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.

Plant virus-derived nanoparticles decorated with genetically encoded SARS-CoV-2 nanobodies display enhanced neutralizing activity.

Viral nanoparticles (VNPs) are a new class of virus-based formulations that can be used as building blocks to implement a variety of functions of potential interest in biotechnology and nanomedicine. Viral coat proteins (CP) that exhibit self-assembly properties are particularly appropriate for displaying antigens and antibodies, by generating multivalent VNPs with therapeutic and diagnostic potential. Here, we developed genetically encoded multivalent VNPs derived from two filamentous plant viruses, potato virus X (PVX) and tobacco etch virus (TEV), which were efficiently and inexpensively produced in the biofactory Nicotiana benthamiana plant. PVX and TEV-derived VNPs were decorated with two different nanobodies recognizing two different regions of the receptor-binding domain (RBD) of the SARS-CoV-2 Spike protein. The addition of different picornavirus 2A ribosomal skipping peptides between the nanobody and the CP allowed for modulating the degree of VNP decoration. Nanobody-decorated VNPs purified from N. benthamiana tissues successfully recognized the RBD antigen in enzyme-linked immunosorbent assays and showed efficient neutralization activity against pseudoviruses carrying the Spike protein. Interestingly, multivalent PVX and TEV-derived VNPs exhibited a neutralizing activity approximately one order of magnitude higher than the corresponding nanobody in a dimeric format. These properties, combined with the ability to produce VNP cocktails in the same N. benthamiana plant based on synergistic infection of the parent PVX and TEV, make these green nanomaterials an attractive alternative to standard antibodies for multiple applications in diagnosis and therapeutics.

Agave Wilt Susceptibility by Reduction of Free Hexoses in Root Tissue of Agave tequilana Weber var. azul Commercial Plants in the Fructan Accumulation Process.

Agave tequilana stems store fructan polymers, the main carbon source for tequila production. This crop takes six or more years for industrial maturity. In conducive conditions, agave wilt disease increases the incidence of dead plants after the fourth year. Plant susceptibility induced for limited photosynthates for defense is recognized in many crops and is known as "sink-induced loss of resistance". To establish whether A. tequilana is more prone to agave wilt as it ages, because the reduction of water-soluble carbohydrates in roots, as a consequence of greater assembly of highly polymerized fructans, were quantified roots sucrose, fructose, and glucose, as well as fructans in stems of agave plants of different ages. The damage induced by inoculation with Fusarium solani or F. oxysporum in the roots or xylem bundles, respectively, was recorded. As the agave plant accumulated fructans in the stem as the main sink, the amount of these hexoses diminished in the roots of older plants, and root rot severity increased when plants were inoculated with F. solani, as evidence of more susceptibility. This knowledge could help to structure disease management that reduces the dispersion of agave wilt, dead plants, and economic losses at the end of agave's long crop cycle.

Multiplexable and Biocomputational Virus Detection by CRISPR-Cas9-Mediated Strand Displacement.

Recurrent disease outbreaks caused by different viruses, including the novel respiratory virus SARS-CoV-2, are challenging our society at a global scale; so versatile virus detection methods would enable a calculated and faster response. Here, we present a novel nucleic acid detection strategy based on CRISPR-Cas9, whose mode of action relies on strand displacement rather than on collateral catalysis, using the Streptococcus pyogenes Cas9 nuclease. Given a preamplification process, a suitable molecular beacon interacts with the ternary CRISPR complex upon targeting to produce a fluorescent signal. We show that SARS-CoV-2 DNA amplicons generated from patient samples can be detected with CRISPR-Cas9. We also show that CRISPR-Cas9 allows the simultaneous detection of different DNA amplicons with the same nuclease, either to detect different SARS-CoV-2 regions or different respiratory viruses. Furthermore, we demonstrate that engineered DNA logic circuits can process different SARS-CoV-2 signals detected by the CRISPR complexes. Collectively, this CRISPR-Cas9 R-loop usage for the molecular beacon opening (COLUMBO) platform allows a multiplexed detection in a single tube, complements the existing CRISPR-based methods, and displays diagnostic and biocomputing potential.

