Automated sequence design of nucleic acid hybridization reactions for microRNA detection

[EN] microRNA (miRNA) can be found in a variety of biological samples and then they represent important molecular markers for early diagnostic strategies. This work (TFG) explores a novel approach based on nested non-enzymatic and enzymatic biochemical processes in vitro. In particular, an automated sequence design algorithm of nucleic acid hybridization reactions for microRNA detection is developed.[ES] Los microRNAs (miRNAs) pueden ser hallados en una gran variedad de muestras biológicas y suponen una fuente importante de marcadores moleculares para estrategias de diagnóstico tempranas. En este trabajo (TFG), se explora un abordaje novedoso basado en procesos bioquímicos anidados enzimáticos y no enzimáticos in vitro. Particularmente, se desarrolla un algoritmo de diseño de secuencias automatizado para reacciones de hibridación de ácidos nucleicos para la detección de microRNA.Goiriz Beltrán, L. (2019). Automated sequence design of nucleic acid hybridization reactions for microRNA detection. http://hdl.handle.net/10251/125058TFG

CRISPR-Mediated Strand Displacement Logic Circuits with Toehold-Free DNA

[EN] DNA nanotechnology, and DNA computing in particular, has grown extensively over the past decade to end with a variety of functional stable structures and dynamic circuits. However, the use as designer elements of regular DNA pieces, perfectly complementary double strands, has remained elusive. Here, we report the exploitation of CRISPR-Cas systems to engineer logic circuits based on isothermal strand displacement that perform with toehold-free double-stranded DNA. We designed and implemented molecular converters for signal detection and amplification, showing good interoperability between enzymatic and nonenzymatic processes. Overall, these results contribute to enlarge the repertoire of substrates and reactions (hardware) for DNA computing.We thank V. Aragones (IBMCP) for her technical assistance on PAGE. The work was supported by the Spanish Ministry of Economy and Competitiveness grants BFU2015-66894-P (to GR) and BIO2017-83184-R (to JAD) and by the Spanish Ministry of Science, Innovation, and Universities grant PGC2018-101410-B-I00 (to GR); grants cofinanced by the European Regional Development Fund.Montagud-Martínez, R.; Heras-Hernández, M.; Goiriz, L.; Rodrigo Tarrega, G.; Daròs, J. (2021). CRISPR-Mediated Strand Displacement Logic Circuits with Toehold-Free DNA. ACS Synthetic Biology. 10(5):950-956. https://doi.org/10.1021/acssynbio.0c0064995095610

Non-equilibrium model approaches for genetic systems

[ES] El estudio metabólico de microorganismos brinda la oportunidad de comprender su funcionamiento para modificar su red metabólica y transformarlos en potenciales plataformas industriales. Los actuales modelos metabólicos no incluyen aspectos limitantes de la maquinaria celular, como límites máximos al volumen celular, número máximo de ribosomas o copias de ARN mensajero y, por eso, suelen sobreestimar la capacidad de producción de metabolitos del organismo incluso aunque haya suficientes recursos en el ambiente. Tl presente trabajo pretender abordar el problema mediante una metodología de optimización multiobjetivo mediante algoritmos diferenciales evolutivos de manera que se puedan incluir dichas restricciones de asignación de recursos celulares en el estudio de optimización metabólica. Para ello, se incorporarán nuevas restricciones no lineales en forma de funciones que reducirán el espacio de soluciones del sistema.[EN] The metabolic study of microorganisms provides the opportunity to understand their functioning, to modify their metabolic network, and to transform them into potential industrial platforms. Current metabolic models do not include limiting aspects of cellular machinery, such as maximum cell volume limits, the maximum number of ribosomes or copies of RNA messenger and, therefore, tend to overestimate the microorganism's metabolic production capacity even if there are sufficient resources in the environment. The present work intends to address the problem through a multiobjective optimization methodology through evolutionary differential algorithms so that these restrictions on the allocation of cellular resources can be included in the metabolic optimization study. For this, new non-linear restrictions will be incorporated in the form of functions that will reduce the space of system solutions.Goiriz Beltrán, L. (2020). Non-equilibrium model approaches for genetic systems. http://hdl.handle.net/10251/150995TFG

Nonequilibrium thermodynamics of the RNA-RNA interaction underlying a genetic transposition program

Thermodynamic descriptions are powerful tools to formally study complex gene expression programs evolved in living cells on the basis of macromolecular interactions. While transcriptional regulations are often modeled in the equilibrium, other interactions that occur in the cell follow a more complex pattern. Here, we adopt a nonequilibrium thermodynamic scheme to explain the RNA-RNA interaction underlying IS10 transposition. We determine the energy landscape associated with such an interaction at the base-pair resolution, and we present an original scaling law for expression prediction that depends on different free energies characterizing that landscape. Then, we show that massive experimental data of the IS10 RNA-controlled expression are better explained by this thermodynamic description in nonequilibrium. Overall, these results contribute to better comprehend the kinetics of post-transcriptional regulations and, more broadly, the functional consequences of processes out of the equilibrium in biology.Work was supported by Grant No. PGC2018-101410-BI00 (SYSY-RNA) from the Spanish Ministry of Science, Innovation, and Universities (cofinanced by the European Regional Development Fund). L.G. was supported by CSIC JAE Intro Fellowship No. JAEINT-20-00714.Peer reviewe

A variant-dependent molecular clock with anomalous diffusion models SARS-CoV-2 evolution in humans

