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At least 1,009 records · Page 56

Cognitive Model of Trust Dynamics Predicts Human Behavior within and between Two Games of Strategic Interaction with Computerized Confederate Agents

When playing games of strategic interaction, such as iterated Prisoner’s Dilemma and iterated Chicken Game, people exhibit specific within-game learning (e.g., learning a game’s optimal outcome) as well as transfer of learning between games (e.g., a game’s optimal outcome occurring at a higher proportion when played after another game). The reciprocal trust players develop during the first game is thought to mediate transfer of learning effects. Recently, a computational cognitive model using a novel trust mechanism has been shown to account for human behavior in both games, including the transfer between games. We present the results of a study in which we evaluate the model’s a priori predictions of human learning and transfer in 16 different conditions. The model’s predictive validity is compared against five model variants that lacked a trust mechanism. The results suggest that a trust mechanism is necessary to explain human behavior across multiple conditions, even when a human plays against a non-human agent. The addition of a trust mechanism to the other learning mechanisms within the cognitive architecture, such as sequence learning, instance-based learning, and utility learning, leads to better prediction of the empirical data. It is argued that computational cognitive modeling is a useful tool for studying trust development, calibration, and repair.

59 BASIC BIOLOGICAL SCIENCES↗

Hydrogen bonded trimesic acid networks on Cu(111) reveal how basic chemical properties are imprinted in HR-AFM images

High resolution non-contact atomic force microscopy measurements characterize assemblies of trimesic acid molecules on Cu(111) and the link group interactions, providing the first fingerprints utilizing CO-based probes for this widely studied paradigm for hydrogen bond driven molecular self assembly. The enhanced submolecular resolution offered by this technique uniquely reveals key aspects of the competing interactions. Accurate comparison between full-density-based modeled images and experiment allows to identify key structural elements in the assembly in terms of the electron-withdrawing character of the carboxylic groups, interactions of those groups with Cu atoms in the surface, and the valence electron density in the intermolecular region of the hydrogen bonds. This study of trimesic acid assemblies on Cu(111) combining high resolution atomic force microscopy measurements with theory and simulation forges clear connections between fundamental chemical properties of molecules and key features imprinted in force images with submolecular resolution.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Comparative genomics and stable isotope analysis reveal the saprotrophic-pathogenic lifestyle of a neotropical fungus

In terrestrial forested ecosystems, fungi may interact with trees in at least three distinct ways: (i) associated with roots as symbionts; (ii) as pathogens in roots, trunks, leaves, flowers, and fruits; or (iii) decomposing dead tree tissues on soil or even on dead tissues in living trees. Distinguishing the latter two nutrition modes is rather difficult in Hymenochaetaceae (Basidiomycota) species. Herein, we have used an integrative approach of comparative genomics, stable isotopes, host tree association, and bioclimatic data to investigate the lifestyle ecology of the scarcely known neotropical genus Phellinotus, focusing on the unique species Phellinotus piptadeniae. This species is strongly associated with living Piptadenia gonoacantha (Fabaceae) trees in the Atlantic Forest domain on a relatively high precipitation gradient. Phylogenomics resolved P. piptadeniae in a clade that also includes both plant pathogens and typical wood saprotrophs. Furthermore, both genome-predicted Carbohydrate-Active Enzymes (CAZy) and stable isotopes (δ 13 C and δ 15 N) revealed a rather flexible lifestyle for the species. Altogether, our findings suggest that P. piptadeniae has been undergoing a pathotrophic specialization in a particular tree species while maintaining all the metabolic repertoire of a wood saprothroph.