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.

Suprathreshold Stochastic Resonance behind Cancer.

Noise in gene expression is pervasive and, in some cases, even fulfills a functional role. Cancer cell populations exploit noise to increase heterogeneity as a defense against therapies. What lies behind this picture is a phenomenon of stochastic resonance led by the collective, rather than by individual cells.

Molecular signatures of silencing suppression degeneracy from a complex RNA virus.

As genomic architectures become more complex, they begin to accumulate degenerate and redundant elements. However, analyses of the molecular mechanisms underlying these genetic architecture features remain scarce, especially in compact but sufficiently complex genomes. In the present study, we followed a proteomic approach together with a computational network analysis to reveal molecular signatures of protein function degeneracy from a plant virus (as virus-host protein-protein interactions). We employed affinity purification coupled to mass spectrometry to detect several host factors interacting with two proteins of Citrus tristeza virus (p20 and p25) that are known to function as RNA silencing suppressors, using an experimental system of transient expression in a model plant. The study was expanded by considering two different isolates of the virus, and some key interactions were confirmed by bimolecular fluorescence complementation assays. We found that p20 and p25 target a common set of plant proteins including chloroplastic proteins and translation factors. Moreover, we noted that even specific targets of each viral protein overlap in function. Notably, we identified argonaute proteins (key players in RNA silencing) as reliable targets of p20. Furthermore, we found that these viral proteins preferentially do not target hubs in the host protein interactome, but elements that can transfer information by bridging different parts of the interactome. Overall, our results demonstrate that two distinct proteins encoded in the same viral genome that overlap in function also overlap in their interactions with the cell proteome, thereby highlighting an overlooked connection from a degenerate viral system.

Binary addition in a living cell based on riboregulation.

Synthetic biology aims at (re-)programming living cells like computers to perform new functions for a variety of applications. Initial work rested on transcription factors, but regulatory RNAs have recently gained much attention due to their high programmability. However, functional circuits mainly implemented with regulatory RNAs are quite limited. Here, we report the engineering of a fundamental arithmetic logic unit based on de novo riboregulation to sum two bits of information encoded in molecular concentrations. Our designer circuit robustly performs the intended computation in a living cell encoding the result as fluorescence amplitudes. The whole system exploits post-transcriptional control to switch on tightly silenced genes with small RNAs, together with allosteric transcription factors to sense the molecular signals. This important result demonstrates that regulatory RNAs can be key players in synthetic biology, and it paves the way for engineering more complex RNA-based biocomputers using this designer circuit as a building block.

Viral Fitness Correlates with the Magnitude and Direction of the Perturbation Induced in the Host's Transcriptome: The Tobacco Etch Potyvirus-Tobacco Case Study.

Determining the fitness of viral genotypes has become a standard practice in virology as it is essential to evaluate their evolutionary potential. Darwinian fitness, defined as the advantage of a given genotype with respect to a reference one, is a complex property that captures, in a single figure, differences in performance at every stage of viral infection. To what extent does viral fitness result from specific molecular interactions with host factors and regulatory networks during infection? Can we identify host genes in functional classes whose expression depends on viral fitness? Here, we compared the transcriptomes of tobacco plants infected with seven genotypes of tobacco etch potyvirus that differ in fitness. We found that the larger the fitness differences among genotypes, the more dissimilar the transcriptomic profiles are. Consistently, two different mutations, one in the viral RNA polymerase and another in the viral suppressor of RNA silencing, resulted in significantly similar gene expression profiles. Moreover, we identified host genes whose expression showed a significant correlation, positive or negative, with the virus' fitness. Differentially expressed genes which were positively correlated with viral fitness activate hormone- and RNA silencing-mediated pathways of plant defense. In contrast, those that were negatively correlated with fitness affect metabolism, reducing growth, and development. Overall, these results reveal the high information content of viral fitness and suggest its potential use to predict differences in genomic profiles of infected hosts.

