in tumor or spleen could be observed for the other promoters. Nucleotide sequences are presented in the S3 Fig. Foot note: I, II, III—corresponding sequences were taken from promoters P0.212, P1.6, P0.134 respectively. cons—consensus sequences for the corresponding elements. a, b—modification of loci around putative start of transcription to facilitate DNA melting by random substitution of "C/G"s by "A/T"s.
Fig 6
Fig 6. Activation of bacterial tumor-specific promoters under various conditions.
(A) Expression ratios of tumor specific promoters in anaerobic and aerobic environments. For comparison, ratios for tumor and spleen are given. Three groups can be identified: group A–promoters that have similar expression (tumor—high; spleen—low; anaerobic -high; aerobic -low); group B–promoters that lost expression under anaerobic conditions and group C–promoters showing higher expression under aerobic conditions compared to anaerobic. Data were acquired 4 hrs after initiation of the cultures. (B) Promoter activation under acidic induction medium conditions. Only promoter P0.134 and its fragment P0.134_1 show expression. Promoter grouping is the same as in Fig 6A. Data were acquired 3 hrs after initiation of the cultures. The experiments were carried out twice under similar conditions. Results were essentially the same.
Fig 7
Fig 7. Localization of Salmonella expressing GFP under control of P0.212_1 within various regions of solid murine tumors.
Consecutive tumor sections are shown. (A) Hematoxylin and eosin (H&E) staining showing infiltration of live immune cells (closed purple nuclei) between viable (V) and necrotic (N) tumor zones. (B) Immunochemical detection of hypoxic tissue (light brown staining) by a rabbit-anti-pimonidazole antibody and (C) S. Typhimurium strain SL7207 cells (dark brown) by a rabbit-anti-salmonella antibody. Here, arrow heads indicate vessles, long arrows indicate sebaceous glands.
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This work was supported in part by the Deutsche Krebshife and the Ministry for Education and Research (BMBF). NK was supported by the Helmholtz Graduate School for Infection Research. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.