59 BASIC BIOLOGICAL SCIENCES↗

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence–function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ~400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

59 BASIC BIOLOGICAL SCIENCES↗

SERTA Domain Containing Protein 1 (SERTAD1) Interacts with Classical Swine Fever Virus Structural Glycoprotein E2, Which Is Involved in Virus Virulence in Swine

E2 is the major structural glycoprotein of the classical swine fever virus (CSFV). E2 has been shown to be involved in important virus functions such as replication and virulence in swine. Using the yeast two-hybrid system, we previously identified several host proteins specifically interacting with CSFV E2. Here, we analyze the protein interaction of E2 with SERTA domain containing protein 1 (SERTAD1), a factor involved in the stimulation of the transcriptional activities of different host genes. We have confirmed that the interaction between these two proteins occurs in CSFV-infected swine cells by using a proximity ligation assay and confocal microscopy. Amino acid residues in the CSFV E2 protein that are responsible for mediating the interaction with SERTAD1 were mapped by a yeast two-hybrid approach using a randomly mutated E2 library. Using that information, a recombinant CSFV mutant (E2ΔSERTAD1v) that harbors substitutions in those residues mediating the protein-interaction with SERTAD1 was developed and used to study the role of the E2-SERTAD1 interaction in viral replication and virulence in swine. CSFV E2ΔSERTAD1v, when compared to the parental BICv, showed a clearly decreased ability to replicate in the SK6 swine cell line and a more severe replication defect in primary swine macrophage cultures. Importantly, 80% of animals infected with E2ΔSERTAD1v survived infection, remaining clinically normal during the 21-day observational period. This result would indicate that the ability of CSFV E2 to bind host SERTAD1 protein during infection plays a critical role in virus virulence.

59 BASIC BIOLOGICAL SCIENCES↗

Evolved Streptavidin Mutants Reveal Key Role of Loop Residue in High-affinity Binding

We have performed a detailed analysis of streptavidin variants with altered specificity towards desthiobiotin. In addition to changes in key residues which widen the ligand binding pocket and accommodate the more structurally flexible desthiobiotin, the data revealed the role of a key, non-active site mutation at the base of the flexible loop (S52G) which slows dissociation of this ligand by approximately sevenfold. Our data suggest that this mutation results in the loss of a stabilizing contact which keeps this loop open and accessible in the absence of ligand. When this mutation was introduced into the wild-type protein, destabilization of the opened loop conferred a {approx}10-fold decrease in both the on-rate and off-rate for the ligand biotin-4-fluoroscein. A similar effect was observed when this mutation was added to a monomeric form of this protein. Our results provide key insight into the role of the streptavidin flexible loop in ligand binding and maintaining high affinity interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Archeological wood conservation with selected organosilicon compounds studied by XFM and nanoindentation

Waterlogged wood conservation is a complex and challenging task. Detailed knowledge about the interactions between the applied chemicals and wood is necessary to ensure the effective and safe conservation of wooden artifacts. The present research aims to determine the mechanism of dimensional stabilization of archeological wood by organosilicon compounds using the combination of synchrotron-based X-ray fluorescence microscopy (XFM) and nanoindentation. Archeological oak wood was treated with methyltrimethoxysilane, (3-mercaptopropyl)trimethoxysilane, or 1,3-bis-[(diethylamino)-3-(propoxy)propan-2-ol]-1,1,3,3-tetramethyldisiloxane, which in previous studies were found to be more effective than other organosilicons in stabilizing wood dimensions. The XFM and nanoindentation results showed that all three organosilicons infiltrated wood cell walls and enhanced their mechanical properties. The XFM also showed that part of the chemicals filled some void spaces like cell lumina. Based on the results obtained here and in our previous research, it is determined that the mechanism of archeological wood dimensional stabilization by organosilicon treatment is complex and likely involves both filling cell lumina and infiltration into cell walls where organosilicons interact with wood polymers.

59 BASIC BIOLOGICAL SCIENCES↗

Kindlin Is Mechanosensitive: Force-Induced Conformational Switch Mediates Cross-Talk among Integrins

Mechanical stresses directly regulate the function of several proteins of the integrin-mediated focal adhesion complex as they experience intra- and extracellular forces. Kindlin is a largely overlooked member of the focal adhesion complex whose roles in cellular mechanotransduction are only recently being identified. Recent crystallographic experiments have revealed that kindlins can form dimers that bind simultaneously to two integrins, providing a mechanistic explanation of how kindlins may promote integrin activation and clustering. In this study, using the newly identified molecular structure, we modeled the response of the kindlin2 dimer in complex with integrin β1 to mechanical cytoskeletal forces on integrins. Using molecular dynamics simulations, we show that forces on integrins are directly transmitted to the kindlin2 dimerization site, resulting in a shift in an R577-S550/E553 interaction network at this site. Under force, R577 on one protomer switches from interacting with S550 to forming new hydrogen bonds with E553 on the neighboring protomer, resulting in the strengthening of the kindlin2 dimer in complex with integrin β1. This force-induced strengthening is similar to the catch-bond mechanisms that have previously been observed in other adhesion molecules. So, based on our results, we propose that the kindlin2 dimer is mechanosensitive and can strengthen integrin-mediated focal adhesions under force by shifting the interactions at its dimerization sites.

