PAQR3 controls autophagy by integrating AMPK signaling to enhance ATG14L‐associated PI3K activity

The Beclin1–VPS34 complex is recognized as a central node in regulating autophagy via interacting with diverse molecules such as ATG14L for autophagy initiation and UVRAG for autophagosome maturation. However, the underlying molecular mechanism that coordinates the timely activation of VPS34 complex is poorly understood. Here, we identify that PAQR3 governs the preferential formation and activation of ATG14L‐linked VPS34 complex for autophagy initiation via two levels of regulation. Firstly, PAQR3 functions as a scaffold protein that facilitates the formation of ATG14L‐ but not UVRAG‐linked VPS34 complex, leading to elevated capacity of PI(3)P generation ahead of starvation signals. Secondly, AMPK phosphorylates PAQR3 at threonine 32 and switches on PI(3)P production to initiate autophagosome formation swiftly after glucose starvation. Deletion of PAQR3 leads to reduction of exercise‐induced autophagy in mice, accompanied by a certain degree of disaggregation of ATG14L‐associated VPS34 complex. Together, this study uncovers that PAQR3 can not only enhance the capacity of pro‐autophagy class III PI3K due to its scaffold function, but also integrate AMPK signal to activation of ATG14L‐linked VPS34 complex upon glucose starvation.     

Identification and Characterization of the Lysine-Rich Matrix Protein Family in <Emphasis Type="Italic">Pinctada fucata</Emphasis>: Indicative of Roles in Shell Formation

Mantle can secret matrix proteins playing key roles in regulating the process of shell formation. The genes encoding lysine-rich matrix proteins (KRMPs) are one of the most highly expressed matrix genes in pearl oysters. However, the expression pattern of KRMPs is limited and the functions of them still remain unknown. In this study, we isolated and identified six new members of lysine-rich matrix proteins, rich in lysine, glycine and tyrosine, and all of them are basic matrix proteins. Combined with four members of the KRMPs previously reported, all these proteins can be divided into three subclasses according to the results of phylogenetic analyses: KRMP1–3 belong to subclass KPI, KRMP4–5 belong to KPII, and KRMP6–10 belong to KPIII. Three subcategories of lysine-rich matrix proteins are highly expressed in the D-phase, the larvae and adult mantle. Lysine-rich matrix proteins are involved in the shell repairing process and associated with the formation of the shell and pearl. What’s more, they can cause abnormal shell growth after RNA interference. In detail, KPI subgroup was critical for the beginning formation of the prismatic layer; both KPII and KPIII subgroups participated in the formation of prismatic layer and nacreous layer. Compared with different temperatures and salinity stimulation treatments, the influence of changes in pH on KRMPs gene expression was the greatest. Recombinant KRMP7 significantly inhibited CaCO₃ precipitation, changed the morphology of calcite, and inhibited the growth of aragonite in vitro. Our results are beneficial to understand the functions of the KRMP genes during shell formation.     

Plastic responses in the metabolome and functional traits of maize plants to temperature variations

Environmentally inducible phenotypic plasticity is a major player in plant responses to climate change. However, metabolic responses and their role in determining the phenotypic plasticity of plants that are subjected to temperature variations remain poorly understood. The metabolomic profiles and metabolite levels in the leaves of three maize inbred lines grown in different temperature conditions were examined with a nuclear magnetic resonance metabolomic technique. The relationship of functional traits to metabolome profiles and the metabolic mechanism underlying temperature variations were then explored. A comparative analysis showed that during heat and cold stress, maize plants shared common plastic responses in biomass accumulation, carbon, nitrogen, sugars, some amino acids and compatible solutes. We also found that the plastic response of maize plants to heat stress was different from that under cold stress, mainly involving biomass allocation, shikimate and its aromatic amino acid derivatives, and other non‐polar metabolites. The plastic responsiveness of functional traits of maize lines to temperature variations was low, while the metabolic responsiveness in plasticity was high, indicating that functional and metabolic plasticity may play different roles in maize plant adaptation to temperature variations. A linear regression analysis revealed that the maize lines could adapt to growth temperature variations through the interrelation of plastic responses in the metabolomes and functional traits, such as biomass allocation and the status of carbon and nitrogen. We provide valuable insight into the plastic response strategy of maize plants to temperature variations that will permit the optimisation of crop cultivation in an increasingly variable environment.