Alanine-, serine-, cysteine-preferring transporter 2 (ASCT2, SLC1A5) is responsible for the uptake of glutamine into cells, a major source of cellular energy and a key regulator of mammalian target ...of rapamycin (mTOR) activation. Furthermore, ASCT2 expression has been reported in several human cancers, making it a potential target for both diagnostic and therapeutic purposes. Here we identify ASCT2 as a membrane-trafficked cargo molecule, sorted through a direct interaction with the PDZ domain of sorting nexin 27 (SNX27). Using both membrane fractionation and subcellular localization approaches, we demonstrate that the majority of ASCT2 resides at the plasma membrane. This is significantly reduced within CrispR-mediated SNX27 knockout (KO) cell lines, as it is missorted into the lysosomal degradation pathway. The reduction of ASCT2 levels in SNX27 KO cells leads to decreased glutamine uptake, which, in turn, inhibits cellular proliferation. SNX27 KO cells also present impaired activation of the mTOR complex 1 (mTORC1) pathway and enhanced autophagy. Taken together, our data reveal a role for SNX27 in glutamine uptake and amino acid–stimulated mTORC1 activation via modulation of ASCT2 intracellular trafficking.
Waste threatens human health and the environment. Public participation, as an essential link in the whole waste management chain, is important for countries to achieve carbon neutrality and promote ...sustainable development. However, some countries are still in the initial stage of policy practice, for example, China's waste sorting policy is still in the pilot stage and has not yet covered the whole country. Therefore, it is necessary to understand whether waste sorting policy has a catalytic effect on public waste sorting behavior, and based on the Theory of Planned Behavior, knowledge and intention were proposed to have chain-mediating effect. With a large-sample national survey, we compared the differences in public waste sorting behavior between areas with and without waste sorting policies and examined the mechanism. Results showed that the public in areas with waste sorting policies participated more in actual waste sorting behavior than the public in areas without waste sorting policies, and the proposed effects of knowledge and intention were verified. The research results provide valuable insights for policymakers and stakeholders from multiple perspectives of policy implementation, policy instruments, and population differences.
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•Waste sorting policy implementation increases public waste sorting behaviors in China.•Knowledge and intention serially mediate the positive effect of policy implementation.•A large-scale national survey was conducted with cross-regional comparison.
Protein trafficking requires coat complexes that couple recognition of sorting motifs in transmembrane cargoes with biogenesis of transport carriers. The mechanisms of cargo transport through the ...endosomal network are poorly understood. Here, we identify a sorting motif for endosomal recycling of cargoes, including the cation-independent mannose-6-phosphate receptor and semaphorin 4C, by the membrane tubulating BAR domain-containing sorting nexins SNX5 and SNX6. Crystal structures establish that this motif folds into a β-hairpin, which binds a site in the SNX5/SNX6 phox homology domains. Over sixty cargoes share this motif and require SNX5/SNX6 for their recycling. These include cargoes involved in neuronal migration and a Drosophila snx6 mutant displays defects in axonal guidance. These studies identify a sorting motif and provide molecular insight into an evolutionary conserved coat complex, the 'Endosomal SNX-BAR sorting complex for promoting exit 1' (ESCPE-1), which couples sorting motif recognition to the BAR-domain-mediated biogenesis of cargo-enriched tubulo-vesicular transport carriers.
•Personal moral norms, waste sorting knowledge and incentive measures have been considered.•Personal moral norms and waste sorting knowledge positively affect waste sorting intention.•Incentive ...measures narrow the gap between waste sorting intention and behavior.
Waste sorting is essential to address the current predicament of waste management. Though it is important, insufficient attention has been paid to explore residents’ waste sorting intention and behavior and understand its formation process. To narrow the research gap, this research built a theoretical research model by adding personal moral norms and waste sorting knowledge into the theory of planned behavior to explicate residents’ waste sorting intention and behavior formation process. Meanwhile, given the discrepancy between waste sorting intention and actual behavior, this research also explored the effect of external conditions, such as incentive measures, on this discrepancy. Based on survey data from 397 Chinese residents, this research found that attitudes, subjective norms, perceived behavioral control, personal moral norms and waste sorting knowledge were directly and significantly related to residents’ waste sorting intention. Waste sorting knowledge also had an indirect influence on residents’ waste sorting intention through attitudes and perceived behavioral control. Additionally, this research corroborated the discrepancy between waste sorting intention and behavior, and suggested that the link between intention and behavior was contingent on incentive measures. Incentive measures strengthened the effect of intention on behavior. This research is useful for understanding residents’ waste sorting intention and behavior and valuable for encouraging residents to sort waste in their daily lives.
SignalP is the currently most widely used program for prediction of signal peptides from amino acid sequences. Proteins with signal peptides are targeted to the secretory pathway, but are not ...necessarily secreted. After a brief introduction to the biology of signal peptides and the history of signal peptide prediction, this chapter will describe all the options of the current version of SignalP and the details of the output from the program. The chapter includes a case study where the scores of SignalP were used in a novel way to predict the functional effects of amino acid substitutions in signal peptides.