59 BASIC BIOLOGICAL SCIENCES↗

Phonon-mediated lipid raft formation in biological membranes

Short-wavelength collective molecular motions, also known as phonons, have recently attracted much interest in revealing dynamic properties of biological membranes through the use of neutron and x-ray scattering, infrared and Raman spectroscopies, and molecular dynamics simulations. Experimentally detecting unique vibrational patterns such as, shear phonon excitations, viscoelastic crossovers, transverse acoustic phonon gaps, and continuous and truncated optical phonon modes in cellular membranes, to name a few, has proven non-trivial. Here, we review recent advances in liquid thermodynamics that have resulted in the development of the phonon theory of 1 liquids. The theory has important predictions regarding the shear vibrational spectra of fluids, namely the emergence of viscoelastic crossovers and transverse acoustic phonon gaps. Furthermore, we show that these vibrational patterns are common in soft (non-crystalline) materials, including, but not limited to liquids, colloids, liquid crystals (mesogens), block copolymers, and biological membranes. The existence of viscoelastic crossovers and acoustic phonon gaps define the self-diffusion properties of cellular membranes and provide a molecular picture of the transient nature of lipid rafts.1 Importantly, the timescales (picoseconds) for the formation and dissolution of transient lipid rafts match the lifetime of the formation and breakdown of interfacial water hydrogen bonds. Apart from acoustic propagating phonon modes, biological membranes can also support more energetic non-propagating optical phonon excitations, also known as standing waves or breathing modes. Importantly, optical phonons can be truncated due to the existence of finite size nanodomains made up of strongly correlated lipid-cholesterol molecular pairs. These strongly coupled molecular pairs can serve as nucleation centers for the formation of stable rafts at larger length scales, due to correlations of spontaneous fluctuations (Onsager’s regression hypothesis). Finally and importantly, molecular level viscoelastic crossovers, acoustic phonon gaps, and continuous and truncated optical phonon modes may offer insights as to how lipid-lipid and lipid-protein interactions enable biological function.

59 BASIC BIOLOGICAL SCIENCES↗

The Survival Motor Neuron Protein Forms Soluble Glycine Zipper Oligomers

The survival motor neuron (SMN) protein forms the oligomeric core of a multiprotein complex that functions in spliceosomal snRNP biogenesis. Loss of function mutations in the SMN gene cause spinal muscular atrophy (SMA), a leading genetic cause of infant mortality. Nearly half of the known SMA patient missense mutations map to the SMN YG-box, a highly conserved oligomerization domain of unknown structure that contains a (YxxG)3 motif. Here, we report that the SMN YG-box forms helical oligomers similar to the glycine zippers found in transmembrane channel proteins. A network of tyrosine-glycine packing between helices drives formation of soluble YG-box oligomers, providing a structural basis for understanding SMN oligomerization and for relating defects in oligomerization to the mutations found in SMA patients. These results have important implications for advancing our understanding of SMN function and glycine zipper-mediated helix-helix interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Genome-driven evolutionary game theory helps understand the rise of metabolic interdependencies in microbial communities

Metabolite exchanges in microbial communities give rise to ecological interactions that govern ecosystem diversity and stability. It is unclear, however, how the rise of these interactions varies across metabolites and organisms. Here we address this question by integrating genome-scale models of metabolism with evolutionary game theory. Specifically, we use microbial fitness values estimated by metabolic models to infer evolutionarily stable interactions in multi-species microbial “games”. We first validate our approach using a well-characterized yeast cheater-cooperator system. We next perform over 80,000 in silico experiments to infer how metabolic interdependencies mediated by amino acid leakage in Escherichia coli vary across 189 amino acid pairs. While most pairs display shared patterns of inter-species interactions, multiple deviations are caused by pleiotropy and epistasis in metabolism. Moreover, simulated invasion experiments reveal possible paths to obligate cross-feeding. Our study provides genomically driven insight into the rise of ecological interactions, with implications for microbiome research and synthetic ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Topology, landscapes, and biomolecular energy transport

