Artificial nanovesicles for dsRNA delivery in spray-induced gene silencing for crop protection.

Spray-induced gene silencing (SIGS) is an innovative and eco-friendly technology where topical application of pathogen gene-targeting RNAs to plant material can enable disease control. SIGS applications remain limited because of the instability of RNA, which can be rapidly degraded when exposed to various environmental conditions. Inspired by the natural mechanism of cross-kingdom RNAi through extracellular vesicle trafficking, we describe herein the use of artificial nanovesicles (AVs) for RNA encapsulation and control against the fungal pathogen, Botrytis cinerea. AVs were synthesized using three different cationic lipid formulations, DOTAP + PEG, DOTAP and DODMA, and examined for their ability to protect and deliver double stranded RNA (dsRNA). All three formulations enabled dsRNA delivery and uptake by B. cinerea. Further, encapsulating dsRNA in AVs provided strong protection from nuclease degradation and from removal by leaf washing. This improved stability led to prolonged RNAi-mediated protection against B. cinerea both on pre- and post-harvest plant material using AVs. Specifically, the AVs extended the protection duration conferred by dsRNA to 10 days on tomato and grape fruits and to 21 days on grape leaves. The results of this work demonstrate how AVs can be used as a new nanocarrier to overcome RNA instability in SIGS for crop protection.

Spray-induced gene silencing for disease control is dependent on the efficiency of pathogen RNA uptake.

Recent discoveries show that fungi can take up environmental RNA, which can then silence fungal genes through environmental RNA interference. This discovery prompted the development of Spray-Induced Gene Silencing (SIGS) for plant disease management. In this study, we aimed to determine the efficacy of SIGS across a variety of eukaryotic microbes. We first examined the efficiency of RNA uptake in multiple pathogenic and non-pathogenic fungi, and an oomycete pathogen. We observed efficient double-stranded RNA (dsRNA) uptake in the fungal plant pathogens Botrytis cinerea, Sclerotinia sclerotiorum, Rhizoctonia solani, Aspergillus niger and Verticillium dahliae, but no uptake in Colletotrichum gloeosporioides, and weak uptake in a beneficial fungus, Trichoderma virens. For the oomycete plant pathogen, Phytophthora infestans, RNA uptake was limited and varied across different cell types and developmental stages. Topical application of dsRNA targeting virulence-related genes in pathogens with high RNA uptake efficiency significantly inhibited plant disease symptoms, whereas the application of dsRNA in pathogens with low RNA uptake efficiency did not suppress infection. Our results have revealed that dsRNA uptake efficiencies vary across eukaryotic microbe species and cell types. The success of SIGS for plant disease management can largely be determined by the pathogen's RNA uptake efficiency.

TurboRVB: A many-body toolkit for ab initio electronic simulations by quantum Monte Carlo.

TurboRVB is a computational package for ab initio Quantum Monte Carlo (QMC) simulations of both molecular and bulk electronic systems. The code implements two types of well established QMC algorithms: Variational Monte Carlo (VMC) and diffusion Monte Carlo in its robust and efficient lattice regularized variant. A key feature of the code is the possibility of using strongly correlated many-body wave functions (WFs), capable of describing several materials with very high accuracy, even when standard mean-field approaches [e.g., density functional theory (DFT)] fail. The electronic WF is obtained by applying a Jastrow factor, which takes into account dynamical correlations, to the most general mean-field ground state, written either as an antisymmetrized geminal power with spin-singlet pairing or as a Pfaffian, including both singlet and triplet correlations. This WF can be viewed as an efficient implementation of the so-called resonating valence bond (RVB) Ansatz, first proposed by Pauling and Anderson in quantum chemistry [L. Pauling, The Nature of the Chemical Bond (Cornell University Press, 1960)] and condensed matter physics [P.W. Anderson, Mat. Res. Bull 8, 153 (1973)], respectively. The RVB Ansatz implemented in TurboRVB has a large variational freedom, including the Jastrow correlated Slater determinant as its simplest, but nontrivial case. Moreover, it has the remarkable advantage of remaining with an affordable computational cost, proportional to the one spent for the evaluation of a single Slater determinant. Therefore, its application to large systems is computationally feasible. The WF is expanded in a localized basis set. Several basis set functions are implemented, such as Gaussian, Slater, and mixed types, with no restriction on the choice of their contraction. The code implements the adjoint algorithmic differentiation that enables a very efficient evaluation of energy derivatives, comprising the ionic forces. Thus, one can perform structural optimizations and molecular dynamics in the canonical NVT ensemble at the VMC level. For the electronic part, a full WF optimization (Jastrow and antisymmetric parts together) is made possible, thanks to state-of-the-art stochastic algorithms for energy minimization. In the optimization procedure, the first guess can be obtained at the mean-field level by a built-in DFT driver. The code has been efficiently parallelized by using a hybrid MPI-OpenMP protocol, which is also an ideal environment for exploiting the computational power of modern Graphics Processing Unit accelerators.