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in humans has been monitored at an unprecedented level due to the public health crisis, yet the stochastic dynamics underlying such a process is dubious. Here, considering the number of acquired mutations as the displacement of the viral particle from the origin, we performed biostatistical analyses from numerous whole genome sequences on the basis of a time-dependent probabilistic mathematical model. We showed that a model with a constant variant-dependent evolution rate and nonlinear mutational variance with time (i.e., anomalous diffusion) explained the SARS-CoV-2 evolutionary motion in humans during the first 120 wk of the pandemic in the United Kingdom. In particular, we found subdiffusion patterns for the Primal, Alpha, and Omicron variants but a weak superdiffusion pattern for the Delta variant. Our findings indicate that non-Brownian evolutionary motions occur in nature, thereby providing insight for viral phylodynamics.Work supported by CSIC PTI Global Health (SGL2021-03-040) through the NextGenerationEU Fund (reg. 2020/2094) and Generalitat Valenciana (ACIF/2021/183, GVA-COVID19/2021/100, and GVA-COVID19/2021/036).Funding for open access by Universitat Politècnica de València.Peer reviewe

Gene regulation by a protein translation factor at the single-cell level

Gene expression is inherently stochastic and pervasively regulated. While substantial work combining theory and experiments has been carried out to study how noise propagates through transcriptional regulations, the stochastic behavior of genes regulated at the level of translation is poorly understood. Here, we engineered a synthetic genetic system in which a target gene is down-regulated by a protein translation factor, which in turn is regulated transcriptionally. By monitoring both the expression of the regulator and the regulated gene at the single-cell level, we quantified the stochasticity of the system. We found that with a protein translation factor a tight repression can be achieved in single cells, noise propagation from gene to gene is buffered, and the regulated gene is sensitive in a nonlinear way to global perturbations in translation. A suitable mathematical model was instrumental to predict the transfer functions of the system. We also showed that a Gamma distribution parameterized with mesoscopic parameters, such as the mean expression and coefficient of variation, provides a deep analytical explanation about the system, displaying enough versatility to capture the cell-to-cell variability in genes regulated both transcriptionally and translationally. Overall, these results contribute to enlarge our understanding on stochastic gene expression, at the same time they provide design principles for synthetic biology.This work was supported by the grants H2020-MSCA-ITN-2018 #813239 (RNAct) from the European Commission and PGC2018-101410-B-I00 (SYSY-RNA) from the Spanish Ministry of Science, Innovation, and Universities (co-financed by the European Regional Development Fund) to GR. RD acknowledges a Marie Curie fellowship linked to MSCA-ITN-2018 #813239 and LG a CSIC JAE Intro fellowship (Consejo Superior de Investigaciones Científicas).Peer reviewe

CRISPR-Mediated Strand Displacement Logic Circuits with Toehold-Free DNA

[EN] DNA nanotechnology, and DNA computing in particular, has grown extensively over the past decade to end with a variety of functional stable structures and dynamic circuits. However, the use as designer elements of regular DNA pieces, perfectly complementary double strands, has remained elusive. Here, we report the exploitation of CRISPR-Cas systems to engineer logic circuits based on isothermal strand displacement that perform with toehold-free double-stranded DNA. We designed and implemented molecular converters for signal detection and amplification, showing good interoperability between enzymatic and nonenzymatic processes. Overall, these results contribute to enlarge the repertoire of substrates and reactions (hardware) for DNA computing.We thank V. Aragones (IBMCP) for her technical assistance on PAGE. The work was supported by the Spanish Ministry of Economy and Competitiveness grants BFU2015-66894-P (to GR) and BIO2017-83184-R (to JAD) and by the Spanish Ministry of Science, Innovation, and Universities grant PGC2018-101410-B-I00 (to GR); grants cofinanced by the European Regional Development Fund.Montagud-Martínez, R.; Heras-Hernández, M.; Goiriz, L.; Rodrigo Tarrega, G.; Daròs, J. (2021). CRISPR-Mediated Strand Displacement Logic Circuits with Toehold-Free DNA. ACS Synthetic Biology. 10(5):950-956. https://doi.org/10.1021/acssynbio.0c0064995095610

CRISPR-mediated strand displacement logic circuits with toehold-free DNA

Resumen del trabajo presentado a la 1st International BioDesign Research Conference, celebrada de forma virtual del 1 la 18 de diciembre de 2020.Peer reviewe

Repurposing the mammalian RNA-binding protein Musashi-1 as an allosteric translation repressor in bacteria

The RNA recognition motif (RRM) is the most common RNA-binding protein domain identified in nature. However, RRM-containing proteins are only prevalent in eukaryotic phyla, in which they play central regulatory roles. Here, we engineered an orthogonal post-transcriptional control system of gene expression in the bacterium Escherichia coli with the mammalian RNA-binding protein Musashi-1, which is a stem cell marker with neurodevelopmental role that contains two canonical RRMs. In the circuit, Musashi-1 is regulated transcriptionally and works as an allosteric translation repressor thanks to a specific interaction with the N-terminal coding region of a messenger RNA and its structural plasticity to respond to fatty acids. We fully characterized the genetic system at the population and single-cell levels showing a significant fold change in reporter expression, and the underlying molecular mechanism by assessing the in vitro binding kinetics and in vivo functionality of a series of RNA mutants. The dynamic response of the system was well recapitulated by a bottom-up mathematical model. Moreover, we applied the post-transcriptional mechanism engineered with Musashi-1 to specifically regulate a gene within an operon, implement combinatorial regulation, and reduce protein expression noise. This work illustrates how RRM-based regulation can be adapted to simple organisms, thereby adding a new regulatory layer in prokaryotes for translation control