While ubiquitous, energy redistribution remains a poorly understood facet of the nonequilibrium thermodynamics of biomolecules. At the molecular level, finite-size effects, pronounced nonlinearities, and ballistic processes produce behavior that diverges from the macroscale. Here, we show that transient thermal transport reflects macromolecular energy landscape architecture through the topological characteristics of molecular contacts and the nonlinear processes that mediate dynamics. While the former determines transport pathways via pairwise interactions, the latter reflects frustration within the landscape for local conformational rearrangements. Unlike transport through small-molecule systems, such as alkanes, nonlinearity dominates over coherent processes at even quite short time- and length-scales. Our exhaustive all-atom simulations and novel local-in-time and space analysis, applicable to both theory and experiment, permit dissection of energy migration in biomolecules. The approach demonstrates that vibrational energy transport can probe otherwise inaccessible aspects of macromolecular dynamics and interactions that underly biological function.

59 BASIC BIOLOGICAL SCIENCES↗

A machine learning approach to predict metabolic pathway dynamics from time-series multiomics data

New synthetic biology capabilities hold the promise of dramatically improving our ability to engineer biological systems. However, a fundamental hurdle in realizing this potential is our inability to accurately predict biological behavior after modifying the corresponding genotype. Kinetic models have traditionally been used to predict pathway dynamics in bioengineered systems, but they take significant time to develop, and rely heavily on domain expertise. Here, we show that the combination of machine learning and abundant multiomics data (proteomics and metabolomics) can be used to effectively predict pathway dynamics in an automated fashion. The new method outperforms a classical kinetic model, and produces qualitative and quantitative predictions that can be used to productively guide bioengineering efforts. This method systematically leverages arbitrary amounts of new data to improve predictions, and does not assume any particular interactions, but rather implicitly chooses the most predictive ones.

59 BASIC BIOLOGICAL SCIENCES↗

The ER stress sensor PERK luminal domain functions as a molecular chaperone to interact with misfolded proteins

PERK is one of the major sensor proteins which can detect the protein-folding imbalance generated by endoplasmic reticulum (ER) stress. It remains unclear how the sensor protein PERK is activated by ER stress. It has been demonstrated that the PERK luminal domain can recognize and selectively interact with misfolded proteins but not native proteins. Moreover, the PERK luminal domain may function as a molecular chaperone to directly bind to and suppress the aggregation of a number of misfolded model proteins. The data strongly support the hypothesis that the PERK luminal domain can interact directly with misfolded proteins to induce ER stress signaling. To illustrate the mechanism by which the PERK luminal domain interacts with misfolded proteins, the crystal structure of the human PERK luminal domain was determined to 3.2 Å resolution. Two dimers of the PERK luminal domain constitute a tetramer in the asymmetric unit. Superimposition of the PERK luminal domain molecules indicated that the β-sandwich domain could adopt multiple conformations. It is hypothesized that the PERK luminal domain may utilize its flexible β-sandwich domain to recognize and interact with a broad range of misfolded proteins.

59 BASIC BIOLOGICAL SCIENCES↗

The Influence of Bacteria on the Growth, Lipid Production, and Extracellular Metabolite Accumulation by Phaeodactylum tricornutum (Bacillariophyceae)