Inferring the regulatory network of the miRNA-mediated response to biotic and abiotic stress in melon.

BACKGROUND: MiRNAs have emerged as key regulators of stress response in plants, suggesting their potential as candidates for knock-in/out to improve stress tolerance in agricultural crops. Although diverse assays have been performed, systematic and detailed studies of miRNA expression and function during exposure to multiple environments in crops are limited. RESULTS: Here, we present such pioneering analysis in melon plants in response to seven biotic and abiotic stress conditions. Deep-sequencing and computational approaches have identified twenty-four known miRNAs whose expression was significantly altered under at least one stress condition, observing that down-regulation was preponderant. Additionally, miRNA function was characterized by high scale degradome assays and quantitative RNA measurements over the intended target mRNAs, providing mechanistic insight. Clustering analysis provided evidence that eight miRNAs showed a broad response range under the stress conditions analyzed, whereas another eight miRNAs displayed a narrow response range. Transcription factors were predominantly targeted by stress-responsive miRNAs in melon. Furthermore, our results show that the miRNAs that are down-regulated upon stress predominantly have as targets genes that are known to participate in the stress response by the plant, whereas the miRNAs that are up-regulated control genes linked to development. CONCLUSION: Altogether, this high-resolution analysis of miRNA-target interactions, combining experimental and computational work, Illustrates the close interplay between miRNAs and the response to diverse environmental conditions, in melon.

Model-based design of RNA hybridization networks implemented in living cells.

Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermodynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations.

Identification, introgression, and validation of fruit volatile QTLs from a red-fruited wild tomato species.

Volatile organic compounds (VOCs) are major determinants of fruit flavor, a primary objective in tomato breeding. A recombinant inbred line (RIL) population consisting of 169 lines derived from a cross between Solanum lycopersicum and a red-fruited wild tomato species Solanum pimpinellifolium accession (SP) was characterized for VOCs in three different seasons. Correlation and hierarchical cluster analyses were performed on the 52 VOCs identified, providing a tool for the putative assignation of individual compounds to metabolic pathways. Quantitative trait locus (QTL) analysis, based on a genetic linkage map comprising 297 single nucleotide polymorphisms (SNPs), revealed 102 QTLs (75% not described previously) corresponding to 39 different VOCs. The SP alleles exerted a positive effect on most of the underlying apocarotenoid volatile QTLs-regarded as desirable for liking tomato-indicating that alleles inherited from SP are a valuable resource for flavor breeding. An introgression line (IL) population developed from the same parental genotypes provided 12 ILs carrying a single SP introgression and covering 85 VOC QTLs, which were characterized at three locations. The results showed that almost half of the QTLs previously identified in the RILs maintained their effect in an IL form, reinforcing the value of these QTLs for flavor/aroma breeding in cultivated tomato.

Molecular noise can minimize the collective sensitivity of a clonal heterogeneous cell population.

It is now widely accepted that molecular noise, rather than be always detrimental, introduces in many circumstances the required boost to reach fundamental cellular activities or strategies otherwise unattainable. In threshold-like genetic systems, molecular noise serves to generate heterogeneous responses in a clonal population, also in a tissue, due to cell-to-cell variability. Here, we derived a mathematical framework from which we could study in detail this effect. We focused on a minimal decision-making gene circuit implemented as a transcriptional positive-feedback loop. We evidenced that when the individual responses of each cell within the population are averaged, a sort of collective behavior, the resulting dose-response curve is linearized. In other words, the population is less sensitive than the individuals, which otherwise enhances the information transfer from signal to response. We found that the distance to the ideal linear response of the cell population is minimized for a particular noise level, and also characterized the interplay between intrinsic and extrinsic noise. Overall, our results highlight how cells could, by acting as a collective, entangle their genetic systems with their environments by adjusting the intracellular noise levels.

