Model-guided design of ligand-regulated RNAi for programmable control of gene expression

Progress in constructing biological networks will rely on the development of more advanced components that can be predictably modified to yield optimal system performance. We have engineered an RNA-based platform, which we call an shRNA switch, that provides for integrated ligand control of RNA interference (RNAi) by modular coupling of an aptamer, competing strand, and small hairpin (sh) RNA stem into a single component that links ligand concentration and target gene expression levels. A combined experimental and mathematical modelling approach identified multiple tuning strategies and moves towards a predictable framework for the forward design of shRNA switches. The utility of our platform is highlighted by the demonstration of fine-tuning, multi-input control, and model-guided design of shRNA switches with an optimized dynamic range. Thus, shRNA switches can serve as an advanced component for the construction of complex biological systems and offer a controlled means of activating RNAi in disease therapeutics

Development and validation of anti-human Alpha synuclein DNA aptamer using computer modelling techniques—an in silico study

Biomarker detection strategies have, in recent years, been moving towards nucleic acid-based detection systems in the form of aptamers, short oligonucleotide sequences which have shown promise in pre-clinical and research settings. One such aptamer is M5-15, a DNA aptamer raised against human alpha synuclein (α-syn) the causative agent in Lewy body and Parkinson’s disease (PD) associated dementia. While this aptamer has shown promise, in silico methodologies have demonstrated a capacity to produce aptamers that have higher affinities for their targets than in vitro generated sequences. A Python script random generated library of DNA sequences were screened based on their thermodynamic stability with the use of DINAMelt server-QuickFold web server. The selected sequences were examined with MFold in order to generate secondary structure data that were used to produce 3D data with the use of RNA composer software. Further on, the structure was corrected and RNA was replaced with DNA and the virtual screening for α-syn aptamer took place with a series of molecular docking experiments with the use of CSD-Discovery-GOLD software. Herein we propose an alternative in silico generated aptamer we call TMG-79 which demonstrates greater affinity for the target compared to M5-15 (M5-15 = –15.9 kcal/mol, TMG-79 = –17.77 kcal/mol) as well as better ChemPLP fitness scoring between the top poses (M5-15 = 32.33, TMG-79 = 53.32). Structural analysis suggests that while there are similarities, the greater potential flexibility of TMG-79 could be promoting greater affinity for the α-syn compared to M5-15. In silico methods of aptamer generation has the potential to revolutionise the field of aptamer design. We feel that further development of TMG-79 and validation in vitro will make it a viable candidate for diagnostic and research use in the future

Smart Approach for the Design of Highly Selective Aptamer-Based Biosensors

Aptamers are chemically synthesized single-stranded DNA or RNA oligonucleotides widely used nowadays in sensors and nanoscale devices as highly sensitive biorecognition elements. With proper design, aptamers are able to bind to a specific target molecule with high selectivity. To date, the systematic evolution of ligands by exponential enrichment (SELEX) process is employed to isolate aptamers. Nevertheless, this method requires complex and time-consuming procedures. In silico methods comprising machine learning models have been recently proposed to reduce the time and cost of aptamer design. In this work, we present a new in silico approach allowing the generation of highly sensitive and selective RNA aptamers towards a specific target, here represented by ammonium dissolved in water. By using machine learning and bioinformatics tools, a rational design of aptamers is demonstrated. This "smart" SELEX method is experimentally proved by choosing the best five aptamer candidates obtained from the design process and applying them as functional elements in an electrochemical sensor to detect, as the target molecule, ammonium at different concentrations. We observed that the use of five different aptamers leads to a significant difference in the sensor's response. This can be explained by considering the aptamers' conformational change due to their interaction with the target molecule. We studied these conformational changes using a molecular dynamics simulation and suggested a possible explanation of the experimental observations. Finally, electrochemical measurements exposing the same sensors to different molecules were used to confirm the high selectivity of the designed aptamers. The proposed in silico SELEX approach can potentially reduce the cost and the time needed to identify the aptamers and potentially be applied to any target molecule

Array-based evolution of DNA aptamers allows modelling of an explicit sequence-fitness landscape

Mapping the landscape of possible macromolecular polymer sequences to their fitness in performing biological functions is a challenge across the biosciences. A paradigm is the case of aptamers, nucleic acids that can be selected to bind particular target molecules. We have characterized the sequence-fitness landscape for aptamers binding allophycocyanin (APC) protein via a novel Closed Loop Aptameric Directed Evolution (CLADE) approach. In contrast to the conventional SELEX methodology, selection and mutation of aptamer sequences was carried out in silico, with explicit fitness assays for 44 131 aptamers of known sequence using DNA microarrays in vitro. We capture the landscape using a predictive machine learning model linking sequence features and function and validate this model using 5500 entirely separate test sequences, which give a very high observed versus predicted correlation of 0.87. This approach reveals a complex sequence-fitness mapping, and hypotheses for the physical basis of aptameric binding; it also enables rapid design of novel aptamers with desired binding properties. We demonstrate an extension to the approach by incorporating prior knowledge into CLADE, resulting in some of the tightest binding sequences