Biotechnological Approaches: Gene Overexpression, Gene Silencing, and Genome Editing to Control Fungal and Oomycete Diseases in Grapevine.

Downy mildew, powdery mildew, and grey mold are some of the phytopathological diseases causing economic losses in agricultural crops, including grapevine, worldwide. In the current scenario of increasing global warming, in which the massive use of agrochemicals should be limited, the management of fungal disease has become a challenge. The knowledge acquired on candidate resistant (R) genes having an active role in plant defense mechanisms has allowed numerous breeding programs to integrate these traits into selected cultivars, even though with some limits in the conservation of the proper qualitative characteristics of the original clones. Given their gene-specific mode of action, biotechnological techniques come to the aid of breeders, allowing them to generate simple and fast modifications in the host, without introducing other undesired genes. The availability of efficient gene transfer procedures in grapevine genotypes provide valid tools that support the application of new breeding techniques (NBTs). The expertise built up over the years has allowed the optimization of these techniques to overexpress genes that directly or indirectly limit fungal and oomycetes pathogens growth or silence plant susceptibility genes. Furthermore, the downregulation of pathogen genes which act as virulence effectors by exploiting the RNA interference mechanism, represents another biotechnological tool that increases plant defense. In this review, we summarize the most recent biotechnological strategies optimized and applied on Vitis species, aimed at reducing their susceptibility to the most harmful fungal and oomycetes diseases. The best strategy for combating pathogenic organisms is to exploit a holistic approach that fully integrates all these available tools.

Advanced characterization-informed machine learning framework and quantitative insight to irradiated annular U-10Zr metallic fuels.

U-10Zr Metal fuel is a promising nuclear fuel candidate for next-generation sodium-cooled fast spectrum reactors. Since the Experimental Breeder Reactor-II in the late 1960s, researchers accumulated a considerable amount of experience and knowledge on fuel performance at the engineering scale. However, a mechanistic understanding of fuel microstructure evolution and property degradation during in-reactor irradiation is still missing due to a lack of appropriate tools for rapid fuel microstructure assessment and property prediction based on post irradiation examination. This paper proposed a machine learning enabled workflow, coupled with domain knowledge and large dataset collected from advanced post-irradiation examination microscopies, to provide rapid and quantified assessments of the microstructure in two reactor irradiated prototypical annular metal fuels. Specifically, this paper revealed the distribution of Zr-bearing secondary phases and constitutional redistribution across different radial locations. Additionally, the ratios of seven different microstructures at various locations along the temperature gradient were quantified. Moreover, the distributions of fission gas pores on two types of U-10Zr annular fuels were quantitatively compared.

Artificial nanovesicles for dsRNA delivery in spray induced gene silencing for crop protection.