Genetic Redundancies Enhance Information Transfer in Noisy Regulatory Circuits.

Cellular decision making is based on regulatory circuits that associate signal thresholds to specific physiological actions. This transmission of information is subjected to molecular noise what can decrease its fidelity. Here, we show instead how such intrinsic noise enhances information transfer in the presence of multiple circuit copies. The result is due to the contribution of noise to the generation of autonomous responses by each copy, which are altogether associated with a common decision. Moreover, factors that correlate the responses of the redundant units (extrinsic noise or regulatory cross-talk) contribute to reduce fidelity, while those that further uncouple them (heterogeneity within the copies) can lead to stronger information gain. Overall, our study emphasizes how the interplay of signal thresholding, redundancy, and noise influences the accuracy of cellular decision making. Understanding this interplay provides a basis to explain collective cell signaling mechanisms, and to engineer robust decisions with noisy genetic circuits.

Dynamic signal processing by ribozyme-mediated RNA circuits to control gene expression.

Organisms have different circuitries that allow converting signal molecule levels to changes in gene expression. An important challenge in synthetic biology involves the de novo design of RNA modules enabling dynamic signal processing in live cells. This requires a scalable methodology for sensing, transmission, and actuation, which could be assembled into larger signaling networks. Here, we present a biochemical strategy to design RNA-mediated signal transduction cascades able to sense small molecules and small RNAs. We design switchable functional RNA domains by using strand-displacement techniques. We experimentally characterize the molecular mechanism underlying our synthetic RNA signaling cascades, show the ability to regulate gene expression with transduced RNA signals, and describe the signal processing response of our systems to periodic forcing in single live cells. The engineered systems integrate RNA-RNA interaction with available ribozyme and aptamer elements, providing new ways to engineer arbitrary complex gene circuits.

Interaction network of tobacco etch potyvirus NIa protein with the host proteome during infection.

BACKGROUND: The genomes of plant viruses have limited coding capacity, and to complete their infectious cycles, viral factors must target, direct or indirectly, many host elements. However, the interaction networks between viruses and host factors are poorly understood. The genus Potyvirus is the largest group of plus-strand RNA viruses infecting plants. Potyviral nuclear inclusion a (NIa) plays many roles during infection. NIa is a polyprotein consisting of two domains, viral protein genome-linked (VPg) and protease (NIaPro), separated by an inefficiently utilized self-proteolytic site. To gain insights about the interaction between potyviral NIa and the host cell during infection, we constructed Tobacco etch virus (TEV, genus Potyvirus) infectious clones in which the VPg or the NIaPro domains of NIa were tagged with the affinity polypeptide Twin-Strep-tag and identified the host proteins targeted by the viral proteins by affinity purification followed by mass spectrometry analysis (AP-MS). RESULTS: We identified 232 different Arabidopsis thaliana proteins forming part of complexes in which TEV NIa products were also involved. VPg and NIaPro specifically targeted 89 and 76 of these proteins, respectively, whereas 67 proteins were targeted by both domains and considered full-length NIa targets. Taking advantage of the currently known A. thaliana interactome, we constructed a protein interaction network between TEV NIa domains and 516 host proteins. The most connected elements specifically targeted by VPg were G-box regulating factor 6 and mitochondrial ATP synthase δ subunit; those specifically targeted by NIaPro were plasma membrane aquaporin PIP2;7 and actin 7, whereas those targeted by full-length NIa were heat shock protein 70-1 and photosystem protein LHCA3. Moreover, a contextualization in the global A. thaliana interactome showed that NIa targets are not more connected with other host proteins than expected by chance, but are in a position that allows them to connect with other host proteins in shorter paths. Further analysis of NIa-targeted host proteins revealed that they are mainly involved in response to stress, metabolism, photosynthesis, and localization. Many of these proteins are connected with the phytohormone ethylene. CONCLUSIONS: Potyviral NIa targets many host elements during infection, establishing a network in which information is efficiently transmitted.

A new frontier in synthetic biology: automated design of small RNA devices in bacteria.