Here, to examine the impact of heterotrophic bacteria on microalgal physiology, we co-cultured the diatom Phaeodactylum tricornutum with six bacterial strains to quantify bacteria-mediated differences in algal biomass, total intracellular lipids, and for a subset, extracellular metabolite accumulation. A Marinobacter isolate significantly increased algal cell concentrations, dry biomass, and lipid content compared to axenic algal cultures. Two other bacterial strains from the Bacteroidetes order, of the genera Algoriphagus and Muricauda, significantly lowered P. tricornutum biomass, leading to overall decreased lipid accumulation. These three bacterial co-cultures (one mutualistic, two competitive) were analyzed for extracellular metabolites via untargeted liquid chromatography mass spectrometry to compare against bacteria-free cultures. Over 80% of the extracellular metabolites differentially abundant in at least one treatment were in higher concentrations in the axenic cultures, in agreement with the hypothesis that the co-cultured bacteria incorporated algal-derived organic compounds for growth. Furthermore, the extracellular metabolite profiles of the two growth-inhibiting cultures were more similar to one another than the growth-promoting co-culture, linking metabolite patterns to ecological role. Our results show that algal–bacterial interactions can influence the accumulation of intracellular lipids and extracellular metabolites, and suggest that utilization and accumulation of compounds outside the cell play a role in regulating microbial interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Predicting drug-metagenome interactions: Variation in the microbial β-glucuronidase level in the human gut metagenomes

Characterizing the gut microbiota in terms of their capacity to interfere with drug metabolism is necessary to achieve drug efficacy and safety. Although examples of drug-microbiome interactions are well-documented, little has been reported about a computational pipeline for systematically identifying and characterizing bacterial enzymes that process particular classes of drugs. The goal of our study is to develop a computational approach that compiles drugs whose metabolism may be influenced by a particular class of microbial enzymes and that quantifies the variability in the collective level of those enzymes among individuals. The present paper describes this approach, with microbial β-glucuronidases as an example, which break down drug-glucuronide conjugates and reactivate the drugs or their metabolites. We identified 100 medications that may be metabolized by β-glucuronidases from the gut microbiome. These medications included morphine, estrogen, ibuprofen, midazolam, and their structural analogues. The analysis of metagenomic data available through the Sequence Read Archive (SRA) showed that the level of β-glucuronidase in the gut metagenomes was higher in males than in females, which provides a potential explanation for the sex-based differences in efficacy and toxicity for several drugs, reported in previous studies. Our analysis also showed that infant gut metagenomes at birth and 12 months of age have higher levels of β-glucuronidase than the metagenomes of their mothers and the implication of this observed variability was discussed in the context of breastfeeding as well as infant hyperbilirubinemia. Overall, despite important limitations discussed in this paper, our analysis provided useful insights on the role of the human gut metagenome in the variability in drug response among individuals. Importantly, this approach exploits drug and metagenome data available in public databases as well as open-source cheminformatics and bioinformatics tools to predict drug-metagenome interactions.

59 BASIC BIOLOGICAL SCIENCES↗

The microbiome of a Pacific moon jellyfish Aurelia coerulea

The impact of microbiome in animal physiology is well appreciated, but characterization of animal-microbe symbiosis in marine environments remains a growing need. This study characterizes the microbial communities associated with the moon jellyfish Aurelia coerulea, first isolated from the East Pacific Ocean and has since been utilized as an experimental system. We find that the microbiome of this Pacific Aurelia culture is dominated by two taxa, a Mollicutes and Rickettsiales. The microbiome is stable across life stages, although composition varies. Mining the host sequencing data, we assembled the bacterial metagenome-assembled genomes (MAGs). The bacterial MAGs are highly reduced, and predict a high metabolic dependence on the host. Analysis using multiple metrics suggest that both bacteria are likely new species. We therefore propose the names Ca. Mariplasma lunae (Mollicutes) and Ca. Marinirickettsia aquamalans (Rickettsiales). Finally, comparison with studies of Aurelia from other geographical populations suggests the association with Ca. Mariplasma lunae occurs in Aurelia from multiple geographical locations. The low-diversity microbiome of Aurelia provides a relatively simple system to study host-microbe interactions.

59 BASIC BIOLOGICAL SCIENCES↗

A dynamic interplay between membranes and the cytoskeleton critical for cell development and signaling

Diverse cellular processes that underlie plant development and response to environmental cues rely on a dynamic interplay between membranes and the cytoskeleton. The original research and review articles assembled in this Research Topic provide a valuable insight into our current understanding of how actin filaments and microtubules physically and functionally interact with membranes and cell wall and vice versa.

59 BASIC BIOLOGICAL SCIENCES↗