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a b s t r a c tHerbivore outbreaks, a major form of natural disturbance in many ecosystems, often have devastating impacts on their food plants. Understanding those factors permitting herbivore outbreaks to occur is a long-standing issue in conventional studies of plant-herbivore interactions. These studies are largely concerned with the relative importance of intrinsic biological factors and extrinsic environmental variations in determining the degree of herbivore outbreaks. In this paper, we illustrated that how the time delay associated with plant defense responses to herbivore attacks and the spatial diffusion of herbivore jointly promote outbreaks of herbivore population. Using a reaction-diffusion model, we showed that there exists a threshold of time delay in plant-herbivore interactions; when time delay is below the threshold value, there is no herbivore outbreak. However, when time delay is above the threshold value, periodic outbreak of herbivore emerges. Furthermore, the results confirm that during the outbreak period, plants display much lower density than its normal level but higher in the inter-outbreak periods. Our results are supported by empirical findings.Crown

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SummaryPlant adaptation in variable soil nitrate concentrations involves sophisticated signaling and transport systems that modulate a variety of physiological and developmental responses. However, we know very little about their molecular mechanisms. It has recently been reported that many of these responses are regulated by a transceptor NRT1.1, a transporter cum receptor of nitrate signaling. NRT1.1 displays dual-affinity modes of nitrate binding and establishes phosphorylated/non-phosphorylated states at the amino acid residue threonine 101 in response to fluctuating nitrate concentrations. Here we report that intrinsic structural asymmetries between the protomers of the homodimer NRT1.1 provide a functional basis for having dual-affinity modes of nitrate binding and play a pivotal role for the phosphorylation switch. Nitrate-triggered local conformational changes facilitate allosteric communications between the nitrate binding and the phosphorylation site in one protomer, but such communications are impeded in the other. Structural analysis therefore suggests the functional relevance of NRT1.1 interprotomer asymmetries.

The entry of the SARS-CoV-2, a causative agent of COVID-19, into human host cells is mediated by the SARS-CoV-2 spike (S) glycoprotein, which critically depends on the formation of complexes involving the spike protein receptor-binding domain (RBD) and the human cellular membrane receptor angiotensin-converting enzyme 2 (hACE2). Using classical site density functional theory (SDFT) and structural bioinformatics methods, we investigate binding and conformational properties of these complexes and study the overlooked role of water-mediated interactions. Analysis of the three-dimensional reference interaction site model (3DRISM) of SDFT indicates that water mediated interactions in the form of additional water bridges strongly increases the binding between SARS-CoV-2 spike protein and hACE2 compared to SARS-CoV-1-hACE2 complex. By analyzing structures of SARS-CoV-2 and SARS-CoV-1, we find that the homotrimer SARS-CoV-2 S receptor-binding domain (RBD) has expanded in size, indicating large conformational change relative to SARS-CoV-1 S protein. Protomer with the up-conformational form of RBD, which binds with hACE2, exhibits stronger intermolecular interactions at the RBD-ACE2 interface, with differential distributions and the inclusion of specific H-bonds in the CoV-2 complex. Further interface analysis has shown that interfacial water promotes and stabilizes the formation of CoV-2/hACE2 complex. This interaction causes a significant structural rigidification of the spike protein, favoring proteolytic processing of the S protein for the fusion of the viral and cellular membrane. Moreover, conformational dynamics simulations of RBD motions in SARS-CoV-2 and SARS-CoV-1 point to the role in modification of the RBD dynamics and their impact on infectivity.

Bertalanffy proposed the differential equation m´(t) = p × m (t) a-q × m (t) for the description of the mass growth of animals as a function m(t) of time t. He suggested that the solution using the metabolic scaling exponent a = 2/3 (von Bertalanffy growth function VBGF) would be universal for vertebrates. Several authors questioned universality, as for certain species other models would provide a better fit. This paper reconsiders this question. Using the Akaike information criterion it proposes a testable definition of 'weak universality' for a taxonomic group of species. (It roughly means that a model has an acceptable fit to most data sets of that group.) This definition was applied to 60 data sets from literature (37 about fish and 23 about non-fish species) and for each dataset an optimal metabolic scaling exponent 0 ≤ a opt < 1 was identified, where the model function m(t) achieved the best fit to the data. Although in general this optimal exponent differed widely from a = 2/3 of the VBGF, the VBGF was weakly universal for fish, but not for non-fish. This observation supported the conjecture that the pattern of growth for fish may be distinct. The paper discusses this conjecture. PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.3303v1 | CC BY 4.0 Open Access | rec Abstract. Bertalanffy proposed the differential equation m´(t) = pm(t) a-qm(t) for the description of the mass growth 10 of animals as a function m(t) of time t. He suggested that the solution using the metabolic scaling exponent a = 2/3 11 (von Bertalanffy growth function VBGF) would be universal for vertebrates. Several authors questioned universality, 12 as for certain species other models would provide a better fit. This paper reconsiders this question. Using the Akaike 13 information criterion it proposes a testable definition of 'weak universality' for a taxonomic group of species. (It 14 roughly means that a model has an acceptable fit to most data sets of that group.) This definition was applied to 60 15 data sets from literature (37 about fish and 23 about non-fish species) and for each dataset an optimal metabolic scaling 16 exponent 0 ≤ a opt < 1 was identified, where the model function m(t) achieved the best fit to the data. Although in 17 general this optimal exponent differed widely from a = 2/3 of the VBGF, the VBGF was weakly universal for fish, 18 but not for non-fish. This observation supported the conjecture that the pattern of growth for fish may be distinct. The 19 paper discusses this conjecture. 20 Keywords: Akaike's information criteria (AIC), multi-model inference, von Bertalanffy growth function (VBGF), 21 metabolic scaling exponent, weak universality 22 1. Introduction 23 Growth models: Size at age is a key metric of productivity for any animal population (MacNeil 24 et al., 2017) and since Verhulst' (1838) seminal work about the logistic function a wide range of 25 growth models to describe the size of animals as a function of time has been developed. Amongst 26 applications are improved otolith analysis fo...

Defective nitrate signaling in plants causes disorder in nitrogen metabolism, and it negatively affects nitrate transport systems, which toggle between high-and low-affinity modes in variable soil nitrate conditions. Recent discovery of a plasma membrane nitrate transceptor protein NRT1.1-a transporter cum sensor-provides a clue on this toggling mechanism. However, the general mechanistic description still remains poorly understood. Here, we illustrate adaptive responses and regulation of NRT1.1-mediated nitrate signaling in a wide range of extracellular nitrate concentrations. The results show that the homodimeric structure of NRT1.1 and its dimeric switch play an important role in eliciting specific cytosolic calcium waves sensed by the calcineurin-B-like calcium sensor CBL9, which activates the kinase CIPK23, in low nitrate concentration that is, however, impeded in high nitrate concentration. Nitrate binding at the high-affinity unit initiates NRT1.1 dimer decoupling and priming of the Thr101 site for phosphorylation by CIPK23. This phosphorylation stabilizes the NRT1.1 monomeric state, acting as a high-affinity nitrate transceptor. However, nitrate binding in both monomers, retaining the unmodified NRT1.1 state through dimerization, attenuates CIPK23 activity and thereby maintains the low-affinity mode of nitrate signaling and transport. This phosphorylation-led modulation of NRT1.1 activity shows bistable behavior controlled by an incoherent feedforward loop, which integrates nitrate-induced positive and negative regulatory effects on CIPK23. These results, therefore, advance our molecular understanding of adaptation in fluctuating nutrient availability and are a way forward for improving plant nitrogen use efficiency.

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