Riboswitches as targets for metabolic engineering in Bacillus subtilis

Many metabolic pathways in bacteria are modulated by metabolite-sensing riboswitches, which regulate gene expression at the level of transcription elongation or translation initiation. Riboswitches represent promising targets to modulate expression of genes and operons relevant for the biotechnological production of commercially relevant compounds. In Firmicutes, approximately 70% of all putative and validated riboswitches (are predicted to) act exclusively at the transcriptional level using a termination-antitermination mechanism. In a first attempt to interfere with purine-sensing riboswitches and deregulate purine metabolism in Bacillus subtilis, a set of synthetic small RNAs (sRNAs) targeting the purine-sensing aptamers were designed to impair ligand binding using rational design combined with in silico evolution. However, the designed sRNAs did not show any activity in vivo on the riboswitch controlling purine biosynthesis (pur operon riboswitch). The effect of the antisense RNA (asRNA) perfectly complementary to the aptamer of the pur operon riboswitch was also tested; The asRNA did not affect negatively expression of a riboswitch-regulated lacZ gene, yet similarly to the partially complementary sRNAs, the asRNA did not impair the downregulation exerted by the riboswitch in the presence of ligand. Finally, expression of the small RNAs in B. subtiliswas quantified, and the kinetic limitations for their hybridization with the aptamer and their competition with the ligand are discussed. A second metabolic engineering strategy based on editing the genome of B. subtilis with regard to transcriptional riboswitches was investigated. Removal of the riboswitches that control purine biosynthesis and riboflavin biosynthesis in B. subtilis led to auxotrophic strains. As an alternative, a rational approach was developed for engineering transcriptional riboswitches independently from the availability of their 3D structures. This approach consists in the identification and deletion of a key nucleotide sequence exclusively involved in transcription termination without affecting formation of other secondary and tertiary structures potentially involved in other roles. To demonstrate the efficacy of the approach, it was applied to derepress the purine and the riboflavin biosynthetic pathways in B. subtilis. Following the proof of concept using specialized reporter strains, the approach was implemented into a B. subtilis wild-type strain employing CRISPR-Cas genome editing. The CRISPRCas9 system displayed an efficiency of 61% in editing the genome, and the resulting purine and riboflavin production strains were characterized at the level of gene expression, metabolite synthesis, and growth. With a substantial enhancement observed at each level, the strategy established here represents a powerful tool for deregulating pathways modulated by transcriptional riboswitches. Finally, applying this strategy to derepress the purine pathway of an industrial riboflavin overproducing strain, with impaired growth, led to an increase in biomass by 53% and resulted in an enhanced total production of riboflavin in the culture

Prostate-specific Rna Aptamer: Promising Nucleic Acid Antibody-like Cancer Detection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)We described the selection of a novel nucleic acid antibody-like prostate cancer (PCa) that specifically binds to the single-stranded DNA molecule from a 277-nt fragment that may have been partially paired and bound to the PCA3 RNA conformational structure. PCA3-277 aptamer ligands were obtained, and the best binding molecule, named CG3, was synthesized for validation. Aiming to prove its diagnostic utility, we used an apta-qPCR assay with CG3-aptamer conjugated to magnetic beads to capture PCA3 transcripts, which were amplified 97-fold and 7-fold higher than conventional qPCR in blood and tissue, respectively. Histopathologic analysis of 161 prostate biopsies arranged in a TMA and marked with biotin-labeled CG3-aptamer showed moderate staining in both cytoplasm and nucleus of PCa samples; in contrast, benign prostatic hyperplasia (BPH) samples presented strong nuclear staining (78% of the cases). No staining was observed in stromal cells. In addition, using an apta-qPCR, we demonstrated that CG3-aptamer specifically recognizes the conformational PCA3-277 molecule and at least three other transcript variants, indicating that long non-coding RNA (lncRNA) is processed after transcription. We suggest that CG3-aptamer may be a useful PCa diagnostic tool. In addition, this molecule may be used in drug design and drug delivery for PCa therapy.5Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Fundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)FAPESP [2012/24911-0]CNPq [490574/2010-6, 457420/2013-8

In silico selection of an aptamer to estrogen receptor alpha using computational docking employing estrogen response elements as aptamer-alike molecules

Aptamers, the chemical-antibody substitute to conventional antibodies, are primarily discovered through SELEX technology involving multi-round selections and enrichment. Circumventing conventional methodology, here we report an in silico selection of aptamers to estrogen receptor alpha (ERα) using RNA analogs of human estrogen response elements (EREs). The inverted repeat nature of ERE and the ability to form stable hairpins were used as criteria to obtain aptamer-alike sequences. Near-native RNA analogs of selected single stranded EREs were modelled and their likelihood to emerge as ERα aptamer was examined using AutoDock Vina, HADDOCK and PatchDock docking. These in silico predictions were validated by measuring the thermodynamic parameters of ERα -RNA interactions using isothermal titration calorimetry. Based on the in silico and in vitro results, we selected a candidate RNA (ERaptR4; 5′-GGGGUCAAGGUGACCCC-3′) having a binding constant (Ka) of 1.02 ± 0.1 × 108 M−1 as an ERα-aptamer. Target-specificity of the selected ERaptR4 aptamer was confirmed through cytochemistry and solid-phase immunoassays. Furthermore, stability analyses identified ERaptR4 resistant to serum and RNase A degradation in presence of ERα. Taken together, an efficient ERα-RNA aptamer is identified using a non-SELEX procedure of aptamer selection. The high-affinity and specificity can be utilized in detection of ERα in breast cancer and related diseases

Developments in the tools and methodologies of synthetic biology.

Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a body of knowledge from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community