(670e) In silico Design and Validation of Riboswitches for the High-Throughput Detection of Isoflavone Genistein

Isoflavones are a group of compounds found in soybeans and foods derived from them [1]. These compounds are known to promote health benefits, for example, in the treatment of menopausal symptoms in women, a decrease in the probability of cardiovascular disease and cancer [2]. Of particular interest is the control of symptoms related to hormonal changes associated with menopause due to the absence of definitive treatments [3]. Multiple studies have shown that the administration of isoflavones, mainly genistein, leads to a significant reduction in menopausal symptoms, such as the hot flashes experienced by many women [4]. Also, they appear to induce a sustained cardiovascular response at the uterus, without substantially increasing endometrial thickness [5]. As a result, over the past few years, genistein has attracted much attention from food and pharma companies and consequently, it has been manufactured at industrial scale via chemical synthesis, solid-liquid extraction from soybeans, fermentation processes, and enzymatic synthesis [6][7]. Most of these processes, however, are relatively costly and exhibit low yields, and for this reason, alternatives for higher production rates are of the utmost importance.

Recent efforts have involved the use of microbial factories, which have been enabled by the relative ease for de novo gene synthesis and the corresponding heterologous expression [8]. Despite the success of these approaches, the detection of the produced compounds generally involves the use of expensive and tedious liquid chromatography methods [9]. Alternatively, recent works have described novel biosensors for in situ determination of the recombinantly expressed compounds including, riboswitches enzyme-based and optical biosensors [10]. Due to their ease of manipulation and specificity, riboswitches have recently emerged as robust alternatives for tracking microbial product production [11]. Riboswitches are segments of RNA responsible for regulating the production of proteins and therefore can be incorporated into processes for highly-sensitive selection and detection of the compounds of interest [12]. Despite the potential of these biosensors, this approach relies on exploring a relatively high number of segments (i.e., aptamers) to search for increased specificity. This process could be lengthy and sometimes might even exceed the transformation limit of the microorganism and the number of attainable experiments. As a result, the associated costs could be prohibitive.

To try to overcome this issue, here, we aimed at accelerating the search for testable aptamers by conducting in silico interaction experiments of the candidate RNA sequences with genistein. For this purpose, the secondary structure of the aptamers was predicted via the ViennaRNA package by considering an initial database of 97 nucleotides with 3 regions of folding comprised of 5 variable nucleotides [13]. Also, calculations of the conformational free energy were carried for the active (i,e., ON) and inactive (i.e., OFF) conformations. With the results, it was possible to calculate the probability of occupation of each nucleotide in each variable position of the binding region to the ligand (i.e., genistein) and, therefore, the number of possible useful aptamers were successfully reduced by nine orders of magnitude. Also, terminators (interrupting transcription) and aptamers that are active either in the presence or absence of ligands, were found, which would allow validating the biosensors experimentally in the future. The tertiary structure of the identified aptamers, in conjunction with genistein, was predicted via AutoDock Vina. Additional details of the interactions were explored by Molecular Dynamics (MD) simulations in GROMACS to reduce even further the number of candidates for experimental evaluation [14][15][16].

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