Spray-Induced Gene Silencing (SIGS) is an innovative and eco-friendly technology where topical application of pathogen gene-targeting RNAs to plant material can enable disease control. SIGS applications remain limited because of the instability of dsRNA, which can be rapidly degraded when exposed to various environmental conditions. Inspired by the natural mechanism of cross-kingdom RNAi through extracellular vesicle trafficking, we describe herein the use of artificial nanovesicles (AVs) for dsRNA encapsulation and control against the fungal pathogen, Botrytis cinerea. AVs were synthesized using three different cationic lipid formulations, DOTAP + PEG, DOTAP, and DODMA, and examined for their ability to protect and deliver dsRNA. All three formulations enabled dsRNA delivery and uptake by B. cinerea. Further, encapsulating dsRNA in AVs provided strong protection from nuclease degradation and from removal by leaf washing. This improved stability led to prolonged RNAi-mediated protection against B. cinerea both on pre- and post-harvest plant material using AVs. Specifically, the AVs extended the protection duration conferred by dsRNA to 10 days on tomato and grape fruits and to 21 days on grape leaves. The results of this work demonstrate how AVs can be used as a new nanocarrier to overcome dsRNA instability in SIGS for crop protection.

Efficient protocol of de novo shoot organogenesis from somatic embryos for grapevine genetic transformation.

Plant genetic transformation is a powerful tool that can facilitate breeding programs for disease tolerance, abiotic stress, fruit production, and quality by preserving the characteristics of fruit tree elite genotypes. However, most grapevine cultivars worldwide are considered recalcitrant, and most available genetic transformation protocols involve regeneration by somatic embryogenesis, which often requires the continuous production of new embryogenic calli. Cotyledons and hypocotyls derived from flower-induced somatic embryos of the Vitis vinifera cultivars Ancellotta and Lambrusco Salamino, in comparison with the model cultivar Thompson Seedless, are here validated for the first time as starting explants for in vitro regeneration and transformation trials. Explants were cultured on two different MS-based culture media, one having a combination of 4.4 µM BAP and 0.49 µM IBA (M1), and the other only supplemented with 13.2 µM BAP (M2). The competence to regenerate adventitious shoots was higher in cotyledons than in hypocotyls on both M1 and M2. M2 medium increased significantly the average number of shoots only in Thompson Seedless somatic embryo-derived explants. This efficient regeneration strategy, that proposes a combination of somatic embryogenesis and organogenesis, has been successfully exploited in genetic engineering experiments. Ancellotta and Lambrusco Salamino cotyledons and hypocotyls produced the highest number of calli expressing eGFP when cultured on M2 medium, while for Thompson Seedless both media tested were highly efficient. The regeneration of independent transgenic lines of Thompson Seedless was observed from cotyledons cultured on both M1 and M2 with a transformation efficiency of 12 and 14%, respectively, and from hypocotyls on M1 and M2 with a transformation efficiency of 6 and 12%, respectively. A single eGFP fluorescent adventitious shoot derived from cotyledons cultured on M2 was obtained for Ancellotta, while Lambrusco Salamino showed no regeneration of transformed shoots. In a second set of experiments, using Thompson Seedless as the model cultivar, we observed that the highest number of transformed shoots was obtained from cotyledons explants, followed by hypocotyls and meristematic bulk slices, confirming the high regeneration/transformation competences of somatic embryo-derived cotyledons. The independent transformed shoots obtained from the cultivars Thompson Seedless and Ancellotta were successfully acclimatized in the greenhouse and showed a true-to-type phenotype. The novel in vitro regeneration and genetic transformation protocols optimized in this study will be useful for the application of new and emerging modern biotechnologies also to other recalcitrant grapevine genotypes.

An efficient instance segmentation approach for studying fission gas bubbles in irradiated metallic nuclear fuel.

Gaseous fission products from nuclear fission reactions tend to form fission gas bubbles of various shapes and sizes inside nuclear fuel. The behavior of fission gas bubbles dictates nuclear fuel performances, such as fission gas release, grain growth, swelling, and fuel cladding mechanical interaction. Although mechanical understanding of the overall evolution behavior of fission gas bubbles is well known, lacking the quantitative data and high-level correlation between burnup/temperature and microstructure evolution blocks the development of predictive models and reduces the possibility of accelerating the qualification for new fuel forms. Historical characterization of fission gas bubbles in irradiated nuclear fuel relied on a simple threshold method working on low-resolution optical microscopy images. Advanced characterization of fission gas bubbles using scanning electron microscopic images reveals unprecedented details and extensive morphological data, which strains the effectiveness of conventional methods. This paper proposes a hybrid framework, based on digital image processing and deep learning models, to efficiently detect and classify fission gas bubbles from scanning electron microscopic images. The developed bubble annotation tool used a multitask deep learning network that integrates U-Net and ResNet to accomplish instance-level bubble segmentation. With limited annotated data, the model achieves a recall ratio of more than 90%, a leap forward compared to the threshold method. The model has the capability to identify fission gas bubbles with and without lanthanides to better understand the movement of lanthanide fission products and fuel cladding chemical interaction. Lastly, the deep learning model is versatile and applicable to the micro-structure segmentation of similar materials.