RNA devices provide synthetic biologists with tools for manipulating post-transcriptional regulation and conditional detection of cellular biomolecules. The use of computational methods to design RNA devices has improved to the stage where it is now possible to automate the entire design process. These methods utilize structure prediction tools that optimize nucleotide sequences, together with fragments of known independent functionalities. Recently, this approach has been used to create an automated method for the de novo design of riboregulators. Here, we describe how it is possible to obtain riboregulatory circuits in prokaryotes by capturing the relevant interactions of RNAs inside the cytoplasm using a physicochemical model. We focus on the regulation of protein expression mediated by intra- or intermolecular interactions of small RNAs (sRNAs), and discuss the design of riboregulators for other functions. The automated design of RNA devices opens new possibilities for engineering fully synthetic regulatory systems that program new functions or reprogram dysfunctions in living cells.

Exploring the Dynamics and Mutational Landscape of Riboregulation with a Minimal Synthetic Circuit in Living Cells.

The regulation of gene expression, triggered by conformational changes in RNA molecules, is widely observed in cellular systems. Here, we examine this mode of control by means of a model-based design and construction of a fully synthetic riboregulatory device. We present a theoretical framework that rests on a simple energy model to predict the dynamic response of such a system. Following an equilibrium description, our framework integrates thermodynamic properties­anticipated with an RNA physicochemical model­with a detailed description of the intermolecular interaction. The theoretical calculations are confirmed with an experimental characterization of the action of the riboregulatory device within living cells. This illustrates, more broadly, the predictability of genetic robustness on synthetic systems, and the faculty to engineer gene expression programs from a minimal set of first principles.

Viral Strain-Specific Differential Alterations in Arabidopsis Developmental Patterns.

Turnip mosaic virus (TuMV) infections affect many Arabidopsis developmental traits. This paper analyzes, at different levels, the development-related differential alterations induced by different strains of TuMV, represented by isolates UK 1 and JPN 1. The genomic sequence of JPN 1 TuMV isolate revealed highest divergence in the P1 and P3 viral cistrons, upon comparison with the UK 1 sequence. Infectious viral chimeras covering the whole viral genome uncovered the P3 cistron as a major viral determinant of development alterations, excluding the involvement of the PIPO open reading frame. However, constitutive transgenic expression of P3 in Arabidopsis did not induce developmental alterations nor modulate the strong effects induced by the transgenic RNA silencing suppressor HC-Pro from either strain. This highlights the importance of studying viral determinants within the context of actual viral infections. Transcriptomic and interactomic analyses at different stages of plant development revealed large differences in the number of genes affected by the different infections at medium infection times but no significant differences at very early times. Biological functions affected by UK 1 (the most severe strain) included mainly stress response and transport. Most cellular components affected cell-wall transport or metabolism. Hubs in the interactome were affected upon infection.

RiboMaker: computational design of conformation-based riboregulation.

MOTIVATION: The ability to engineer control systems of gene expression is instrumental for synthetic biology. Thus, bioinformatic methods that assist such engineering are appealing because they can guide the sequence design and prevent costly experimental screening. In particular, RNA is an ideal substrate to de novo design regulators of protein expression by following sequence-to-function models. RESULTS: We have implemented a novel algorithm, RiboMaker, aimed at the computational, automated design of bacterial riboregulation. RiboMaker reads the sequence and structure specifications, which codify for a gene regulatory behaviour, and optimizes the sequences of a small regulatory RNA and a 5'-untranslated region for an efficient intermolecular interaction. To this end, it implements an evolutionary design strategy, where random mutations are selected according to a physicochemical model based on free energies. The resulting sequences can then be tested experimentally, providing a new tool for synthetic biology, and also for investigating the riboregulation principles in natural systems. AVAILABILITY AND IMPLEMENTATION: Web server is available at http://ribomaker.jaramillolab.org/. Source code, instructions and examples are freely available for download at http://sourceforge.net/projects/ribomaker/.