Composing a Tumor Specific Bacterial Promoter

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.

BestCRM: An Exhaustive Search for Optimal Cis-Regulatory Modules in Promoters Accelerated by the Multidimensional Hash Function

“…The process of gene regulation involves transcription factors (TFs) binding to specific regions of the genome, such as proximal promoters or distal enhancers, to control gene expression [1]. TF binding to its target sites (TFBS) often occurs cooperatively, forming cisregulatory modules (CRMs) that are essential for effective and highly specific transcriptional regulation [2]. Collaborations between TFs, whether synergistic or antagonistic, impact gene specificity and regulatory flexibility during processes like tissue development or response to stimuli [3].…”

Guidelines on the performance evaluation of motif recognition methods in bioinformatics

“…However, when it comes to the practical use of bioinformatic predictors, a researcher is often puzzled, first by selecting an appropriate bioinformatic program and then by a huge list of predictions that such programs usually produce. Once several programs are used to increase the chances of one at least finding a real functional motif, the list of predictions becomes too long for experimental verification ( Deyneko et al, 2016 ), even though independently found similar motifs are more likely to be correct and can be given higher priority ( Machanick and Kibet, 2017 ).…”

Advances in bacterial cancer therapies using synthetic biology

“…By sorting and sequencing GFP expressing bacteria, they were able to identify tumor specific promoters [27]. In a follow-up paper, Deyneko et al then adapted these promoters and incorporated hypoxia sensing elements to build a synthetic tumor specific hypoxic promoter [28]. …”