A fine pore-preserved deep neural network for porosity analytics of a high burnup U-10Zr metallic fuel.

U-10 wt.% Zr (U-10Zr) metallic fuel is the leading candidate for next-generation sodium-cooled fast reactors. Porosity is one of the most important factors that impacts the performance of U-10Zr metallic fuel. The pores generated by the fission gas accumulation can lead to changes in thermal conductivity, fuel swelling, Fuel-Cladding Chemical Interaction (FCCI) and Fuel-Cladding Mechanical Interaction (FCMI). Therefore, it is crucial to accurately segment and analyze porosity to understand the U-10Zr fuel system to design future fast reactors. To address the above issues, we introduce a workflow to process and analyze multi-source Scanning Electron Microscope (SEM) image data. Moreover, an encoder-decoder-based, deep fully convolutional network is proposed to segment pores accurately by integrating the residual unit and the densely-connected units. Two SEM 250 × field of view image datasets with different formats are utilized to evaluate the new proposed model's performance. Sufficient comparison results demonstrate that our method quantitatively outperforms two popular deep fully convolutional networks. Furthermore, we conducted experiments on the third SEM 2500 × field of view image dataset, and the transfer learning results show the potential capability to transfer the knowledge from low-magnification images to high-magnification images. Finally, we use a pre-trained network to predict the pores of SEM images in the whole cross-sectional image and obtain quantitative porosity analysis. Our findings will guide the SEM microscopy data collection efficiently, provide a mechanistic understanding of the U-10Zr fuel system and bridge the gap between advanced characterization to fuel system design.

RNA Interference Strategies for Future Management of Plant Pathogenic Fungi: Prospects and Challenges.

Plant pathogenic fungi are the largest group of disease-causing agents on crop plants and represent a persistent and significant threat to agriculture worldwide. Conventional approaches based on the use of pesticides raise social concern for the impact on the environment and human health and alternative control methods are urgently needed. The rapid improvement and extensive implementation of RNA interference (RNAi) technology for various model and non-model organisms has provided the initial framework to adapt this post-transcriptional gene silencing technology for the management of fungal pathogens. Recent studies showed that the exogenous application of double-stranded RNA (dsRNA) molecules on plants targeting fungal growth and virulence-related genes provided disease attenuation of pathogens like Botrytis cinerea, Sclerotinia sclerotiorum and Fusarium graminearum in different hosts. Such results highlight that the exogenous RNAi holds great potential for RNAi-mediated plant pathogenic fungal disease control. Production of dsRNA can be possible by using either in-vitro or in-vivo synthesis. In this review, we describe exogenous RNAi involved in plant pathogenic fungi and discuss dsRNA production, formulation, and RNAi delivery methods. Potential challenges that are faced while developing a RNAi strategy for fungal pathogens, such as off-target and epigenetic effects, with their possible solutions are also discussed.

Double-Stranded RNA Targeting Dicer-Like Genes Compromises the Pathogenicity of Plasmopara viticola on Grapevine.

