Arabidopsis heterotrimeric G-protein regulates cell wall defense and resistance to necrotrophic fungi

The Arabidopsis heterotrimeric G-protein controls defense responses to necrotrophic and vascular fungi. The agb1 mutant impaired in the Gβ subunit displays enhanced susceptibility to these pathogens. Gβ/AGB1 forms an obligate dimer with either one of the Arabidopsis Gγ subunits (γ1/AGG1 and γ2/AGG2). Accordingly, we now demonstrate that the agg1 agg2 double mutant is as susceptible as agb1 plants to the necrotrophic fungus Plectosphaerella cucumerina. To elucidate the molecular basis of heterotrimeric G-protein-mediated resistance, we performed a comparative transcriptomic analysis of agb1-1 mutant and wild-type plants upon inoculation with P. cucumerina. This analysis, together with metabolomic studies, demonstrated that G-protein-mediated resistance was independent of defensive pathways required for resistance to necrotrophic fungi, such as the salicylic acid, jasmonic acid, ethylene, abscisic acid, and tryptophan-derived metabolites signaling, as these pathways were not impaired in agb1 and agg1 agg2 mutants. Notably, many mis-regulated genes in agb1 plants were related with cell wall functions, which was also the case in agg1 agg2 mutant. Biochemical analyses and Fourier Transform InfraRed (FTIR) spectroscopy of cell walls from G-protein mutants revealed that the xylose content was lower in agb1 and agg1 agg2 mutants than in wild-type plants, and that mutant walls had similar FTIR spectratypes, which differed from that of wild-type plants. The data presented here suggest a canonical functionality of the Gβ and Gγ1/γ2 subunits in the control of Arabidopsis immune responses and the regulation of cell wall composition.

A matrix pencil approach to the existence of compactly supported reconstruction functions in average sampling

The aim of this work is to solve a question raised for average sampling in shift-invariant spaces by using the well-known matrix pencil theory. In many common situations in sampling theory, the available data are samples of some convolution operator acting on the function itself: this leads to the problem of average sampling, also known as generalized sampling. In this paper we deal with the existence of a sampling formula involving these samples and having reconstruction functions with compact support. Thus, low computational complexity is involved and truncation errors are avoided. In practice, it is accomplished by means of a FIR filter bank. An answer is given in the light of the generalized sampling theory by using the oversampling technique: more samples than strictly necessary are used. The original problem reduces to finding a polynomial left inverse of a polynomial matrix intimately related to the sampling problem which, for a suitable choice of the sampling period, becomes a matrix pencil. This matrix pencil approach allows us to obtain a practical method for computing the compactly supported reconstruction functions for the important case where the oversampling rate is minimum. Moreover, the optimality of the obtained solution is established.

Cryptographic properties of Boolean functions defining elementary cellular automata

In this work, the algebraic properties of the local transition functions of elementary cellular automata (ECA) were analysed. Specifically, a classification of such cellular automata was done according to their algebraic degree, the balancedness, the resiliency, nonlinearity, the propagation criterion and the existence of non-zero linear structures. It is shown that there is not any ECA satisfying all properties at the same time.

Dissecting Arabidopsis Gß signal transduction on the protein surface.

The heterotrimeric G-protein complex provides signal amplification and target specificity. The Arabidopsis (Arabidopsis thaliana) G?-subunit of this complex (AGB1) interacts with and modulates the activity of target cytoplasmic proteins. This specificity resides in the structure of the interface between AGB1 and its targets. Important surface residues of AGB1, which were deduced from a comparative evolutionary approach, were mutated to dissect AGB1-dependent physiological functions. Analysis of the capacity of these mutants to complement well-established phenotypes of G?-null mutants revealed AGB1 residues critical for specific AGB1-mediated biological processes, including growth architecture, pathogen resistance, stomata-mediated leaf-air gas exchange, and possibly photosynthesis. These findings provide promising new avenues to direct the finely tuned engineering of crop yield and traits.

Characterization of tomato Cycling Dof Factors reveals conserved and new functions in the control of flowering time and abiotic stress responses.

DNA binding with One Finger (DOF) transcription factors are involved in multiple aspects of plant growth and development but their precise roles in abiotic stress tolerance are largely unknown. Here we report a group of five tomato DOF genes, homologous to Arabidopsis Cycling DOF Factors (CDFs), that function as transcriptional regulators involved in responses to drought and salt stress and flowering-time control in a gene-specific manner. SlCDF1?5 are nuclear proteins that display specific binding with different affinities to canonical DNA target sequences and present diverse transcriptional activation capacities in vivo. SlCDF1?5 genes exhibited distinct diurnal expression patterns and were differentially induced in response to osmotic, salt, heat, and low-temperature stresses. Arabidopsis plants overexpressing SlCDF1 or SlCDF3 showed increased drought and salt tolerance. In addition, the expression of various stress-responsive genes, such as COR15, RD29A, and RD10, were differentially activated in the overexpressing lines. Interestingly, overexpression in Arabidopsis of SlCDF3 but not SlCDF1 promotes late flowering through modulation of the expression of flowering control genes such as CO and FT. Overall, our data connect SlCDFs to undescribed functions related to abiotic stress tolerance and flowering time through the regulation of specific target genes and an increase in particular metabolites

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand- avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.

UAS See-and-Avoid Strategy using a Fuzzy Logic Controller Optimized by Cross-Entropy in Scaling Factors and Membership Functions.

This work aims to develop a novel Cross-Entropy (CE) optimization-based fuzzy controller for Unmanned Aerial Monocular Vision-IMU System (UAMVIS) to solve the seeand-avoid problem using its accurate autonomous localization information. The function of this fuzzy controller is regulating the heading of this system to avoid the obstacle, e.g. wall. In the Matlab Simulink-based training stages, the Scaling Factor (SF) is adjusted according to the specified task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the collison avoidance performance. After obtained the optimal SF and MF, 64% of rules has been reduced (from 125 rules to 45 rules), and a large number of real flight tests with a quadcopter have been done. The experimental results show that this approach precisely navigates the system to avoid the obstacle. To our best knowledge, this is the first work to present the optimized fuzzy controller for UAMVIS using Cross-Entropy method in Scaling Factors and Membership Functions optimization.