The PDZ-domain-containing sorting nexin 27 (SNX27) promotes recycling of internalized transmembrane proteins from endosomes to the plasma membrane by linking PDZ-dependent cargo recognition to ...retromer-mediated transport. Here, we employed quantitative proteomics of the SNX27 interactome and quantification of the surface proteome of SNX27- and retromer-suppressed cells to dissect the assembly of the SNX27 complex and provide an unbiased global view of SNX27-mediated sorting. Over 100 cell surface proteins, many of which interact with SNX27, including the glucose transporter GLUT1, the Menkes disease copper transporter ATP7A, various zinc and amino acid transporters, and numerous signalling receptors, require SNX27-retromer to prevent lysosomal degradation and maintain surface levels. Furthermore, we establish that direct interaction of the SNX27 PDZ domain with the retromer subunit VPS26 is necessary and sufficient to prevent lysosomal entry of SNX27 cargo. Our data identify the SNX27-retromer as a major endosomal recycling hub required to maintain cellular nutrient homeostasis.
The mammalian genome encodes 49 proteins that possess a PX (phox-homology) domain, responsible for membrane attachment to organelles of the secretory and endocytic system via binding of ...phosphoinositide lipids. The PX domain proteins, most of which are classified as SNXs (sorting nexins), constitute an extremely diverse family of molecules that play varied roles in membrane trafficking, cell signalling, membrane remodelling and organelle motility. In the present review, we present an overview of the family, incorporating recent functional and structural insights, and propose an updated classification of the proteins into distinct subfamilies on the basis of these insights. Almost all PX domain proteins bind PtdIns3P and are recruited to early endosomal membranes. Although other specificities and localizations have been reported for a select few family members, the molecular basis for binding to other lipids is still not clear. The PX domain is also emerging as an important protein-protein interaction domain, binding endocytic and exocytic machinery, transmembrane proteins and many other molecules. A comprehensive survey of the molecular interactions governed by PX proteins highlights the functional diversity of the family as trafficking cargo adaptors and membrane-associated scaffolds regulating cell signalling. Finally, we examine the mounting evidence linking PX proteins to different disorders, in particular focusing on their emerging importance in both pathogen invasion and amyloid production in Alzheimer's disease.
To ensure security, image encryption algorithms generally include two stages: permutation and diffusion. The traditional image permutation algorithms include the sort-based permutation algorithm, ...Arnold-based permutation algorithm, Baker-based permutation algorithm and the cyclic shift permutation algorithm, etc. However, these algorithms have the disadvantages of either high time complexity or poor permutation performance. Therefore, in combination with cyclic shift and sorting, this paper proposes a permutation algorithm that can not only guarantees good permutation performance but also guarantee low time and space complexity. Most importantly, this paper proposes a parallel diffusion method. This method ensures the parallelism of diffusion to the utmost extent and achieves a qualitative improvement in efficiency over traditional streaming diffusion methods. Finally, combined with the proposed permutation and diffusion, the paper proposes a computational model for parallel image encryption algorithms.
In recent years, the need for emergency resources has dramatically increased and it has caused an overcrowding problem for the emergency department (ED). Solving this problem by increasing medical ...resources is either impractical or infeasible. Thus, this manuscript develops a multi-objective mathematical model to allocate medical resources for the emergency department (ED). The optimal resource allocation is exploited by using some meta-heuristic algorithms, i.e., fast and elitism non-dominated sorting genetic algorithm (NSGA II), non-dominated sorting particle swarm algorithm (NSPSO), and non-dominated sorting differential evolution (NSDE). Thereafter, a dynamic simulation model, which embeds the solutions from the resource allocation model in the simulation process, is constructed. Each feasible solution from the three meta-heuristic algorithms is simulated to estimate the performance of the resources allocated in terms of the average service level and staff utilization. The results show that the performance of the NSGAII, where the average service level and staff utilization for the current resources are 0.844 and 0.751, respectively, is better than those of NSPSO and NSDE. Besides, the number of medical staff gives a significant effect on the service level and utilization while the number of beds only impacts staff utilization. The simulation model can find out that the best combination of the number of staff and the number of beds is from 1 to 10 staffs and 1–6 beds to maximize the utilization and service level.
Spikesorting is crucial in studying neural individually and synergistically encoding and decoding behaviors. However, existent spike sorting algorithms perform unsatisfactorily in real scenarios ...where heavy noises and overlapping samples are commonly in the spikes, and the spikes from different neurons are similar. To address such challenging scenarios, we propose an automatic spike sporting method in this paper, which integrally combines low-rank and sparse representation (LRSR) into a unified model. In particular, LRSR models spikes through low-rank optimization, uncovering global data structure for handling similar and overlapped samples. To eliminate the influence of the embedded noises, LRSR uses a sparse constraint, effectively separating spikes from noise. The optimization is solved using alternate augmented Lagrange multipliers methods. Moreover, we conclude with an automatic spike-sorting framework that employs the spectral clustering theorem to estimate the number of neurons. Extensive experiments over various simulated and real-world datasets demonstrate that our proposed method, LRSR, can handle spike sorting effectively and efficiently.
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