Downy mildew caused by Plasmopara viticola is one of the most devastating diseases of grapevine, attacking all green parts of the plant. The damage is severe when the infection at flowering stage is left uncontrolled. P. viticola management consumes a significant amount of classical pesticides applied in vineyards, requiring efficient and environmentally safe disease management options. Spray-induced gene silencing (SIGS), through the application of exogenous double-stranded RNA (dsRNA), has shown promising results for the management of diseases in crops. Here, we developed and tested the potential of dsRNA targeting P. viticola Dicer-like (DCL) genes for SIGS-based crop protection strategy. The exogenous application of PvDCL1/2 dsRNA, a chimera of PvDCL1 and PvDCL2, highly affected the virulence of P. viticola. The reduced expression level of PvDCL1 and PvDCL2 transcripts in infected leaves, treated with PvDCL1/2 dsRNA, was an indication of an active RNA interference mechanism inside the pathogen to compromise its virulence. Besides the protective property, the PvDCL1/2 dsRNA also exhibited a curative role by reducing the disease progress rate of already established infection. Our data provide a promising future for PvDCL1/2 dsRNA as a new generation of RNA-based resistant plants or RNA-based agrochemical for the management of downy mildew disease in grapevine.

Algorithmic differentiation and the calculation of forces by quantum Monte Carlo.

We describe an efficient algorithm to compute forces in quantum Monte Carlo using adjoint algorithmic differentiation. This allows us to apply the space warp coordinate transformation in differential form, and compute all the 3M force components of a system with M atoms with a computational effort comparable with the one to obtain the total energy. Few examples illustrating the method for an electronic system containing several water molecules are presented. With the present technique, the calculation of finite-temperature thermodynamic properties of materials with quantum Monte Carlo will be feasible in the near future.

Adventitious Shoot Regeneration from In Vitro Leaf Explants of the Peach Rootstock Hansen 536.

In the present study, an efficient system for the in vitro regeneration of adventitious shoots from the peach rootstock Hansen 536 leaves has been established. Twenty regeneration media containing McCown Woody Plant Medium (WPM) as a basal salt supplemented with different concentrations and combinations of plant growth regulators (PGRs) were tested. Expanded leaves along with their petiole from 3-week-old elongated in vitro shoot cultures were used as starting explants. The highest regeneration rate (up to 53%) was obtained on WPM basal medium enriched with 15.5 µM N6-benzylaminopurine (BAP). The influences on leaf regeneration of the ethylene inhibitor silver thiosulphate (STS) and of different combinations of antibiotics added to the optimized regeneration medium were also investigated. The use of 10 µM STS or carbenicillin (238 µM) combined with cefotaxime (210 µM) significantly increased the average number of regenerating shoots per leaf compared to the control. In vitro shoots were finally elongated, rooted and successfully acclimatized in the greenhouse. The results achieved in this study advances the knowledge on factors affecting leaf organogenesis in Prunus spp., and the regeneration protocol described looks promising for the optimization of new genetic transformation procedures in Hansen 536 and other peach rootstocks and cultivars.

Factors Affecting the Regeneration, via Organogenesis, and the Selection of Transgenic Calli in the Peach Rootstock Hansen 536 (Prunus persica × Prunus amygdalus) to Express an RNAi Construct against PPV Virus.

Prunus spp. is one of the most recalcitrant fruit tree species in terms of in vitro regeneration and transformation, mostly when mature tissues are used as explants. The present study describes the in vitro regeneration via indirect organogenesis, and Agrobacterium tumefaciens-mediated transformation of the peach rootstock Hansen 536 (Prunus persica × Prunus amygdalus) through the use of meristematic bulks (MBs) as starting explants. Efficient adventitious shoot regeneration was obtained when Hansen 536 MBs were cultured on an optimized medium consisting of modified McCown Woody Plant medium (WPM) enriched with 4.4 M 6-Benzyladenine (BA), 0.1 M 1-Naphthaleneacetic acid (NAA) and 6.0 g L-1 plant agar S1000 (B&V). MB slices were used later as starting explants for Agrobacterium-mediated transformation to introduce an RNAi construct "ihp35S-PPV194" against PPV virus. Transgenic events were identified by both green fluorescent protein (GFP) screening and kanamycin selection at different concentrations (0, 17 or 42 M). GFP-fluorescent proliferating callus lines were selected and confirmed to stably express the ihp35S-PPV194::eGFP gene construct by molecular analysis. Although shoot regeneration from these transgenic calli has not been obtained yet, this represents one of the few examples of successful attempts in peach genetic transformation from somatic tissues, and also serves as a useful in vitro system for future gene functional analysis in peach.

