Recognition of phosphatidylserine (PS) lipids exposed on the extracellular leaflet of plasma membranes is implicated in both apoptotic cell removal and immune regulation. The PS receptor T cell immunoglobulin and mucin-domain-containing molecule 4 (Tim4) regulates T-cell immunity via phagocytosis of both apoptotic (high PS exposure) and nonapoptotic (intermediate PS exposure) activated T cells. The latter population must be removed at lower efficiency to sensitively control immune tolerance and memory cell population size, but the molecular basis for how Tim4 achieves this sensitivity is unknown. Using a combination of interfacial X-ray scattering, molecular dynamics simulations, and membrane binding assays, we demonstrate how Tim4 recognizes PS in the context of a lipid bilayer. Our data reveal that in addition to the known Ca 2+ -coordinated, single-PS binding pocket, Tim4 has four weaker sites of potential ionic interactions with PS lipids. This organization makes Tim4 sensitive to PS surface concentration in a manner capable of supporting differential recognition on the basis of PS exposure level. The structurally homologous, but functionally distinct, Tim1 and Tim3 are significantly less sensitive to PS surface density, likely reflecting the differences in immunological function between the Tim proteins. These results establish the potential for lipid membrane parameters, such as PS surface density, to play a critical role in facilitating selective recognition of PSexposing cells. Furthermore, our multidisciplinary approach overcomes the difficulties associated with characterizing dynamic protein/membrane systems to reveal the molecular mechanisms underlying Tim4's recognition properties, and thereby provides an approach capable of providing atomic-level detail to uncover the nuances of protein/membrane interactions. differential membrane recognition | PS recognition

important, as it may assist in designing channelrhodopsin variants with specific properties for optogenetics applications. To dissect structural elements that may act as gates and to explore how protein and water dynamics respond to changes in the protonation state, we combined extensive bioinformatics analyses with molecular dynamics simulations of channelrhodopsin and of bacteriorhodopsin mutants that model specific channelrhodopsin interactions, or have altered proton-transfer kinetics. In some of these mutants, we find that perturbation of specific hydrogen bonds is coupled to the rapid formation of water bridges that could assist proton transfer. In simulations on channelrhodopsin embedded in hydrated lipid membranes, the dynamics of water wires and hydrogen bonds inter-connecting remote regions of the protein are tightly coupled to the protonation state.

Quinoprotein glucose dehydrogenase (GDH) is the most important enzyme of inorganic phosphorus-dissolving metabolism, catalyzing the oxidation of glucose to gluconic acid. The insoluble phosphate in the sediment is converted into soluble phosphate, facilitating mass reproduction of algae. Therefore, studying the diversity of gcd genes which encode GDH is beneficial to reveal the microbial group that has a significant influence on the eutrophication of water. Taking the eutrophic Sancha Lake sediments as the research object, we acquired samples from six sites in the spring and autumn. A total of 219,778 high-quality sequences were obtained by DNA extraction of microbial groups in sediments, PCR amplification of the gcd gene, and high-throughput sequencing. Six phyla, nine classes, 15 orders, 29 families, 46 genera, and 610 operational taxonomic units (OTUs) were determined, suggesting the high genetic diversity of gcd. Gcd genes came mainly from the genera of Rhizobium (1.63–77.99%), Ensifer (0.13–56.95%), Shinella (0.32–25.49%), and Sinorhizobium (0.16–11.88%) in the phylum of Proteobacteria (25.10–98.85%). The abundance of these dominant gcd-harboring bacteria was higher in the spring than in autumn, suggesting that they have an important effect on the eutrophication of the Sancha Lake. The alpha and beta diversity of gcd genes presented spatial and temporal differences due to different sampling site types and sampling seasons. Pearson correlation analysis and canonical correlation analysis (CCA) showed that the diversity and abundance of gcd genes were significantly correlated with environmental factors such as dissolved oxygen (DO), phosphorus hydrochloride (HCl–P), and dissolved total phosphorus (DTP). OTU composition was significantly correlated with DO, total organic carbon (TOC), and DTP. GDH encoded by gcd genes transformed insoluble phosphate into dissolved phosphate, resulting in the eutrophication of Sancha Lake. The results suggest that gcd genes encoding GDH may play an important role in lake eutrophication.

The dynamic nature of lipid membranes presents significant challenges with respect to understanding the molecular basis of protein/membrane interactions. Consequently, there is relatively little known about the structural mechanisms by which membrane-binding proteins might distinguish subtle variations in lipid membrane composition and/or structure. We have previously developed a multidisciplinary approach that combines molecular dynamics simulation with interfacial x-ray scattering experiments to produce an atomistic model for phosphatidylserine recognition by the immune receptor Tim4. However, this approach requires a previously determined protein crystal structure in a membrane-bound conformation. Tim1, a Tim4 homolog with distinct differences in both immunological function and sensitivity to membrane composition, was crystalized in a closed-loop conformation that is unlikely to support membrane binding. Here we have used a previously described highly mobile membrane mimetic membrane in combination with a conventional lipid bilayer model to generate a membrane-bound configuration of Tim1 in silico. This refined structure provided a significantly improved fit of experimental x-ray reflectivity data. Moreover, the coupling of the x-ray reflectivity analysis with both highly mobile membrane mimetic membranes and conventional lipid bilayer molecular dynamics simulations yielded a dynamic model of phosphatidylserine membrane recognition by Tim1 with atomic-level detail. In addition to providing, to our knowledge, new insights into the molecular mechanisms that distinguish the various Tim receptors, these results demonstrate that in silico membrane-binding simulations can remove the requirement that the existing crystal structure be in the membrane-bound conformation for effective x-ray reflectivity analysis. Consequently, this refined methodology has the potential for much broader applicability with respect to defining the atomistic details of membrane-binding proteins.

There is a diverse class of peripheral membrane-binding proteins that specifically bind phosphatidylserine (PS), a lipid that signals apoptosis or cell fusion depending on the membrane context of its presentation. PS-receptors are specialized for particular PS-presenting pathways, indicating that they might be sensitive to the membrane context. In this review, we describe a combination of thermodynamic, structural, and computational techniques that can be used to investigate the mechanisms underlying this sensitivity. As an example, we focus on three PS-receptors of the T-cell Immunoglobulin and Mucin containing (TIM) protein family, which we have previously shown to differ in their sensitivity to PS surface density.