Dissipation-driven phase transition in two-dimensional Josephson arrays.

We analyze the interplay of dissipative and quantum effects in the proximity of a quantum phase transition. The prototypical system is a resistively shunted two-dimensional Josephson junction array, studied by means of an advanced Fourier path-integral Monte Carlo algorithm. The reentrant superconducting-to-normal phase transition driven by quantum fluctuations, recently discovered in the limit of infinite shunt resistance, persists for moderate dissipation strength but disappears in the limit of small resistance. For large quantum coupling our numerical results show that, beyond a critical dissipation strength, the superconducting phase is always stabilized at sufficiently low temperature. Our phase diagram explains recent experimental findings.

Low-temperature broken-symmetry phases of spiral antiferromagnets.

We study Heisenberg antiferromagnets with nearest- (J1) and third- (J3) neighbor exchange on the square lattice. In the limit of spin S-->infinity, there is a zero temperature (T) Lifshitz point at J(3)=1/4J(1), with long-range spiral spin order at T=0 for J3>1/4J(1). We present classical Monte Carlo simulations and a theory for T>0 crossovers near the Lifshitz point: spin rotation symmetry is restored at any T>0, but there is a broken lattice reflection symmetry for 0< or =T

Spin-liquid versus dimerized ground states in a frustrated Heisenberg antiferromagnet.

We present a density matrix renormalization group study of the ground-state properties of spin-1/2 frustrated J1-J3 Heisenberg n(l)-leg ladders (with n(l) up to 8). For strong frustration (J(3)/J(1) approximately 0.5), both even-leg and odd-leg ladders display a finite gap to spin excitations, which we argue remains finite in the two-dimensional limit. In this regime, on odd-leg ladders the ground state is spontaneously dimerized, in agreement with the Lieb-Schultz-Mattis prediction, while on even-leg ladders the dimer correlations decay exponentially. The magnitude of the dimer order parameter decreases as the number of legs increases, consistent with a two-dimensional spin-liquid ground state.

Ising transition in the two-dimensional quantum J1-J2 Heisenberg model.

We study the thermodynamics of the spin-S two-dimensional quantum Heisenberg antiferromagnet on the square lattice with nearest (J1) and next-nearest (J2) neighbor couplings in its collinear phase (J(2)/J(1)>0.5), using the pure-quantum self-consistent harmonic approximation. Our results show the persistence of a finite-temperature Ising phase transition for every value of the spin, provided that the ratio J(2)/J(1) is greater than a critical value corresponding to the onset of collinear long-range order at zero temperature. We also calculate the spin and temperature dependence of the collinear susceptibility and correlation length, and we discuss our results in light of the experiments on Li2VOSiO4 and related compounds.

Chiral spin liquid wave function and the Lieb-Schultz-Mattis theorem.

We study a chiral spin liquid wave function defined as a Gutzwiller projected BCS state with a complex pairing function. After projection, spontaneous dimerization is found for any odd but finite number of chains, thus satisfying the Lieb-Schultz-Mattis theorem, whereas for an even number of chains there is no dimerization. The two-dimensional thermodynamic limit is consistently reached for a large number of chains since the dimer order parameter vanishes in this limit. This property clearly supports the possibility of a spin liquid ground state in two dimensions with a gap to all physical excitations and with no broken translation symmetry.

Reentrant behavior of the phase stiffness in Josephson junction arrays.

The phase diagram of a 2D Josephson junction array with large substrate resistance, described by a quantum XY model, is studied by means of Fourier path-integral Monte Carlo. A genuine Berezinskii-Kosterlitz-Thouless transition is found up to a threshold value g( small star, filled ) of the quantum coupling, beyond which no phase coherence is established. Slightly below g( small star, filled ) the phase stiffness shows a reentrant behavior with temperature, in connection with a low-temperature disappearance of the superconducting phase, driven by strong nonlinear quantum fluctuations.